Samira Azizi | Engineering | Best Researcher Award

Posted on by phenomenological Research

Ms. Samira Azizi | Engineering | Best Researcher Award

Ph.D candidate at Politecnico di Milano, Italy.

Samira Azizi 🎓 is a Ph.D. candidate at Politecnico di Milano 🇮🇹, specializing in smart structural control and vision-based structural health monitoring (SHM) 🏗️📹. Her work focuses on enhancing earthquake resilience through real-time damage detection and adaptive stiffness systems 🌐⚙️. She has contributed significantly to full-field motion estimation using video data and advanced optimization techniques such as particle swarm algorithms 🧠📈. As a dedicated researcher, Samira serves on editorial boards 📚, reviews for prestigious journals ✍️, and engages in innovative, non-contact SHM technologies. Her passion lies in bridging advanced engineering with intelligent monitoring solutions 🌍💡.

Professional Profile:

Scopus

ORCID

Suitability For Best Researcher Award:

Samira Azizi is highly suitable for the Best Researcher Award based on her cutting-edge research, interdisciplinary innovation, and global academic engagement. Her work bridges structural engineering, artificial intelligence, and computer vision, with a clear focus on non-contact, vision-based structural health monitoring (SHM) — a domain crucial for infrastructure safety in earthquake-prone regions. Her leadership as a peer reviewer and editorial board member, combined with impactful publications and innovative methodologies, demonstrate excellence and commitment to advancing civil engineering research.

🔹 Education & Experience

🎓 Education:

  • Ph.D. Candidate in Structural Engineering – Politecnico di Milano, Italy 🇮🇹

  • Research background in system identification, control systems, and structural health monitoring 🏗️

💼 Experience:

  • Short-term research contract (ongoing) at Politecnico di Milano 🔬

  • Peer reviewer for journals including PLOS ONE, Engineering Structures, and Experimental Mechanics 📰

  • Editorial board member of Frontiers in Built Environment 📖

  • Published multiple high-impact research papers in SCI/Scopus-indexed journals 📑

🔹 Professional Development

Samira Azizi has demonstrated exceptional professional growth through collaborative research projects and technical expertise in system dynamics and SHM technologies 🔍🤝. Her editorial roles and frequent peer reviewing across top journals reflect her critical thinking and in-depth knowledge 📘🔬. She continues to refine her research acumen by actively engaging in advanced image processing and video-based structural analysis 📹🧠. With a focus on non-contact, intelligent monitoring frameworks, she is also pursuing a research contract at Politecnico di Milano, enhancing her academic trajectory 🚀. Samira’s constant pursuit of innovation and precision defines her as a rising star in engineering research 🌟📐.

🔹 Research Focus Area

Samira’s research centers on vision-based structural identification and control systems 🎥🏗️. Her innovative work bridges civil engineering with artificial intelligence and image processing 🤖📸, aiming to improve structural integrity assessment without physical sensors. She develops non-contact, video-based motion estimation frameworks that track both macro and subpixel movements, ideal for real-time damage detection ⚡🔧. By integrating tools like particle swarm optimization and complexity pursuit, her studies push forward the field of output-only modal analysis 🌀📉. Her goal is to create sustainable, smart monitoring systems for resilient infrastructure in seismically active regions 🌍🛠️.

🔹 Awards & Honors

🏆 Awards & Recognitions:

  • ✨ Selected editorial board member – Frontiers in Built Environment

  • 🏅 Reviewer for reputed journals: PLOS ONE, Engineering Structures, Experimental Mechanics, etc.

  • 📝 Multiple peer-reviewed journal publications in top-tier SCI/Scopus outlets

  • 🎓 Invited speaker and contributor at international conferences (e.g., ECSA-10)

  • 🌐 Recognized for developing innovative semi-active stiffness control systems and full-field video measurement techniques

Publication Top Notes

Article Title:

Structural Identification Using Digital Image Correlation Technology

Authors:

  • Samira S. Azizi

  • Kaveh K. Karami

  • Stefano S. Mariani

Published in:

Engineering Proceedings, 2023
Access: Open Access (Link currently disabled)

Abstract Summary

This paper explores the application of Digital Image Correlation (DIC) technology for structural identification in engineering systems. DIC is a non-contact optical method used to measure deformation, displacement, and strain by tracking speckle patterns on the surface of materials. The study focuses on the implementation of DIC to assess the structural response under various loading conditions. Through experimental validation and comparative analysis, the authors demonstrate the effectiveness of DIC in enhancing the accuracy and reliability of structural health monitoring techniques.

🏁 Conclusion:

Samira Azizi exemplifies the qualities of a Best Researcher Award recipient. Her interdisciplinary approach, scientific rigor, and global academic engagement place her at the forefront of innovation in structural engineering. She is not only shaping the future of smart infrastructure but also elevating the standards of academic research and collaboration. Awarding her this recognition would honor a truly transformative contributor to engineering science.

JUN WON HO | Computer Engineering | Best Researcher Award

Posted on by phenomenological Research

Dr. JUN WON HO | Computer Engineering | Best Researcher Award

Research Fellow at Incheon National University, South Korea.

Dr. Jun Won-Ho 🎓 is a dedicated Research Fellow at Incheon National University, South Korea 🇰🇷. He earned his Ph.D. in Computer Engineering in February 2023 🧠, focusing on sleep pattern analysis in an unconscious, non-intrusive state 🛏️. His innovations aim to revolutionize sleep health through biosensor-based technologies 💡. With peer-reviewed publications in SCI-indexed journals 📚 and a patent on body weight estimation while lying in bed 🧾, Dr. Jun is making sleep monitoring accessible and home-based. His work bridges healthcare and engineering, offering practical solutions for sleep apnea detection 🩺 using biosensors and ambient signals 🌐.

Professional Profile:

ORCID

Suitability for Best Researcher Award – Dr. Jun Won-Ho

Dr. Jun Won-Ho is highly suitable for the Best Researcher Award due to his pioneering research at the intersection of biomedical engineering and computer science. Despite being an early-career researcher, he has demonstrated remarkable innovation and scientific productivity, especially in the field of non-intrusive sleep health monitoring. His Ph.D. and postdoctoral work have resulted in SCI-indexed journal publications, a granted patent, and the development of AI-based, contact-free technologies to address global health concerns like sleep apnea—showing both originality and real-world impact.

🎓 Education and Experience

  • 🎓 Ph.D. in Computer Engineering – Incheon National University (2023)

  • 🧪 Research Fellow – Incheon National University (Current)

  • 📄 Published in SCI-indexed journals – Including Sensors

  • 🛏️ Doctoral Research – Focused on unobtrusive sleep pattern analysis

  • 🔬 Ongoing Research – Development of self-screening technology for sleep apnea

  • 🧾 Patent Holder – System for estimating body weight while lying on a bed

🚀 Professional Development

Dr. Jun Won-Ho has significantly contributed to the field of sleep science and biomedical engineering 🧠. His journey began with a strong academic foundation in computer engineering 🎓, which he has transformed into impactful research focused on real-world health challenges 🩺. He has authored articles in SCI-indexed journals 📚 and currently works on a cutting-edge sleep apnea screening solution using biosensors and environmental data 🌙📊. His patented invention 🧾 and active engagement in non-contact health monitoring technologies reflect his innovative mindset and commitment to improving global health accessibility 🌍💡.

🧬 Research Focus Category

Dr. Jun Won-Ho’s research falls under the category of Biomedical Engineering and Sleep Science 🧠🛌. He is especially focused on unobtrusive health monitoring, developing systems that use biosensors, physiological signals, and environmental data to analyze sleep patterns and detect sleep disorders like apnea 😴🩺. His goal is to eliminate the need for intrusive clinical testing such as polysomnography 🧪 and instead offer home-based, AI-powered health solutions 🌐📲. His patented work on weight estimation during sleep complements his broader mission of advancing digital health technologies for continuous, contact-free care 🧾💡.

🏅 Awards and Honors

  • 🧾 Patent Granted – System for Estimating Body Weight While Lying on a Bed (KR 10-2556030)

  • 📄 SCI-Indexed Publications – Published 2 articles in renowned journals like Sensors

  • 📌 Ph.D. Achievement – Doctorate completed with impactful research in 2023

  • 🏆 Nominated for Best Researcher Award – For contributions to biomedical sleep technology

  • 🧠 Research Innovation Recognition – Development of non-contact sleep apnea screening system

Publication Top Notes

1. Detection of Sleep Posture via Humidity Fluctuation Analysis in a Sensor-Embedded Pillow

  • Published: April 30, 2025

  • Journal: Bioengineering

  • DOI: 10.3390/bioengineering12050480

  • Summary: This study introduces a novel method for detecting sleep posture by analyzing humidity fluctuations using sensors embedded in a pillow. The system monitors changes caused by respiration and perspiration, offering a non-invasive approach to sleep posture detection.

2. Sleep Pattern Analysis in Unconstrained and Unconscious State

  • Published: November 29, 2022

  • Journal: Sensors

  • DOI: 10.3390/s22239296

  • Citation Count: 6

  • Summary: This research analyzes sleep patterns in individuals without physical constraints or active awareness. Utilizing various sensors, the study collects physiological and environmental data to classify sleep stages, providing insights into natural sleep behaviors.MDPI

3. Multi-Sensor Data Fusion with a Reconfigurable Module and Its Application to Unmanned Storage Boxes

  • Published: July 19, 2022

  • Journal: Sensors

  • DOI: 10.3390/s22145388

  • Citation Count: 12

  • Summary: This paper presents a reconfigurable module for multi-sensor data fusion, applied to unmanned storage boxes. By integrating data from various sensors, the system enhances reliability and security in automated storage environments.

Conclusion

Dr. Jun Won-Ho exemplifies the qualities of a Best Researcher Award recipient through his innovative mindset, impactful biomedical applications, and commitment to global health technology advancement. His work is not only academically rigorous but also practically transformative, making essential health monitoring more accessible, affordable, and patient-friendly. He stands out as a rising star in biomedical engineering, well-deserving of this prestigious recognition.

Yumeng Su | Engineering | Best Researcher Award

Posted on by phenomenological Research

Mr. Yumeng Su | Engineering | Best Researcher Award

Mr. Yumeng Su at Shanghai Jian Qiao University, China.

Su Yumeng 🎓, a top-ranking computer science undergraduate at Shanghai Jian Qiao University 🇨🇳, excels in AI 🤖, robotics 🚁, and embedded systems 🧠. With hands-on experience in drone development, ROS, and deep learning 💡, he has published impactful research and led award-winning teams 🏆. His technical expertise spans Python, MATLAB, LaTeX, and advanced hardware platforms like Jetson Nano and STM32 💻. Beyond academics, he’s a dynamic leader and athlete 🏀🚴‍♂️, known for his resilience and innovation in intelligent systems and smart hardware applications 🔍. Su’s work bridges theoretical AI with real-world applications 🌐.

Publication Top Notes

ORCID

Suitability for Best Researcher Award – Su Yumeng

Su Yumeng is a highly promising and exceptionally driven early-career researcher whose blend of technical excellence, innovation, and leadership places him as a top contender for the Best Researcher Award. As an undergraduate, his hands-on contributions to AI, robotics, and embedded systems are not only commendable but groundbreaking, particularly for his academic level. He demonstrates a rare ability to translate theory into impactful real-world applications, bridging research with innovation in autonomous systems, drone technology, and intelligent hardware solutions.

🔹 Education & Experience

  • 🎓 B.Sc. in Computer Science & Technology, Shanghai Jian Qiao University (2021–Present)

  • 📍 Focus: AI, Robotics, Embedded Systems, and Smart Hardware

  • 📚 Completed key courses with top grades (AI, Python, Robotics, Microcontroller Principles, etc.)

  • 🚀 ROS training at East China Normal University (Basic & Advanced UAV/Vehicle Tracking)

  • 🛠 Internship at Superdimension Technology Space: Autonomous drone development

  • 🧪 Project collaboration with FAST-Lab at Zhejiang University on UAVs

🔹 Professional Development

Su Yumeng continually advances his professional skills through academic projects 🧪, interdisciplinary competitions 🏆, and real-world UAV applications 🚁. He has mastered the integration of AI models like YOLO with edge computing platforms such as Jetson Nano and Raspberry Pi 💻. His leadership in innovation competitions reflects his capacity to guide teams and deliver impactful solutions 🎯. Su’s deep involvement in research and drone design demonstrates his ability to convert academic concepts into cutting-edge technology 💡. With practical ROS experience and sensor fusion expertise, he remains at the forefront of smart automation and robotics 🌐.

🔹 Research Focus Category

Su Yumeng’s research focuses on Artificial Intelligence in Embedded and Autonomous Systems 🤖, especially in smart robotics and deep learning applications for environmental perception and control 🌍. His work bridges physics-informed neural networks (PINNs) with real-time sensor fusion for drones and robotics 🤝. He explores practical challenges like crack detection in infrastructure using UAVs 🛠️, baby posture recognition on embedded platforms 🍼, and SLAM-based navigation for wheeled robots 🚗. His interdisciplinary approach merges hardware innovation with AI, yielding scalable, intelligent, and responsive systems suitable for civil engineering, healthcare, and autonomous mobility fields 🚀.

🔹 Awards & Honors

  • 🥇 National Second Prize, 17th National College Student Computer Design Competition (2024)

  • 🥉 National Bronze & Shanghai Gold, China Innovation Competition (2024)

  • 🥇 Shanghai Gold Award, Career Planning Competition (2024)

  • 🏅 First Prize, Shanghai College Student Computer Application Competition (2024)

  • 🥈 Shanghai Second Prize, Ti Cup Electronic Design Contest (2023)

  • 🥉 Bronze Award, “Challenge Cup” Entrepreneurship Plan Competition

  • 🥉 Shanghai Third Prize, China Robot & AI Competition (2024)

  • 🎖 National Motivational Scholarship ×3

  • 🎓 President “Qing Yun” Scholarship

  • 🎗 School Special Scholarship

Publication Top Notes

  • “The Feasibility Assessment Study of Bridge Crack Width Recognition in Images Based on Special Inspection UAV”
    Cited by: 13 | Year: 2020 ​

  • “Intelligent Crack Detection and Quantification in the Concrete Bridge: A Deep Learning-Assisted Image Processing Approach”
    Cited by: 20 | Year: 2022

Conclusion

Su Yumeng’s combination of academic excellence, deep technical knowledge, hands-on innovation, and research impact clearly distinguishes him as an ideal recipient of the Best Researcher Award. His contributions as an undergraduate are extraordinary and reflect the potential of a future global leader in AI and robotics research.

Ali Alshamrani | Engineering | Best Researcher Award

Posted on by phenomenological Research

Ali Alshamrani | Engineering | Best Researcher Award

Assistant professor at Taifuniversity, Saudi Arabia.

Dr. Ali M. Alshamrani is an accomplished mechanical engineer with a strong background in both academia and industry. Currently serving as an Assistant Professor at Taif University, his expertise lies in fluid mechanics, oil spill behavior, and renewable energy. His extensive research has led to multiple peer-reviewed publications in reputable journals, focusing on areas such as oil slick contraction and fragmentation, and renewable energy solutions like solar distillation. With a solid foundation in teaching and research, Dr. Alshamrani continues to contribute significantly to the advancement of mechanical engineering.

📚 Profile

Scopus

🎓 Education

Dr. Alshamrani earned his Ph.D. in Mechanical Engineering from the University of South Florida (USF) in 2022, graduating with an impressive GPA of 3.9/4.0. His doctoral studies focused on fluid mechanics, material science, and oil spill behavior. He also completed his M.Eng. at USF in 2018 with a GPA of 3.86/4.0, where he conducted research on material sciences and manufacturing processes. Dr. Alshamrani’s academic journey began with a B.Sc. in Mechanical Engineering from Umm Al Qura University in 2014, where he worked on a vortex tube cooler for his graduation project.

💼 Experience

Dr. Alshamrani’s experience spans both industry and academia. He completed internships at Saudi Aramco and King Abdullah & Al Salam Co., where he gained hands-on experience in refinery operations, aircraft maintenance, and construction projects. In academia, he has held teaching positions, including as a lecturer and lab instructor at Taif University, and as a teaching and research assistant at USF. Currently, as an Assistant Professor at Taif University, he teaches courses on fluid mechanics, heat transfer, and fluid dynamics while continuing his research in mechanical engineering.

🔬 Research Interests

Dr. Alshamrani’s research interests focus on fluid mechanics, oil spill dynamics, and renewable energy systems. His work has explored the contraction and fragmentation of crude oil slicks using chemical herders, an innovative approach to oil spill mitigation. He is also involved in research on the design and performance of wind turbines and solar distillers. His interest in combining mechanical engineering principles with environmental challenges positions him at the forefront of sustainable engineering solutions.

🏆 Awards and Honors

Throughout his academic career, Dr. Alshamrani has consistently demonstrated excellence, reflected in his high GPAs during his graduate studies. His research has been recognized at international conferences, including the American Physical Society’s Division of Fluid Dynamics meetings, where his work on oil spill dynamics was featured. Additionally, his contributions to the study of renewable energy technologies have garnered attention within the academic community, further cementing his reputation as a leading researcher in his field.

🔚 Conclusion

Dr. Ali M. Alshamrani is highly qualified for a Best Researcher Award due to his academic excellence, impactful research contributions, and teaching achievements. His expertise in mechanical engineering, particularly fluid mechanics and oil spill research, combined with his real-world industry experience, makes him a strong contender. Expanding his research scope and fostering international collaboration could further strengthen his candidacy in future awards.

Publications Top Notes 📚

Application of an AI-based optimal control framework in smart buildings using borehole thermal energy storage combined with wastewater heat recovery
Alshamrani, A., Abbas, H.A., Alkhayer, A.G., El-Shafay, A.S., Kassim, M.
Journal of Energy Storage, 2024, 101, 113824
Citations: 0

Insights into water-lubricated transport of heavy and extra-heavy oils: Application of CFD, RSM, and metaheuristic optimized machine learning models
Alsehli, M., Basem, A., Jasim, D.J., Musa, V.A., Maleki, H.
Fuel, 2024, 374, 132431
Citations: 2

Enhancing pyramid solar still performance using suspended v-steps, reflectors, Peltier cooling, forced condensation, and thermal storing materials
Alshamrani, A.
Case Studies in Thermal Engineering, 2024, 61, 105109
Citations: 0

Conceptual design and optimization of integrating renewable energy sources with hydrogen energy storage capabilities
Zhao, Q., Basem, A., Shami, H.O., Ahmed, M., El-Shafay, A.S.
International Journal of Hydrogen Energy, 2024, 79, pp. 1313–1330
Citations: 1

Intelligent computing approach for the bioconvective peristaltic pumping of Powell–Eyring nanofluid: heat and mass transfer analysis
Akbar, Y., Huang, S., Alshamrani, A., Alam, M.M.
Journal of Thermal Analysis and Calorimetry, 2024, 149(15), pp. 8445–8462
Citations: 1

Dimensionless dynamics: Multipeak and envelope solitons in perturbed nonlinear Schrödinger equation with Kerr law nonlinearity
Afsar, H., Peiwei, G., Alshamrani, A., Alam, M.M., Aljohani, A.F.
Physics of Fluids, 2024, 36(6), 067126
Citations: 2

Intelligent computing for the electro-osmotically modulated peristaltic pumping of blood-based nanofluid
Akbar, Y., Çolak, A.B., Huang, S., Alshamrani, A., Alam, M.M.
Numerical Heat Transfer; Part A: Applications, 2024
Citations: 0

Neural network design for non-Newtonian Fe3O4-blood nanofluid flow modulated by electroosmosis and peristalsis
Akbar, Y., Huang, S., Alshamrani, A., Alam, M.M.
Modern Physics Letters B, 2024, 2450394
Citations: 1

Analysis of interfacial heat transfer coefficients in squeeze casting of AA6061 aluminum alloy with H13 steel die: Impact of section thickness on thermal behavior
Khawale, V.R., Alshamrani, A., Palanisamy, S., Sharma, M., Alrasheedi, N.H.
Thermal Science, 2024, 28(1), pp. 223–232
Citations: 0

Investigation of the performance of a double-glazing solar distiller with external condensation and nano-phase change material
Alshamrani, A.
Journal of Energy Storage, 2023, 73, 109075
Citations: 4