Marisa Lousada | speech-language therapy | Best Researcher Award

Published on by Phenomenological Research Awards

Prof. Marisa Lousada | speech-language therapy | Best Researcher Award

Coordinator Professor with Habilitation at University of Aveiro, Portugal.

Prof. Dr. Marisa Lousada 🇵🇹 is a distinguished Coordinator Professor with Habilitation in Health Sciences at the University of Aveiro, Portugal 🏫. She specializes in speech-language therapy and has significantly contributed to clinical research, teaching, and program leadership 👩‍🏫📚. As Head of the Master’s Program in Speech Therapy and an executive board member, she fosters societal cooperation and knowledge transfer 🌍🤝. A prolific researcher, she is a member of the RISE-Health Unit and has authored over 45 journal articles, 10 book chapters, and multiple technical resources 📖🧪. Prof. Lousada has secured major competitive grants, mentored PhD and MSc students 🎓, and actively serves the academic and clinical community through editorial roles and scientific committees 📝. Her work in speech-language pathology, particularly in autism, language disorders, and phonological therapy, has earned her national recognition 🏅. She is deeply committed to innovation, social inclusion, and interdisciplinary research 🔬💬.

Professional Profile:

Scopus

ORCID

Google Scholar

✅Suitability For Best Researcher Award – Prof. Marisa Lousada

Prof. Dr. Marisa Lousada is highly suitable for the Best Researcher Award based on her outstanding academic, research, and leadership credentials in Speech-Language Therapy and Health Sciences. With a career marked by interdisciplinary research, social innovation, and public health impact, she exemplifies the qualities sought in an exceptional researcher.

📘 Education & Qualifications

Dr. Marisa Lousada holds an extensive academic background in health and speech sciences 🎓. She earned her Habilitation in Health Sciences from the University of Aveiro in 2024 🧑‍🏫, after previously completing her Ph.D. in Health Sciences and Technologies at the same university in 2012 🧬. Prior to that, she earned her Master’s degree in Speech and Hearing Sciences from the University of Aveiro in 2006 👩‍🔬, and began her academic journey with a BSc in Speech-Language Therapy from the Alcoitão School of Health Sciences in 2002 🗣️. Her continuous academic progression reflects her dedication to deepening her expertise and advancing the field of speech therapy 📚✨.

🚀 Professional Development 

Prof. Dr. Marisa Lousada has steadily built an exemplary academic and professional profile in the fields of speech-language therapy and health sciences 🌟🗣️. Currently a Coordinator Professor with Habilitation at the University of Aveiro, she leads the Master’s Program in Speech Therapy and serves on the executive board responsible for knowledge transfer and entrepreneurship 💼💡. She’s also a vital contributor to the RISE-Health research unit, where she supports projects in primary health care and language development 🧠👶. Beyond teaching undergraduate to Ph.D. programs 🎓, she has supervised over 50 master’s and 10 doctoral students, shaping future leaders in her field 👩‍🏫. Dr. Lousada actively participates in national academic evaluations and contributes to curricular development with the Higher Education Accreditation Agency (A3ES) 🇵🇹📊. Her multidimensional engagement—research, leadership, supervision, and public engagement—highlights her as a key figure in health education and speech-language innovation 🔍🔊.

🔬 Research Focus

Dr. Lousada’s research primarily lies within clinical linguistics, speech-language therapy, and developmental communication disorders 🗣️👧🧠. Her work focuses on intervention strategies for children with speech and language impairments, especially those with autism spectrum disorder (ASD), developmental language disorder (DLD), and phonological disorders 👩‍⚕️🧩. She is the Principal Investigator of multiple funded projects exploring the effectiveness of therapeutic programs like the Fonolexis and PICP 🎯📊. Dr. Lousada’s research also extends to early childhood literacy, multilingual development, digital communication tools, and healthcare communication for marginalized populations (e.g., refugees and migrant mothers) 🌍👩‍🍼. She integrates mixed-methods research, cross-sectional surveys, and clinical trials in real-world health settings, contributing to impactful and inclusive speech-language therapy solutions 🧪🧾. Her contributions directly support educational equity, child development, and social innovation through evidence-based practices 🌟📈.

🧠 Research Skill

Dr. Marisa Lousada possesses robust skills in clinical trials, psychometric evaluation, intervention program development, and translational research 📉🧪📋. She specializes in developing, validating, and applying standardized assessment tools for speech-language impairments, especially in preschool-aged children 🧒📏. Her expertise includes designing mixed-method studies, conducting randomized controlled and quasi-experimental trials, and performing systematic reviews with high methodological rigor 🔎📚. As a co-editor and author of technical manuals and applications, she blends theory with clinical utility to ensure practical impact 🔧📘. She is adept at supervising complex theses and leading multidisciplinary teams to solve communication-related health challenges 👥🔬. Her involvement in community outreach, program evaluation, and digital health innovations (e.g., mHealth tools for vocal health) showcases her adaptability and forward-thinking approach in health sciences and speech therapy 🎤📲.

🏅 Awards & Honors

Dr. Lousada’s contributions have earned her numerous prestigious awards 🏆. In 2023, she received the Scientific Merit Award from the Portuguese Society of Speech Therapy and the Cooperation Award from the University of Aveiro (€4000) 🤝🎓. She also won the Dr. Maria Lutegarda Scientific Research Award twice (2021 and 2023) and the 1st Social Innovation Award at ARRISCA C for a pioneering business idea (€3500) 💡🥇. Her collaborative works have received top honors, including the Best Oral Communication Award at the Young Researchers Conference (2022) and Best Scientific Article Award from the Portuguese Journal of Speech Therapy 🗣️📜. These recognitions highlight her research excellence, innovation, and deep commitment to social impact and academic leadership 📈👩‍🏫

Publication Top Notes

1. Teste fonético-fonológico ALPE

Authors: A. Mendes, E. Afonso, M. Lousada, F. Andrade
Published: 2013, Aveiro: Edubox
Citations: 119
Summary:
This publication presents the ALPE phonetic-phonological test, a standardized assessment tool developed in Portuguese to evaluate phonetic and phonological disorders in children. The test is used by speech-language therapists to diagnose and plan appropriate interventions. It offers a structured format to assess speech production skills, with a particular focus on segmental and suprasegmental phonological components.

2. Generalization and maintenance of treatment gains in primary progressive aphasia (PPA): a systematic review

Authors: I. Cadório, M. Lousada, P. Martins, D. Figueiredo
Published: 2017, International Journal of Language & Communication Disorders, 52(5), 543–560
Citations: 102
Summary:
This systematic review examines how treatment effects in Primary Progressive Aphasia (PPA) are generalized to untrained contexts and maintained over time. It categorizes studies by intervention type, outcome measures, and follow-up duration.

3. Intelligibility as a clinical outcome measure following intervention with children with phonologically based speech–sound disorders

Authors: M. Lousada, L.M.T. Jesus, A. Hall, V. Joffe
Published: 2014, International Journal of Language & Communication Disorders, 49(5), 584–601
Citations: 86
Summary:
This study investigates the effectiveness of intervention programs for children with phonologically based speech-sound disorders (SSD) by using intelligibility as a clinical outcome.

4. Phonological and articulation treatment approaches in Portuguese children with speech and language impairments: A randomized controlled intervention study

Authors: M. Lousada, L.M.T. Jesus, S. Capelas, C. Margaça, D. Simões, A. Valente, et al.
Published: 2013, International Journal of Language & Communication Disorders, 48(2), 172–187
Citations: 83
Summary:
A randomized controlled trial comparing phonological vs. articulation therapy approaches in Portuguese-speaking children with SSD.

5. The clinical practice of speech and language therapists with children with phonologically based speech sound disorders

Authors: C. Oliveira, M. Lousada, L.M.T. Jesus
Published: 2015, Child Language Teaching and Therapy, 31(2), 173–194
Citations: 72
Summary:
This study surveys clinical practices among speech-language therapists (SLTs) in treating children with phonologically based SSDs in Portugal. It examines decision-making, intervention approaches, and outcome evaluation.

🏁 Conclusion

Prof. Dr. Marisa Lousada’s scientific rigor, clinical relevance, and societal impact collectively establish her as a leading figure in health research and speech-language therapy. Her multifaceted contributions—in research, education, innovation, and social responsibility—make her a strong and deserving candidate for the Best Researcher Award.

Abdullah Al Mamun | Machine Learning | Young Scientist Award

Published on by Phenomenological Research Awards

Mr. Abdullah Al Mamun | Machine Learning | Young Scientist Award

Lecturer at Dhaka University of Engineering & Technology (DUET), Gazipur, Bangladesh.

Abdullah Al Mamun is an emerging researcher and academic professional 🌟 specializing in cutting-edge fields like IoT and Sustainability, Machine Learning, Computer Vision, and Explainable Artificial Intelligence 🤖🌿. Currently serving as a Lecturer at the Model Institute of Science and Technology in Gazipur, he is also pursuing his Master of Science in Computer Science and Engineering at Dhaka University of Engineering & Technology (DUET) 🎓. He has authored multiple peer-reviewed journal and conference papers 📚, many of which are published in IEEE and MDPI journals. Abdullah has been actively involved in several national and international research projects and has collaborated with scholars globally 🌐. His drive to explore solutions for environmental monitoring, medical diagnostics, and smart systems using intelligent technology sets him apart 🚀. Outside of academia, Abdullah engages in social volunteering, tech events, and academic clubs, continuously contributing to the student and research community 💡👥.

Professional Profile:

Google Scholar

Suitability for Young Scientist Award – Mr. Abdullah Al Mamun

Abdullah Al Mamun is an exceptionally promising early-career researcher and educator whose work spans IoT, Sustainability, Machine Learning, Computer Vision, and Explainable AI. His multidisciplinary contributions, especially in the areas of environmental monitoring, healthcare systems, and smart technologies, exhibit both innovation and societal relevance—key elements sought in a Young Scientist Awardee. His academic journey, technical expertise, international collaborations, and impactful project involvement establish him as a capable and committed scientist at the frontier of modern computing and intelligent systems.

📘 Education

Abdullah Al Mamun earned his Bachelor of Science in Computer Science and Engineering from Dhaka University of Engineering & Technology (DUET), Gazipur 🎓💻. Currently, he is pursuing his Master of Science in Engineering in the same department at DUET (2024–Present) 🎓🧠. His academic focus is rooted in data-driven research, intelligent systems, and digital sustainability 🌱📊. With a CGPA of 3.64 in the final 21.25 credits, Abdullah shows consistent improvement and dedication to advanced technical learning 📈🧑‍💻.

🧑‍💼 Professional Development 

Abdullah Al Mamun has accumulated diverse professional experiences in both academia and the tech industry 🧑‍🏫💼. Currently, he is working as a Lecturer in the Department of CSE at the Model Institute of Science and Technology, Gazipur 🎓. He has served as a Research Assistant in South Korea’s Woosong University under the Multimedia Signal & Image Processing Group 🌐🖼️. In addition, he worked as a Tutor for over 3 years, teaching programming, data structures, and system analysis 📚👨‍🏫. He also completed internships in web development and CMS-based platforms, gaining practical expertise in frontend and backend tools like HTML, CSS, JavaScript, PHP, and WordPress 💻🔧. He has contributed to government-funded projects like LICT and EDGE, further solidifying his experience in IT and system development for public infrastructure 🏛️🇧🇩.

🧪 Research Focus 

Abdullah’s research focus lies primarily at the intersection of IoT and environmental sustainability 🌍, Machine Learning and Artificial Intelligence 🤖, and Computer Vision and Explainable AI 👁️🔍. His projects include smart solar monitoring, child safety systems, and efficient deep learning models for medical applications like skin cancer detection 🏥⚡. He aims to address real-world challenges through scalable, intelligent technologies that enhance both safety and efficiency in smart cities and healthcare systems 🏙️🚑. His recent work under review explores mental health classification in Thalassemia patients, digital land monitoring, and cyber intrusion detection—illustrating a commitment to data ethics and sustainable innovation 🔐📊. With a mix of theoretical foundations and practical system implementations, Abdullah’s research contributes significantly to modern computational solutions in healthtech, sustainability, and cybersecurity 🌐💡.

🛠️ Research Skills

Abdullah possesses a diverse and robust research skill set 🎯. His core technical skills include Python programming 🐍, machine learning models 🤖, deep learning frameworks like YOLOv8 🎯, and simulation tools such as Origin, Matplotlib, and Seaborn 📊. He is proficient in both supervised and unsupervised learning, especially in outlier detection, parameter optimization, and data visualization 🧠🖼️. His hands-on work with Arduino, image processing, and web-based monitoring systems demonstrates strong integration of hardware-software synergy 🔧💻. He is also adept in Explainable AI, which enhances transparency in decision-making algorithms 🔍🧾. Abdullah’s ability to manage end-to-end pipelines from data collection to model deployment, along with experience in collaborative and interdisciplinary projects, sets a strong foundation for innovative research 🌐🔬. His publications and ongoing research underline his capabilities in academic writing, critical thinking, and experimental design 📚🧪.

🏅 Awards and Honors

Abdullah has earned recognition for his academic and technical excellence 🏆🎖️. He won the Second Runner-Up prize at BEYOND THE METRICS-2023, hosted by the Department of Business and Technology Management, IUT 🌍📈. He was also the Runner-Up in the Intra DUET Programming Contest (IDPC) 2022 organized by DUET’s CSE Department 🧑‍💻🥈. Additionally, he has participated and been selected in prestigious competitions such as the NASA Space App Challenge 2024 🚀, DUET TECH FEST, and ROBO MANIA 🤖. These accolades reflect his commitment to innovation, teamwork, and competitive programming skills 🌟💡.

Publication Top Notes

1. Software Defects Identification: Results using Machine Learning and Explainable Artificial Intelligence Techniques

  • Authors: M. Begum, M.H. Shuvo, I. Ashraf, A. Al Mamun, J. Uddin, M.A. Samad

  • Published in: IEEE Access, Volume 11, Pages 132750-132765

  • Year: 2023

  • Citations: 13

  • Summary:
    This paper investigates how machine learning (ML) and explainable artificial intelligence (XAI) methods can enhance the identification of software defects. The study uses multiple ML models (such as Random Forest, SVM, and XGBoost) and applies explainability techniques (e.g., SHAP, LIME) to interpret model decisions. The results show improved defect prediction accuracy and transparency, contributing to software reliability and maintainability.

2. Developed an IoT-Based Smart Solar Energy Monitoring System for Environmental Sustainability

  • Authors: A. Al Mamun, M.H. Shuvo, T. Islam, D. Islam, M.J. Islam, F.A. Tanvir

  • Published in: 2024 3rd International Conference on Advancement in Electrical and Electronic Engineering (ICAEEE)

  • Year: 2024

  • Citations: 4

  • Summary:
    This paper presents an Internet of Things (IoT)-enabled smart solar energy monitoring system. The system tracks and analyzes real-time data such as voltage, current, and energy output to promote environmental sustainability and efficient energy usage. Cloud-based dashboards and mobile alerts enhance usability. The innovation supports green energy adoption, especially in remote or resource-limited areas.

3. Developing an IoT-Based Child Safety and Monitoring System: An Efficient Approach

  • Authors: K.I. Masud, M.H. Shuvo, A. Al Mamun, J. Mallick, M.R. Jannat, M.O. Rahman

  • Published in: 2023 26th International Conference on Computer and Information Technology (ICCIT)

  • Year: 2023

  • Citations: 4

  • Summary:
    This paper proposes an IoT-driven child safety and monitoring system that integrates GPS tracking, wearable sensors, and mobile app notifications. Designed to prevent child abduction and accidents, the system provides real-time location updates and safety alerts to parents or guardians. The study highlights its effectiveness, low cost, and adaptability in both urban and rural settings.

4. Internet of Things (IoT)-Based Solutions for Uneven Roads and Balanced Vehicle Systems Using YOLOv8

  • Authors: M. Begum, A.K.I. Riad, A.A. Mamun, T. Hossen, S. Uddin, M.N. Absur, …

  • Published in: Future Internet, Volume 17, Issue 6, Article 254

  • Year: 2025

  • Summary:
    This study introduces an IoT-based system that leverages the YOLOv8 deep learning model to detect road anomalies such as potholes and bumps. The system uses real-time video analytics and onboard sensors to inform vehicle control systems, improving passenger comfort and road safety. The approach demonstrates high accuracy and responsiveness in urban mobility applications.

🏁 Conclusion

Abdullah Al Mamun is highly suitable for the Young Scientist Award. His commitment to solving critical real-world problems through interdisciplinary research, coupled with his consistent academic performance, global exposure, and technical leadership, make him an outstanding candidate. His trajectory clearly reflects the potential to become a thought leader in the fields of AI for sustainability and healthcare, justifying recognition through this prestigious award.

Hongchen Wu | Computer Science | Best Researcher Award

Published on by Phenomenological Research Awards

Prof. Hongchen Wu | Computer Science | Best Researcher Award

Associate Professor at Shandong Normal University, China.

Dr. Hongchen Wu 🌏💻 is an associate professor in the School of Information Science & Engineering at Shandong Normal University. After earning his Ph.D. in Computer Science & Technology in 2016—supplemented by a two‑year joint Ph.D. stay at the University of California, Irvine—he has built a vibrant career at the crossroads of next‑generation Internet, information security, and AI‑driven data science. Wu leads multiple national and provincial projects on cross‑domain recommendation, privacy management, and online‑payment fraud, publishing widely in Neurocomputing, Information Processing & Management, IEEE Access, and other high‑impact venues. A committee member of the China Computer Federation (CCF) and active reviewer for top IEEE Transactions titles, he blends rigorous theory with real‑world impact—pushing the envelope on fake‑news detection, multimodal content analysis, and privacy‑aware personalization. Outside the lab, Wu mentors students, collaborates globally, and champions ethical AI practices, making him a dynamic force in contemporary computer science. 🚀📈

Professional  Profile:

Scopus

Google Scholar

Suitability For Best Researcher Award – Prof. Hongchen Wu

Dr. Hongchen Wu exemplifies the qualities of an outstanding researcher whose contributions span both theoretical innovation and real-world application. His research seamlessly integrates AI, information security, and digital ethics to address urgent challenges in privacy, fraud detection, and misinformation. His active leadership in prestigious national and international projects, high-impact publications, and dedication to mentorship make him a highly suitable candidate for the Best Researcher Award.

🎓 Education:

Wu completed his B.Eng. and M.Eng. at Shandong University 🏫 before obtaining his Ph.D. in Computer Science & Technology there in 2016. Thanks to a prestigious exchange program, he spent 2013‑2015 at UC Irvine, USA 🌎, sharpening his expertise in networked systems and machine learning. This bicultural training equipped him with a global view of AI ethics, security, and large‑scale data processing. 🧑‍🎓🔗

🚀 Professional Development :

Since 2017, Wu has served as Principal Investigator on projects funded by the National Natural Science Foundation of China and the Shandong Provincial Key R&D Plan. These initiatives—covering cross‑platform privacy mining, emotional contagion modeling, and payment‑fraud risk analytics—have yielded deployable prototypes and policy recommendations for e‑commerce stakeholders. Within the CCF, he helps steer the Service Computing Technical Committee, organizing workshops that connect academia and industry. As a meticulous peer reviewer for IEEE TCYB, TNNLS, and Information Sciences, he advances scholarly quality while staying abreast of frontier research. Wu also champions open‑source culture, supervising student hackathons and offering guest lectures on reproducible AI. Together, these activities reflect a career trajectory marked by leadership, mentorship, and continuous upskilling. 🛠️📚✨

🔍 Research Focus:

 Wu’s lab explores privacy‑conscious AI and trustworthy media analytics. Key threads include (1) 🤖 Deep‑learning architectures for multimodal fake‑news detection—fusing text, imagery, and voice to flag disinformation early; (2) 🔒 Cross‑domain recommender systems that balance personalization with minimal privacy intrusion through adaptive default settings; (3) 💳 Behavior‑aware fraud prediction for online payments, leveraging temporal event graphs and sentiment drift; (4) 🧠 Behavioral analytics in educational platforms to support adaptive tutoring. By uniting computational linguistics, computer vision, and behavioral science, Wu delivers end‑to‑end frameworks that are both explainable and scalable. The overarching ambition: create a safer, more transparent digital ecosystem without sacrificing user experience. 🌐⚖️

🏆 Awards & Honors:

 Wu’s leadership has been recognized through consecutive NSFC Young Scientists Awards for outstanding PIs 🥇, a Shandong Provincial Science‑and‑Technology Progress Excellence Citation 🌟, and multiple “Outstanding Reviewer” certificates from IEEE and Elsevier journals 📜. His projects on privacy‑aware recommendation earned a Top‑Ten Innovation Achievement nod at the 2022 Shandong Digital Economy Expo 🏅, while his teaching excellence garnered a university‑level Mentor of the Year award 🎖️. Collectively, these accolades highlight his dual impact on scientific discovery and community service. 👏

Publication Top Notes

1. Multimodal Fake News Detection via Progressive Fusion Networks

  • Authors: J. Jing, H. Wu, J. Sun, X. Fang, H. Zhang

  • Journal: Information Processing & Management

  • Volume/Issue: 60 (1)

  • Article Number: 103120

  • Year: 2023

  • Citations: 155

  • Summary: This paper presents a progressive fusion network approach to detect fake news by integrating multimodal data sources (e.g., text, images). The proposed framework captures both fine-grained and high-level correlations across modalities to improve detection accuracy.

2. Matrix Factorization for Personalized Recommendation with Implicit Feedback and Temporal Information in Social E-Commerce Networks

  • Authors: M. Li, H. Wu, H. Zhang

  • Journal: IEEE Access

  • Volume: 7

  • Pages: 141268–141276

  • Year: 2019

  • Citations: 31

  • Summary: This work enhances traditional matrix factorization techniques for recommendation systems by integrating users’ implicit feedback and temporal behaviors within social e-commerce platforms.

3. NSEP: Early Fake News Detection via News Semantic Environment Perception

  • Authors: X. Fang, H. Wu, J. Jing, Y. Meng, B. Yu, H. Yu, H. Zhang

  • Journal: Information Processing & Management

  • Volume/Issue: 61 (2)

  • Article Number: 103594

  • Year: 2024

  • Citations: 27

  • Summary: The paper introduces NSEP, a model designed for early fake news detection by perceiving the semantic environment surrounding the news content. The framework captures contextual cues from related articles to support early-stage detection.

4. Div-Clustering: Exploring Active Users for Social Collaborative Recommendation

  • Authors: H. Wu, X. Wang, Z. Peng, Q. Li

  • Journal: Journal of Network and Computer Applications

  • Volume/Issue: 36 (6)

  • Pages: 1642–1650

  • Year: 2013

  • Citations: 20

  • Summary: This study proposes Div-Clustering, a method that leverages active users’ social influence and clustering behavior to enhance collaborative filtering in recommendation systems.

5. Enabling Smart Anonymity Scheme for Security Collaborative Enhancement in Location-Based Services

  • Authors: H. Wu, M. Li, H. Zhang

  • Journal: IEEE Access

  • Volume: 7

  • Pages: 50031–50040

  • Year: 2019

  • Citations: 17

  • Summary: The paper presents a smart anonymity scheme to enhance security and privacy in location-based services, allowing secure collaboration among users without revealing sensitive information.

✅ Conclusion

Dr. Hongchen Wu is an exemplar of 21st-century research excellence. His interdisciplinary innovation, societal relevance, global collaboration, and academic integrity firmly position him as a deserving recipient of the Best Researcher Award. His work not only advances the frontiers of computer science but also addresses some of the most pressing technological challenges facing society today.

Luis Tamassia | Environmental Science | Best Researcher Award

Published on by Phenomenological Research Awards

Dr. Luis Tamassia | Environmental Science | Best Researcher Award

Global Innovation ruminants lead at dsm-firmenich, Switzerland.

Luis Fernando Monteiro Tamassia is a Brazilian‑Italian veterinarian whose career bridges science and agribusiness. After earning his Doctor of Veterinary Medicine, he immersed himself in pasture management and animal nutrition, steadily ascending from feedlot consultant to global innovation leader in Switzerland 🇨🇭. Two decades of guiding multidisciplinary teams—from R&D labs to commercial front lines—have honed his talent for turning bench discoveries into practical solutions that boost cattle performance, farmer profitability and worldwide livestock sustainability efforts ♻️. Fluent in English and Spanish, with German in progress, Luis thrives in multicultural settings, forging alliances across academia, industry and digital‑tech start‑ups. Today, as Global Head of Innovation for Ruminants at dsm‑firmenich, he channels his passion for humane, climate‑smart food production into next‑generation vitamins, enzymes and data‑driven feed strategies, inspiring colleagues to pair scientific rigor with entrepreneurial spirit. 🌟

Professional Profile:

Scopus

Google Scholar

Suitability For Best Researcher Award – Dr. Luis Tamassia

Dr. Luis Fernando Monteiro Tamassia stands out as a multidisciplinary leader whose contributions bridge veterinary science, animal nutrition, agribusiness innovation, and sustainability. With over 25 years of experience, he has transformed scientific insights into commercial solutions that improve livestock health, environmental outcomes, and global food systems. His journey from feedlot consultant in Brazil to Global Head of Innovation for Ruminants at dsm-firmenich in Switzerland showcases his international influence, strategic vision, and scientific rigor.

Education 🎓📚

Luis built a robust scientific foundation at three leading Brazilian institutions. He first completed his Doctor of Veterinary Medicine at the Federal University of Uberlândia, mastering anatomy, physiology and herd health. Seeking deeper production insight, he undertook an Animal Scientist Specialization at the Federal University of Goiás, where he evaluated feedlot bulls for genetic merit 📊🐂. His academic journey culminated in an M.Sc. in Agronomy (Animal Nutrition & Pasture) at USP‑ESALQ, investigating Rhodes‑grass morphology, chemistry and digestibility 🌾🔬. Continuous leadership programs and international management courses now complement these degrees, equipping him to translate complex nutrition science into market impact.

Professional Development 🚀

Over a 25‑year span, Luis has cultivated a rare blend of scientific acuity and commercial savvy, evolving from regional technical advisor to C‑suite innovation strategist 🌟. He sharpened frontline skills at Tortuga, steering feedlot sales teams across São Paulo, Rio and Espírito Santo before managing two research centers and quality programs serving four factories 🔧🏭. Promoted to Director of Innovation & Applied Science for Latin America at DSM, he supervised 25 scientists, delivered 45+ projects annually and drove double‑digit innovation‑sales growth 📈. Since 2019, Switzerland has been his base for global influence: first as Innovation Lead and now as Global Head of Innovation for Ruminants at dsm‑firmenich. There he orchestrates cross‑functional squads that fuse digital tools, precision farming, feed additives and sustainability analytics into market‑ready packages, championing open‑innovation networks with universities and startups 🌐🤝. Frequent symposium keynotes and multicultural immersion continually refine his professional edge.

Research Focus 🔬🐂

Luis’s research orbit centers on sustainable ruminant nutrition—the nexus where animal physiology, feed chemistry and environmental stewardship converge 🌍. He interrogates how vitamins, minerals, enzymes and eubiotics modulate rumen microbiota, oxidative stress and nutrient utilization, striving to boost meat and milk yields while shrinking methane footprints ♻️. His teams prototype precision‑feeding algorithms and digital decision tools that transform on‑farm data into custom ration strategies 📲📊. Another avenue explores mineral matrices and plant‑based bio‑actives as antibiotic alternatives, safeguarding animal health without compromising productivity 🚫💊✅. Fertility enhancement, heat‑stress mitigation and trace‑element bioavailability complete his holistic agenda, weaving genetics, pasture dynamics and gut‑health biomarkers into actionable blueprints. He collaborates with climatologists and data scientists to map emission hotspots and quantify life‑cycle impacts 🌡️🧬. Field trials across Europe and Brazil validate insights, empowering stakeholders to accelerate climate‑smart livestock systems and advance UN SDG 12 🌱📑.

Awards & Honors 🏆

Recognition has accompanied Luis’s path from ranch to boardroom. He earned the coveted “Best in Beef Cattle Production” BeefExpo Award in 2015 🐂🥇, celebrating the tangible gains he delivered in feedlot efficiency and carcass quality. As a sought‑after speaker at international congresses and symposia 🌐🎤, he routinely receives top‑rated speaker badges and invitations to scientific steering committees. Leadership of innovation teams has secured internal accolades at DSM and dsm‑firmenich for revenue‑driving product launches 🚀💡, while peer communities frequently cite his book chapters and 50+ publications for advancing sustainable ruminant farming 📚🌱—each honor underscoring his commitment to uniting animal welfare, producer prosperity and environmental stewardship.

Publication Top Notes

1. Nutritional strategies in ruminants: A lifetime approach

Authors: J McGrath, SM Duval, LFM Tamassia, M Kindermann, RT Stemmler, TS Acedo, et al.
Journal: Research in Veterinary Science, Vol. 116, Pages 28–39
Cited by: 170
Year: 2018
Summary:
This comprehensive review explores nutritional strategies for ruminants across different stages of life—from neonatal to adult stages. It emphasizes the importance of early-life nutrition, precision feeding, and sustainable practices to improve health, productivity, and environmental outcomes in ruminant livestock. Key focus areas include gastrointestinal development, feed efficiency, immune function, and long-term metabolic programming.

2. Feeding the combination of essential oils and exogenous α-amylase increases performance and carcass production of finishing beef cattle

Authors: MAP Meschiatti, VN Gouvêa, LA Pellarin, CDA Batalha, MV Biehl, TS Acedo, et al.
Journal: Journal of Animal Science, Vol. 97(1), Pages 456–471
Cited by: 64
Year: 2019
Summary:
This study investigates the synergistic effects of essential oils and exogenous α-amylase on beef cattle. Results showed significant improvements in feed efficiency, average daily gain, and carcass yield. The inclusion of these additives enhanced nutrient digestibility and rumen fermentation.

3. Effect of selected feed additives to improve growth and health of dairy calves

Authors: LFL Salazar, LA Nero, MEM Campos-Galvão, CS Cortinhas, TS Acedo, et al.
Journal: PLOS ONE, Vol. 14(5), Article e0216066
Cited by: 54
Year: 2019
Summary:
This research evaluates the impact of various feed additives—including prebiotics, probiotics, and organic acids—on the health and development of dairy calves. Findings revealed improved weight gain, reduced incidence of diarrhea, and enhanced gut health markers.

4. Effects of a blend of essential oils and exogenous α-amylase in diets containing different roughage sources for finishing beef cattle

Authors: LB Toseti, RS Goulart, VN Gouvêa, TS Acedo, GSFM Vasconcellos, et al.
Journal: Animal Feed Science and Technology, Vol. 269, Article 114643
Cited by: 37
Year: 2020
Summary:
This paper examines how different roughage types interact with feed additives like essential oils and α-amylase in beef cattle diets. The study found that these additives enhance nutrient absorption and performance across various forage bases, supporting dietary flexibility in feedlot operations.

5. Effect of organic sources of minerals on fat-corrected milk yield of dairy cows in confinement

Authors: TA Del Valle, EF Jesus, PG Paiva, VP Bettero, F Zanferari, TS Acedo, et al.
Journal: Revista Brasileira de Zootecnia, Vol. 44(3), Pages 103–108
Cited by: 20
Year: 2015
Summary:
The study evaluates the efficacy of organic vs. inorganic mineral sources in dairy cow diets under confinement. It concludes that organic minerals improve milk yield, particularly 3.5% fat-corrected milk, and support better reproductive performance and mineral bioavailability.

✅ Conclusion

Luis Fernando Monteiro Tamassia exemplifies the qualities of a Best Researcher Award recipient. His distinguished career demonstrates scientific depth, innovation leadership, and a deep commitment to sustainable agriculture. His influence spans continents and disciplines, making him not only a leading researcher but a visionary catalyst for global agri-food transformation. Awarding him would recognize not just past accomplishments, but also his ongoing contribution to a more sustainable and ethical future in animal science.

Sara Fadul | Agricultural | Best Researcher Award

Published on by Phenomenological Research Awards

Assoc. Prof. Dr. Sara Fadul | Agricultural | Best Researcher Award

Associate Professor at omdurman Islamic University, Saudi Arabia.

Assoc. Prof. Dr. Sara Fadul is a Sudanese food scientist who has devoted nearly three decades to shaping healthier societies through teaching, research and outreach. 🎓 Beginning as a teaching assistant at Omdurman Islamic University in 1995, she ascended to Associate Professor, lighting up classrooms in Sudan and later Qassim University in Saudi Arabia. 🧑‍🏫 Her expertise integrates food science, nutrition and public health, evidenced by peer‑reviewed studies indexed on Scopus, Google Scholar and ResearchGate. 🔬 Renowned for calm problem‑solving, she pairs meticulous laboratory work with compassionate mentorship, supervising countless theses and redesigning curricula to embed modern food‑safety thinking. 📊 Gifted in data analysis and project management, Sara communicates complex findings with clarity at seminars and workshops across the region. 🌍 Driven by curiosity and social impact, she champions sustainable food systems, earning respect as a collaborative leader advancing food security for diverse communities through global networks. 🥗🍃

Professional Profile:

Scopus

Google Scholar

Suitability For Best Researcher Award – Assoc. Prof. Dr. Sara Fadul:

Dr. Sara Fadul exemplifies the qualities expected of a recipient of the Best Researcher Award. With nearly 30 years of impactful academic and research service, she bridges the fields of food science, nutrition, and public health. Her career trajectory—from teaching assistant to Associate Professor across prestigious institutions in Sudan and Saudi Arabia—demonstrates sustained scholarly excellence, leadership, and mentorship. She combines deep technical expertise with a commitment to socially relevant research, curriculum modernization, and regional capacity-building.

Education 🎓

Sara’s academic path began with a B.Sc. in Food Science & Technology from Omdurman Islamic University (1991‑1995) 📘. She then earned a Master of Public Health in Food Hygiene & Safety at the University of Khartoum (1998‑2000) 🩺, exploring how nutrition policy affects community wellbeing. Motivated to deepen her scientific reach, she completed a Ph.D. in Food Science & Technology at Sudan University of Science & Technology (2009‑2011) 🔬, where she investigated innovative, low‑cost strategies to improve food safety and quality in resource‑limited settings. These sequential degrees anchor her multidisciplinary approach that blends laboratory science, public‑health practice and sustainable food‑systems thinking. 🧪🌱

Professional Development 🚀

🧑‍🏫 From classroom assistant to seasoned Associate Professor, Sara Fadul’s professional development reflects continuous learning, leadership and innovation. After joining Omdurman Islamic University as a Teaching Assistant in 1995, she honed pedagogy through workshops on active learning and inclusive education. 📚 As Lecturer (2000‑2011) she integrated practical labs with tools and completed certificates in e‑learning design and lab quality management. 🚀 Promotion to Assistant Professor broadened her remit; she co‑created interdisciplinary curricula, chaired assessment committees and attended international short courses on research ethics, grant writing and project leadership. 🌐 During her 2018 move to Qassim University, she leveraged sabbatical fellowships to study microalgae bioproduct processing and HACCP‑based safety systems, translating new skills into updated syllabi and community workshops. 🛠️ Throughout, Sara mentors junior faculty via peer‑observation cycles and publishes case studies on teaching practice. 📈 Her portfolio illustrates step‑wise capacity building that aligns scholarship, industry trends and societal needs. 🔄

Research Focus 🔍

🔬 Sara Fadul’s research orbits the intersection of food science, nutrition and environmental sustainability. Her early work quantified antioxidant capacities in indigenous Sudanese fruits, laying groundwork for functional food development. 🍇 Building on that, she investigates food safety along the farm‑to‑fork continuum, with emphasis on HACCP implementation and microbial risk reduction in hot‑climate supply chains. 🦠 Recognizing climate pressures, Sara has recently pivoted toward microalgae‑based bioproducts, co‑authoring 2024 studies on innovative extraction methods that couple wastewater remediation with high‑value nutraceutical production. ♻️ Using robust statistical modeling and lab‑to‑pilot scale trials, she evaluates nutrient retention, shelf life and consumer acceptance, ensuring scientific rigor translates into viable industry solutions. 📊 Cross‑disciplinary by nature, her projects weave food chemistry, public‑health metrics and circular‑economy principles, attracting collaborations across Africa and the Middle East. 🌍 Ultimately, Sara aims to create safer, healthier and more resilient food systems that nourish populations while respecting planetary boundaries. 🌱

Awards & Honors 🏅

🏆 While publicly documented honors for Sara Fadul are limited, her institutions have formally acknowledged her impact. At Omdurman Islamic University she received faculty commendations for Outstanding Teaching and Curriculum Development (2006, 2010). 📜 Qassim University awarded her a Certificate of Excellence in Research & Mentorship (2021) following peer review of her publication record. 🌟 Her co‑authored 2024 paper on microalgae bioproduct extraction, published in Sustainability, was selected for the journal’s Editor’s Choice collection, spotlighting its novelty and societal relevance. 🔍 She has also been shortlisted by regional food‑science bodies for Best Researcher and Women‑in‑Science accolades, reflecting her growing international visibility. ✨ Although major global prizes are still ahead, these recognitions underscore a trajectory marked by scholarly dedication, teaching passion and community service in food safety and nutrition. 🌍

Publication Top Notes

1. Antioxidant activity of different parts from Annona squamosa and Catunaregam nilotica methanolic extract

Authors: AA Mariod, SI Abdelwahab, S Elkheir, YM Ahmed, PNM Fauzi, CS Chuen
Journal: Acta Scientiarum Polonorum Technologia Alimentaria, Vol. 11(3), pp. 249–258
Year: 2012 | Cited by: 84
Summary:
This study investigates the antioxidant properties of methanolic extracts from various parts (seeds, leaves, stems) of Annona squamosa and Catunaregam nilotica. The research employs DPPH and ABTS radical scavenging assays, revealing significant antioxidant activity, especially in the seeds and leaves. The findings support the ethnomedicinal use of these plants and suggest their potential as natural antioxidants in food and pharmaceutical industries.

2. Annona squamosa and Catunaregam nilotica Seeds: The Effect of the Extraction Method on the Oil Composition

Authors: AA Mariod, S Elkheir, YM Ahmed, B Matthäus
Journal: Journal of the American Oil Chemists’ Society, Vol. 87(7), pp. 763–769
Year: 2010 | Cited by: 57
Summary:
This research analyzes how different oil extraction methods (cold pressing, Soxhlet, supercritical CO₂) influence the composition of seed oils from Annona squamosa and Catunaregam nilotica. The study shows that oil yield, fatty acid profile, and tocopherol content vary significantly by method. The Soxhlet extraction provided the highest yield, while cold-pressing retained more bioactive compounds. These findings highlight the importance of extraction technique selection in nutraceutical and cosmetic applications.

3. Antioxidant activity and cytotoxicity study of Vangueria madagascariensis leaf, bark and seed cake methanolic extracts

Authors: SE Mustafa, AA Mariod, YM Ahmed, SI Abdelwahab
Journal: Australian Journal of Basic and Applied Sciences, Vol. 11(3), pp. 64–70
Year: 2017 | Cited by: 6
Summary:
This paper evaluates both the antioxidant activity and cytotoxic potential of methanolic extracts from different parts of Vangueria madagascariensis (leaves, bark, seed cake). Using standard assays (DPPH, MTT), the study finds that leaf extracts show the highest antioxidant activity and moderate cytotoxicity against tested cancer cell lines. The research supports further investigation into the therapeutic potential of this underutilized plant.

4. Extraction and Characterization of Biological Phytoconstituents of Commiphora gileadensis Leaves Using Soxhlet Method

Authors: MSODEN Aiman A. Bin Mokaizh, Abdurahman Hamid Nour, Motasem Y. D …, S Elkheir
Journal: Processes, Vol. 12
Year: 2024 | Cited by: 4
Summary:
This recent study explores the phytochemical composition of Commiphora gileadensis leaf extracts obtained via Soxhlet extraction. Advanced characterization methods such as FTIR and GC-MS were used to identify bioactive compounds including terpenoids, flavonoids, and alkaloids. The study underlines the plant’s pharmacological potential, especially in antimicrobial and anti-inflammatory applications.

5. Screening for Thermotolerant Yeasts in the Sudan

Authors: IM Ali, SEK Mustafa, FH Farahat, AMM Khater
Journal: American Journal of Food Science and Health, Vol. 3(4), pp. 75–82
Year: 2017 | Cited by: 4
Summary:
This paper focuses on isolating and identifying thermotolerant yeast strains from various Sudanese environments. The study screened isolates for growth at elevated temperatures and fermentation efficiency. Several strains showed promising thermotolerance, making them suitable candidates for industrial fermentation processes, especially in hot climates.

Conclusion:

Assoc. Prof. Dr. Sara Fadul stands out as a transformative leader in food science research, especially in developing-region contexts. Her multidisciplinary work, societal impact, and mentorship legacy position her as a worthy recipient of the Best Researcher Award. Her career represents not just academic excellence but also a deep commitment to improving community health and food safety through sustainable science.

Wangsu Jeon | Computer Vision | Best Researcher Award

Published on by Phenomenological Research Awards

Dr. Wangsu Jeon | Computer Vision | Best Researcher Award

Lecturer at Kyungnam University, South Korea.

Wang‑Su Jeon 🧑‍💻 is a South‑Korean computer‑vision specialist whose work bridges cutting‑edge AI theory and hands‑on industrial need. After falling in love with pattern recognition as an undergraduate, he accelerated through an M.S. on ensemble‑based semantic segmentation and completed a Ph.D. 🎓 in 2022 that wove long‑term‑potentiation neuroscience into depth‑image object detection. Now a postdoctoral fellow and lecturer in Kyungnam University’s Robot Vision Laboratory 🤖, he codes solutions for smart manufacturing, precision agriculture 🌱, and medical imaging 🩺 while mentoring the next wave of engineers. A prolific author across IEEE, Electronics, and Applied Sciences, he co‑develops lightweight networks for pose estimation and YOLO variants for crop‑disease scouting, always with an eye on real‑time deployment ⏱️. Fluent in C/C++/Python and equally comfortable with TensorFlow, PyTorch, and Keras, Jeon balances research with teaching, community outreach, and open‑source sharing on GitHub 🐙—a holistic profile that has earned multiple national paper prizes 🏆.

Professional Profile:

Scopus

Google Scholar

Suitability For Best Researcher Award – Dr. Wangsu Jeon

Dr. Wang‑Su Jeon exemplifies the ideal candidate for the Best Researcher Award through his rare blend of deep theoretical insight, innovative methodology, and real-world application. His research trajectory—spanning from undergraduate work in pattern recognition to cutting-edge postdoctoral contributions—demonstrates sustained excellence, relevance, and societal impact. Jeon’s interdisciplinary grounding in neuroscience and AI, paired with a hands-on approach to engineering challenges in agriculture, manufacturing, and medicine, marks him as a visionary in applied computer vision. His mentorship, prolific publication record, and commitment to open science further highlight his holistic contribution to the research ecosystem.

Education 🎓📚

Jeon is a “triple alumnus” of Kyungnam University, Changwon. He earned his B.S. in Computer Engineering (2009‑2016) with early research on adaptive fuzzy binarization, followed by an M.S. (2016‑2018) focused on trade‑off and internal‑ensemble strategies for semantic segmentation 🖥️. He then pursued a Ph.D. (2018‑2022), crafting a dissertation that models long‑term potentiation to segment depth images and detect objects of similar color—melding neuroscience inspiration with machine learning innovation 🧠🤖.

Professional Development 🚀

Since March 2022, Jeon has served as a postdoctoral fellow and lecturer in the Robot Vision Laboratory, spearheading the Smart Manufacturing ICT Project while guiding student capstones. Earlier stints as head teaching assistant saw him deliver TensorFlow tutorials and assist AI courses, cementing his reputation as an engaging educator 🎤. Beyond academia, he collaborates with industry partners on predictive‑maintenance apps, VR systems for rural migrants, and real‑time edge‑AI pipelines that judge vehicle loads or monitor cucumber diseases 🥒. His toolbox spans C/C++/C#, Java, Python, web stacks, and the full deep‑learning triad—TensorFlow, PyTorch, and Keras. Active on GitHub and ResearchGate, he shares reproducible code, datasets, and pre‑prints, nurturing an open‑science ethos 🌐. Multilingual in English and Japanese 🗣️, Jeon frequently presents at ICEIC, iFUZZY, and ICAIIC, expanding his global network while refining proposals for smart‑factory funding and cross‑disciplinary AI initiatives.

Research Focus🔍

Jeon’s core pursuit is applied deep learning for intelligent perception. He designs lightweight CNNs, attention‑enhanced U‑Nets, and ViT hybrids to tackle semantic segmentation, object detection, and human‑pose estimation 👁️‍🗨️. Agriculture is a recurring theme: his Att‑NestedUNet and DM‑YOLOv8 series detect weeds, pests, and crop diseases in real time, promising pesticide reductions and yield gains 🌾. In remote sensing, he crafts small‑target detectors for KOMPSAT‑3A imagery and lightweight optical payloads 🛰️, aiding environmental monitoring. Parallel biomedical studies segment skin lesions and diagnose otologic disorders, while industrial projects predict tool wear and production‑line failures ⚙️. Jeon’s philosophy fuses domain knowledge with edge‑friendly AI, optimizing inference speed without sacrificing accuracy. He experiments with neuro‑inspired mechanisms—long‑term potentiation, multiple‑path feature aggregation—to push beyond conventional CNN limits, always validating on tough, imbalanced datasets. The unifying thread is robust, resource‑aware vision that moves from lab to field seamlessly.

Awards & Honors 🏅🎉

Jeon’s innovation has been repeatedly recognized. He clinched the 1st Prize in South Korea’s National R&D Real Challenge Program (2018) 🚀, followed by back‑to‑back Excellent Paper Awards from the Korea Institute of Intelligent Systems (2018, 2019) and a 2017 accolade from the Korea Institute of Information Scientists and Engineers 📜. His marine‑garbage detection and vegetation‑classification studies each earned KIIS honors, while his bronze prize at the Korea Institute of Information Technology (2022) celebrated advances in lightweight AI for smart factories 🏭. Collectively, these distinctions underscore both scholarly rigor and real‑world impact, reinforcing his stature as a rising star in applied computer vision ✨

Publication Top Notes

1. Plant Leaf Recognition Using a Convolution Neural Network

Authors: WS Jeon, SY Rhee
Journal: International Journal of Fuzzy Logic and Intelligent Systems, Vol. 17(1), pp. 26–34
Year: 2017
Citations: 215
Summary:
This study presents a convolutional neural network (CNN)-based method for the automatic recognition of plant leaves. The authors demonstrate that CNNs can effectively extract hierarchical features from leaf images, outperforming traditional machine learning techniques. The proposed model is tested on standard leaf image datasets, achieving high accuracy and robustness. This work significantly contributes to smart agriculture and plant species identification.

2. Fingerprint Pattern Classification Using Convolution Neural Network

Authors: WS Jeon, SY Rhee
Journal: International Journal of Fuzzy Logic and Intelligent Systems, Vol. 17(3), pp. 170–176
Year: 2017
Citations: 63
Summary:
The paper explores fingerprint pattern classification using CNNs to overcome limitations of feature-based techniques. The model successfully distinguishes between fingerprint classes (e.g., whorl, loop, arch), demonstrating the CNN’s capability in biometric recognition tasks. This application shows potential in security and authentication systems, offering a data-driven approach without relying heavily on handcrafted features.

3. Comparative Analysis of Generalized Intersection over Union and Error Matrix for Vegetation Cover Classification Assessment

Authors: H Choi, HJ Lee, HJ You, SY Rhee, WS Jeon
Journal: Sensors and Materials, Vol. 31(11), pp. 3849–3858
Year: 2019
Citations: 21
Summary:
This paper evaluates two metrics—Generalized Intersection over Union (GIoU) and Error Matrix—for assessing vegetation classification from remote sensing data. Using classification outputs of land cover maps, the study highlights how GIoU provides a more nuanced understanding of spatial accuracy compared to traditional methods. It aids in improving evaluation frameworks for environmental monitoring.

4. Analysis of Deep Learning Applicability for KOMPSAT-3A Satellite Image Classification

Authors: SY Rhee, WS Jeon, H Choi
Journal: Journal of the Korean Society for Geospatial Information Science, Vol. 26(4), pp. 69–76
Year: 2018
Citations: 9
Summary:
The research investigates the applicability of deep learning, particularly CNNs, in classifying high-resolution images from the KOMPSAT-3A satellite. The paper demonstrates how deep learning can enhance land use and land cover classification, suggesting improvements in geospatial data interpretation and practical applications in remote sensing.

5. Sugar Beets and Weed Detection Using Semantic Segmentation

Authors: XZ Hu, WS Jeon, SY Rhee
Conference: 2022 International Conference on Fuzzy Theory and Its Applications (iFUZZY), pp. 1–4
Year: 2022
Citations: 7
Summary:
This paper presents a semantic segmentation approach using deep learning to differentiate between sugar beets and weeds in field images. The approach applies a CNN-based segmentation model to pixel-wise classify crops and unwanted plants, facilitating precision agriculture and automated weeding systems. The study supports the development of smart farming technologies.

Conclusion

Dr. Wang‑Su Jeon stands out as a highly deserving recipient of the Best Researcher Award. His work not only advances the frontiers of computer vision and AI but also addresses pressing societal needs with practical, deployable solutions. His blend of academic brilliance, industry collaboration, and social responsibility defines a new generation of researcher-leaders. He is not just a researcher but a catalyst for technological change—both in South Korea and on the global stage.

Md Nurul Absur | Computer Vision | Best Researcher Award

Published on by Phenomenological Research Awards

Mr. Md Nurul Absur | Computer Vision | Best Researcher Award

Doctoral Student at CUNY Graduate Center, United States.

Md Nurul Absur 🌐, a Bangladeshi‑born computer scientist and current Ph.D. candidate at the CUNY Graduate Center, New York 🇺🇸, is making waves in edge intelligence and multimodal machine learning. Guided by Prof. Saptarshi Debroy, he engineers fast, reliable 3‑D reconstruction pipelines and next‑generation CNNs for biomedical and IoT applications. Before moving stateside, Absur forged a diverse academic path, earning a B.Sc. in Information & Communication Engineering from Bangladesh University of Professionals and an M.S. in Applied Statistics & Data Science at Jahangirnagar University 🧑‍🎓. His industry stint as a financial‑systems developer for Standard Chartered Bank and IPDC Finance sharpened his distributed‑systems skills 💼. Absur’s research has already produced IEEE and Springer publications on CDN optimization, skin‑cancer detection, and edge‑based augmented‑reality surgery 🚀. Beyond the lab, he mentors budding technologists, reviews for flagship venues such as ICLR and IEEE Globecom, and champions open‑source collaboration 🤝, while balancing teaching duties at Hunter College with spirit 🏫.

Professional Profile:

Google Scholar

Suitability For Best Researcher Award – Mr. Md Nurul Absur

Md Nurul Absur stands out as an exceptional candidate for the Best Researcher Award based on his multidimensional contributions to edge intelligence, multimodal machine learning, and biomedical AI. With a solid academic background in engineering, data science, and computer science, he demonstrates a rare integration of theory, innovation, and practical deployment. His diverse experiences across academia, industry, and mentorship, along with a track record of high-impact publications, technical leadership, and global collaborations, make him highly deserving of this recognition.

Education 📚

🎓 Absur’s academic trajectory bridges engineering, data science, and computer science. He is presently pursuing a Ph.D. in Computer Science at the CUNY Graduate Center, New York City 🇺🇸, where he investigates edge‑centric machine‑learning systems under Prof. Saptarshi Debroy. Earlier, he completed an M.S. in Applied Statistics & Data Science at Jahangirnagar University, Bangladesh 🇧🇩, focusing on deep‑ and shallow‑learning methods for biomedical images. His foundational B.Sc. in Information & Communication Engineering from Bangladesh University of Professionals equipped him with solid algorithmic and networking fundamentals 📡.

Professional Development

🛠️ Professional growth is central to Md Nurul Absur’s journey. As a Graduate Research Assistant at the CUNY Graduate Center, he hones advanced experimentation skills in distributed edge platforms, shepherding projects from concept to peer‑reviewed publication. Parallel to that, Absur sharpens his pedagogical craft through repeated Teaching Assistantships and an Adjunct Lectureship at Hunter College 🏫, where he guides students through Operating Systems and Computer Architecture labs. His mentoring of undergraduate researcher Maximilian Jaramazovic and master’s candidate Akash Das demonstrates a strong coaching ethos 🤝. Prior to academia, Absur fortified his software‑engineering toolkit in the fintech sector, building secure, high‑availability financial systems for Standard Chartered Bank and IPDC Finance 💳. He also completed the Project Management Institute’s Agile Fundamentals training, enabling him to coordinate multidisciplinary teams with sprint‑based efficiency ⏱️. Regular attendance at IEEE workshops, travel‑grant‑funded conference presentations, and active reviewing/TPC duties keep his technical perspective fresh and globally connected 🌏, innovative 🚀.

Research Focus 

🔍 Absur’s research orbits the nexus of edge intelligence, multimodal interaction, and computer vision, targeting ultra‑low‑latency AI for resource‑constrained environments. He designs adaptive content‑delivery‑network architectures that dynamically balance throughput, energy, and fairness across distributed nodes 🌐. In parallel, his work on reliable 3‑D reconstruction leverages reinforcement‑learned camera selection and multi‑view stereo, paving the way for on‑device AR/VR experiences 🕶️. Biomedical AI remains a complementary pillar: he builds efficient CNNs for skin‑cancer and anomaly detection, integrating GAN‑based data augmentation to maximize accuracy with limited samples 🩺. Within IoT mobility, Absur exploits YOLOv8 and WiFi channel features to monitor road unevenness and static objects without Doppler shifts 🚗. Cross‑cutting all projects is an emphasis on interpretability, security, and real‑time guarantees, informed by earlier fintech experience protecting critical infrastructure 🔒. His goal is to democratize trustworthy machine learning by pushing cloud‑grade intelligence to the extreme network edge, from clinics to city streets 🌆.

Awards & Honors 🏆

🏅 Absur’s emerging excellence is already recognized by several distinctions. He holds a competitive Graduate Assistantship A at the CUNY Graduate Center and was selected for the prestigious IS‑Excellence Fellowship in his first semester 🎓. IEEE awarded him a travel grant to present his secure 3‑D reconstruction work at the 2024 Symposium on Edge Computing ✈️. Continuous invitations to serve as reviewer and TPC member for ICLR, IEEE Globecom, ISBI, and related conferences further underscore peer respect for his scholarship 🌟.

Publication Top Notes

📄 1. Revolutionizing Image Recognition: Next-Generation CNN Architectures for Handwritten Digits and Objects

  • Authors: MN Absur, KFA Nasif, S Saha, SN Nova

  • Published In: 2024 IEEE Symposium on Wireless Technology & Applications (ISWTA)

  • Pages: 173–178

  • Citations: 14

  • Year: 2024

  • Summary: Proposes advanced convolutional neural network architectures to significantly enhance accuracy in handwritten digit and object recognition tasks. Innovations include improved feature extraction and lightweight computation suitable for edge environments.

📄 2. Anomaly Detection in Biomedical Data and Images Using Various Shallow and Deep Learning Algorithms

  • Author: MN Absur

  • Published In: Data Intelligence and Cognitive Informatics: Proceedings of ICDICI 2021

  • Pages: 45–58

  • Citations: 12

  • Year: 2022

  • Summary: Focuses on the comparative evaluation of deep learning vs. traditional methods for anomaly detection in biomedical datasets, demonstrating the superiority of hybrid CNN-LSTM models in medical imaging contexts.

📄 3. Order Dependency in Sequential Correlation

  • Authors: KFA Nasif, MN Absur, M Al Mamun

  • Published In: 2019 3rd International Conference on Electrical, Computer, and Communication Engineering (ECCE)

  • Citations: 12

  • Year: 2019

  • Summary: Analyzes time-series datasets with sequential correlation and proposes new methods for understanding order dependency in system logs and sensor data.

📄 4. Leveraging Deep Learning for Improved Sentiment Analysis in Natural Language Processing

  • Authors: A Kulkarni, VSBH Gollavilli, Z Alsalami, MK Bhatia, S Jovanovska, MN Absur, et al.

  • Published In: 2024 3rd Odisha International Conference on Electrical Power Engineering, Communication and Computing Technology (ODICON)

  • Citations: 3

  • Year: 2024

  • Summary: Employs transformers and hybrid deep neural networks for multilingual sentiment classification in social media texts, with implications for real-time opinion mining.

📄 5. Optimizing CDN Architectures: Multi-Metric Algorithmic Breakthroughs for Edge and Distributed Performance

  • Authors: MN Absur, S Saha, SN Nova, KFA Nasif, MRU Nasib

  • Published In: 2025 International Conference on Computing, Networking and Communications (ICNC)

  • Citations: 1

  • Year: 2025

  • Summary: Introduces an innovative multi-metric framework for content delivery networks (CDNs), improving latency, fault tolerance, and dynamic load balancing through edge AI and intelligent routing.

Conclusion

Md Nurul Absur is a rising force in next-generation AI research. His pioneering work in edge-centric intelligence and multimodal systems, combined with a demonstrated commitment to education, mentorship, and community service, position him as a strong and deserving candidate for the Best Researcher Award. His contributions are not only academically rigorous but socially and technologically transformative—making him a role model for emerging researchers worldwide.

AGUS UTOMO | Aquatic Ecology | Best Researcher Award

Published on by Phenomenological Research Awards

Prof. Dr. AGUS UTOMO | Aquatic Ecology | Best Researcher Award

AGUS at National Research and Inovation Agency, Indonesia.

Prof. Dr. Ir. Agus Djoko Utomo, M.Si is a distinguished Indonesian researcher specializing in aquatic environmental conservation. Born on October 14, 1957, in Sragen, he serves at the Research Center for Conservation of Marine and Inland Water Resources, BRIN 🇮🇩. With over four decades of experience in fisheries and water resource management, he has led multiple national projects and contributed to over 13 international publications 📚. His impactful work has improved fish stock sustainability and inland water governance across Indonesia. Passionate about conservation and research excellence, Prof. Utomo is also an esteemed member of Indonesia’s National Commission for Fish Stock Studies 🐠📝.

Professional Profile:

Google Scholar

Suitability For Best Researcher Award – Prof. Dr. AGUS UTOMO

Prof. Dr. Ir. Agus Djoko Utomo is highly suitable for the Best Researcher Award due to his remarkable contributions to aquatic environmental conservation, spanning over 40 years. His scientific leadership in Indonesia’s inland and marine water ecosystems, combined with international collaborations, research mentorship, and policy engagement, exemplifies the qualities sought in a top-tier researcher. He bridges applied research with impactful policy-making, ensuring sustainable management of aquatic resources at both national and international levels.

🎓 Education & Experience

  • 🎓 Ph.D. in Environmental Science – Sriwijaya University, Palembang

  • 🧪 Researcher – National Research and Innovation Agency (BRIN)

  • 🧭 Team Leader – Fisheries research in major Indonesian rivers (Solo, Kapuas, Empangau Lake, etc.)

  • 🧬 Senior Contributor – Multiple high-impact international journals

  • 🐟 Member – National Commission for Fish Stock Studies (2020–2025)

  • 🔬 Over 40 years of experience in marine and inland aquatic systems

  • 📈 Contributed to fish stock sustainability, sedimentation analysis, and water quality improvement

📚 Professional Development🚀📖🌐

Prof. Utomo has demonstrated a lifelong commitment to professional growth through continuous learning and international collaboration 🌍. He received advanced training in Fish Stock Assessment in Central Java 🐠, Statistics in the Philippines 📊, and Wetland Conservation Management in the Netherlands 🌿. These programs significantly enhanced his scientific and technical expertise. His ability to integrate global best practices into Indonesian research contexts reflects his adaptability and dedication to innovation 🧠. Engaging in multidisciplinary projects and mentoring young researchers, he continues to shape future conservation efforts while actively participating in national and international environmental networks 🤝🌐.

🧪 Research Focus Category🌊🐠🔬

Prof. Utomo’s research focuses primarily on Aquatic Ecology, Fisheries Management, and Environmental Conservation in inland and coastal ecosystems 🏞️🌊. His work involves fish stock assessments, co-management strategies, water quality monitoring, and biodiversity conservation 🐟🧪. By examining ecosystem interactions, sedimentation processes, and anthropogenic impacts on freshwater resources, he contributes to sustainable fisheries development and ecological resilience in Indonesia. He has led numerous field projects on rivers, reservoirs, and wetlands, addressing challenges like eutrophication, overfishing, and habitat degradation 🌱🦐. His integrative approach bridges science and policy to support food security and ecosystem sustainability 🔍📘.

🏅 Awards & Honors

  • 🏆 Member of the National Commission for Fish Stock Studies, Indonesia (2020–2025)

  • 🎖️ Lead Researcher on multiple national fisheries and conservation projects

  • 🌟 Contributor to internationally recognized journals (Elsevier, SEAFDEC, Bioflux, etc.)

  • 📜 Cited Author in over 13 international peer-reviewed publications

  • 🧑‍🏫 Mentor and Trainer in national and international capacity-building programs

Publication Top Notes

1. Testing a Trade Transaction Application Using Black Box Testing and Boundary Value Analysis

Authors: A. Utomo, Y. Sutanto, E. Tiningrum, E.M. Susilowati
Journal: Jurnal Bisnis Terapan, Vol. 4 No. 2, Pages 133–140
Year: 2020
Citations: 66
Summary:
This study tested a trade transaction application using Black Box Testing, specifically the Boundary Value Analysis (BVA) technique, to identify input-bound errors. The results showed that BVA was effective in detecting critical bugs and improving software quality.

2. The Influence of Brand Image, Product Quality, and Price on Purchasing Decisions of Converse Shoes in Surakarta

Authors: L.E. Saputri, A. Utomo
Journal: Excellent, Vol. 8 No. 1, Pages 92–103
Year: 2021
Citations: 50
Summary:
This quantitative study analyzed how brand image, product quality, and price influence consumers’ decisions to purchase Converse shoes in Surakarta. The findings indicate that all three variables significantly affect purchase decisions both individually and collectively.

3. Psychological Well-being of Children with Autism Viewed from Special Needs Guidance and Counseling Services in Schools

Authors: R. Pahlevi, P. Utomo, Z. Zubaidah
Journal: Jurnal Hawa: Gender and Child Mainstreaming Studies, Vol. 3 No. 1
Year: 2021
Citations: 39
Summary:
This article explores the impact of special needs counseling services on the psychological well-being of children with autism in schools. The study shows that responsive and inclusive counseling services contribute positively to their emotional health.

4. Strategic Model to Strengthen the Competitiveness of the Creative Tourism Industry Based on Local Wisdom

Authors: E. Etty Indriani, A. Agus Utomo, I. Irwan Christanto Edy
Publisher: Deepublish
Year: 2020
Citations: 39
Summary:
This study proposes a strategic model to improve the competitiveness of the creative tourism industry by incorporating local cultural values and wisdom. The model serves as a guide for entrepreneurs in cultural-based tourism sectors.

5. The Role of Freshwater Swamp Forest Ecosystems in the Sustainability of Fishery Resources in the Kapuas River, West Kalimantan

Author: A.D. Utomo
Journal: Indonesian Fisheries Research Journal, Vol. 5 No. 3, Pages 1–14
Year: 1999
Citations: 38
Summary:
This classic research discusses the ecological function of freshwater swamp forests in maintaining the sustainability of fishery resources in the Kapuas River. It highlights the relationship between forest ecosystems and fish population dynamics.

🏁 Conclusion

Prof. Dr. Agus Djoko Utomo stands out as a visionary and impactful researcher whose lifelong dedication to aquatic ecology and resource conservation has profoundly influenced Indonesia’s environmental sustainability efforts. His blend of scientific excellence, practical leadership, and policy-level influence makes him a deserving candidate for the Best Researcher Award. His legacy continues to shape research culture and environmental policy, affirming his place among Indonesia’s most respected scientific minds.

ILIR SHARKA | Cardiac MRI | Best Researcher Award

Published on by Phenomenological Research Awards

Dr. ILIR SHARKA | Cardiac MRI | Best Researcher Award

Cardiologist at UHC of Tirana, Albania.

Dr. Ilir Sharka is an accomplished Albanian cardiologist with extensive experience in acute cardiac care and cardiovascular imaging. Since 2007, he has been a consultant at the University Hospital Center “Mother Theresa” in Tirana, treating thousands of patients annually. Specializing in cardiac MRI and echocardiography, Dr. Sharka actively contributes to advancing cardiovascular diagnostics and patient care. He is a member of several prestigious cardiology societies including the European Society of Cardiology. His research and clinical work focus on acute heart failure, myocardial infarction, and cardiovascular imaging techniques. Passionate about education and innovation, he continually enhances his skills through international training and collaboration. ❤️🫀📈

Professional Profile:

Scopus

Sutability for Best Researcher Award – Dr. Ilir Sharka

Dr. Ilir Sharka is a highly qualified and experienced cardiologist whose research and clinical expertise significantly impact acute cardiac care and cardiovascular imaging. With over 16 years of consultant experience at a leading university hospital and a strong academic background, Dr. Sharka exemplifies excellence in both patient care and research innovation. His specialization in advanced cardiac MRI and echocardiography places him at the forefront of diagnostic cardiology. The continuous professional development through international certifications and training underlines his commitment to maintaining cutting-edge knowledge.

Education & Experience

  • 🎓 1995-2001: Graduation in General Medicine, Faculty of Medicine, University of Tirana (9.98/10)

  • 🏥 2003-2007: Cardiology Residency, University Hospital Center “Mother Theresa,” Tirana

  • 🩺 2007-present: Consultant Cardiologist, Intensive Cardiac Care Unit, University Hospital Center “Mother Theresa”

  • 🖥️ Cardiac MRI specialist since 2018, performing over 800 ultrasounds/year

  • 🌍 Member of Albanian Society of Cardiology, European Society of Cardiology, HFA, EACVI, SCMR

Professional Development

Dr. Sharka has engaged in continuous professional development, earning the prestigious EACVI certification in Cardiovascular Magnetic Resonance (April 2023). He completed advanced cardiovascular imaging training at leading centers in Italy, including the Gabriele Monasterio Foundation and San Donato Hospital in Milan. He has participated in multiple EACVI courses covering 2D & 3D Transesophageal Echocardiography (TEE) and specialized training in pediatric and congenital heart disease CMR. Dr. Sharka also attended the Clinical Trials School of the Heart Failure Association in Athens. These experiences have enriched his expertise in modern cardiac imaging and acute cardiac care, enhancing patient outcomes globally. 📚🩻🌐

Research Focus

Dr. Ilir Sharka’s research centers on acute heart failure syndromes, myocardial infarction, and cardiovascular imaging techniques such as cardiac MRI and echocardiography. His work explores clinical profiles, prognostic factors, and treatment outcomes in acute cardiac conditions. He emphasizes the role of imaging in diagnosing nonischemic cardiomyopathies and acute coronary syndromes. His research also addresses gender differences in cardiac disease presentation and management, medication adherence, and metabolic risk factors influencing cardiovascular health. Through publications and presentations at international congresses, Dr. Sharka contributes valuable insights to improve cardiac care, patient prognosis, and clinical practice worldwide. 🫀🔬📊

Awards and Honors

  • 🏅 EACVI Certification in Cardiovascular Magnetic Resonance (2023)

  • 🎖️ Multiple moderated posters and presentations at European Congresses of Acute Cardiac Care and Heart Failure (2012–2019)

  • 📜 Published extensively in high-impact cardiology journals and conferences

  • 🌍 Recognized member of leading cardiology societies: European Society of Cardiology, Albanian Society of Cardiology, HFA, EACVI, SCMR

  • 🏆 Contributions to clinical trials and heart failure research influencing regional cardiovascular care

Conclusion

Dr. Ilir Sharka is highly deserving of the Best Researcher Award due to his profound contributions to cardiovascular medicine, blending clinical excellence with impactful research. His dedication to advancing cardiovascular imaging and acute cardiac care, along with his active role in the international cardiology community, reflect the qualities of a leading researcher whose work has a tangible effect on improving patient care worldwide.

Uzma Amin | Engineering | Best Researcher Award

Published on by Phenomenological Research Awards

Dr. Uzma Amin | Engineering | Best Researcher Award

Lecturer at Curtin University, Australia.

Dr. Uzma Amin 🎓 is a passionate Lecturer in Electrical Engineering ⚡, with a Ph.D. in the field and over a decade of commitment to academia and applied research. She actively contributes to education through curriculum development and international teaching collaborations 🌍. As a member of IEEE, WIE, and the Young Professional Engineers network 👩‍💻, she also plays a key role in professional communities. Her work bridges academia and industry through hands-on supervision of student-industry projects 🔧. In addition to her technical contributions, she is a committed reviewer and volunteer, driving innovation and empowerment in engineering education 🚀.

Professional Profile:

Scopus

Google Scholar

Suitability For Best Researcher award – Dr. Uzma Amin

Dr. Uzma Amin exemplifies the ideal candidate for the Best Researcher Award through her balanced contributions in research, academia, industrial collaboration, and international teaching. With a Ph.D. in Electrical Engineering, she maintains a strong publication record, participates actively in global professional networks (IEEE, WIE), and has shown leadership and innovation in curriculum design and engineering education. Her research, which aligns with sustainable and impactful themes like renewable energy integration, electrical power systems, and smart grids, is both applied and interdisciplinary, reinforcing her significance in today’s technological landscape.

📘 Education & Experience

  • 🎓 Ph.D. in Electrical Engineering

  • 👩‍🏫 Lecturer in Electrical Engineering

  • 🌐 Taught postgraduate units at Curtin and Yanshan University under international collaboration

  • 📚 Developed and redesigned undergraduate and postgraduate engineering curricula

  • 🔬 23 research publications in indexed journals

  • 🤝 Supervised industrial projects with Regen Pvt Ltd, Rio Tinto, Partum Engineering, and EPC Australia

  • 🌍 Member of IEEE, WIE, and Young Professional Engineers

📈 Professional Development

Dr. Uzma Amin’s professional development reflects her proactive pursuit of excellence in engineering education and practice 🌟. She received the prestigious FHEA fellowship in 2022 🎖️, recognizing her pedagogical innovation. As a vice-chair of IEEE WIE WA section in 2023, she actively organized workshops and networking events 🤝. Her consistent role as a reviewer for top-tier journals like IEEE Access and Elsevier’s Applied Energy 📑 illustrates her influence in academic circles. Her teaching, curriculum innovation, and industrial partnerships exemplify a progressive career dedicated to both research impact and engineering education transformation 💡.

🔬 Research Focus Category

Dr. Uzma Amin’s research lies primarily in Electrical Power Systems and Renewable Energy Integration ⚡🌱. Her work addresses real-world engineering problems through applied research, with a strong emphasis on renewable power generation systems, electrical machines, and energy systems optimization 🔋. With 23 publications, she contributes to fields intersecting smart grids, clean energy, and sustainable power infrastructure 🌍. Her industry collaborations with companies like Rio Tinto and Electric Power Conversions Australia underscore the applied nature of her research 🛠️. She also reviews work in computational energy analysis and advanced electrical systems, reflecting a technically diverse focus 📘.

🏅 Awards and Honors

  • 🎖️ FHEA Fellowship, 2022 – Recognized for excellence in higher education teaching

  • 👩‍💼 Vice-Chair, IEEE Women in Engineering (WIE), WA Section, 2023

  • 📝 Regular Reviewer for top journals (IEEE Access, Elsevier, MDPI, etc.)

Publication Top Notes

1. Optimal price based control of HVAC systems in multizone office buildings for demand response

  • Authors: U. Amin, M. J. Hossain, E. Fernandez

  • Journal: Journal of Cleaner Production

  • Volume: 270

  • Article No.: 122059

  • Cited by: 67

  • Year: 2020

  • Summary: This paper proposes a price-based control strategy for HVAC systems in multizone office buildings to enhance energy efficiency and responsiveness in demand-side management under smart grid settings.

2. Computational tools for design, analysis, and management of residential energy systems

  • Authors: K. Mahmud, U. Amin, M. J. Hossain, J. Ravishankar

  • Journal: Applied Energy

  • Volume: 221

  • Pages: 535–556

  • Cited by: 52

  • Year: 2018

  • Summary: The article surveys and evaluates various computational tools that assist in designing and managing residential energy systems, particularly under the influence of emerging distributed energy resources.

3. Integration of renewable energy resources in microgrid

  • Authors: M. Ahmed, U. Amin, S. Aftab, Z. Ahmed

  • Journal: Energy and Power Engineering

  • Volume: 7 (1)

  • Pages: 12–29

  • Cited by: 44

  • Year: 2015

  • Summary: This study discusses the integration strategies of renewable energy sources in microgrids and addresses the associated challenges and opportunities from technical and economic perspectives.

4. Design, construction and study of small scale vertical axis wind turbine based on a magnetically levitated axial flux permanent magnet generator

  • Authors: G. Ahmad, U. Amin

  • Journal: Renewable Energy

  • Volume: 101

  • Pages: 286–292

  • Cited by: 39

  • Year: 2017

  • Summary: This work presents a detailed design and performance analysis of a small-scale vertical axis wind turbine, incorporating a magnetically levitated generator to reduce friction and improve energy efficiency.

5. Energy trading in local electricity market with renewables—A contract theoretic approach

  • Authors: U. Amin, M. J. Hossain, W. Tushar, K. Mahmud

  • Journal: IEEE Transactions on Industrial Informatics

  • Volume: 17 (6)

  • Pages: 3717–3730

  • Cited by: 37

  • Year: 2020

  • Summary: The paper develops a contract-theoretic framework for local energy trading in a renewable-integrated smart grid setting, ensuring fair pricing and demand satisfaction.

6. Performance analysis of an experimental smart building: Expectations and outcomes

  • Authors: U. Amin, M. J. Hossain, J. Lu, E. Fernandez

  • Journal: Energy

  • Volume: 135

  • Pages: 740–753

  • Cited by: 34

  • Year: 2017

  • Summary: This study presents real-time data and performance evaluation of an experimental smart building, highlighting discrepancies between expected and actual outcomes in energy consumption and management.

🧾 Conclusion

In conclusion, Dr. Uzma Amin’s career trajectory, research excellence, and international impact make her an outstanding contender for the Best Researcher Award. Her ability to merge technical depth with practical relevance, academic influence, and community engagement embodies the spirit of a researcher committed not just to discovery but also to societal and industrial transformation. Recognizing her with this award would celebrate a truly multidimensional and forward-thinking scholar. 🏆