Sun Jong Kim | In Vitro Diagnostics | Science and Technology Pioneer Award

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Dr. Sun Jong Kim | In Vitro Diagnostics | Science and Technology Pioneer Award 

Researcher at BioFront | South Korea

Dr. Sun Jong Kim is a highly accomplished biotechnology and life sciences professional whose career reflects sustained contributions to in vitro diagnostics, stem cell science, biomolecular research, and translational biomedical innovation. Equipped with a strong academic foundation including bachelor’s, master’s, and doctoral studies in life sciences, Dr. Sun Jong Kim has developed deep expertise in cellular biology, developmental biology, and molecular mechanisms of pluripotency. His professional journey includes senior research and leadership roles across multiple biomedical organizations, where he has guided R&D programs involving the establishment and maintenance of pluripotent stem cell lines, large-scale microalgae production systems, medical device development, and regulatory preparation for diagnostic technologies. He has contributed to the development of human embryonic stem cell resources, in vitro differentiation platforms, and advanced diagnostic systems applied to areas such as oncology, COVID-19 rapid testing, and point-of-care technologies. His industrial leadership also includes oversight of product development pipelines, quality assurance systems, and multidisciplinary research operations, demonstrating an ability to translate scientific results into usable biomedical solutions that directly support clinical and research infrastructures. His research outputs include numerous scientific publications, national and international presentations, and patents in areas such as stem cell culturing techniques, photobioreactors, and biomaterial-based innovations. The measurable impact of his scholarly contribution is represented by 24 citations by 24 documents, 2 indexed documents, and an h-index of 2, reflecting ongoing engagement and recognition within the scientific community. Dr. Sun Jong Kim’s research interests encompass stem cell biology, human cell culture systems, the regulation of self-renewal and differentiation pathways, bioprocess design, clinical diagnostics, and biotechnology commercialization. His work has been supported by significant research grants and has contributed to advancements in both academic discovery and applied biomedical engineering. In addition to laboratory research, he has played a crucial role in the development, certification, and evaluation of diagnostic medical devices aligned with international regulatory standards and real-world clinical needs. Through his ongoing work at Biofront and other institutions, Dr. Sun Jong Kim continues to drive innovation in science and technology, contributing to advancements that support more accurate diagnostics, greater understanding of biological systems, and the modernization of biomedical tools used in healthcare and life science research.

Profile: Scopus

Featured Publications:

Kim, S. J.,(1999). Isolation of developmentally regulated novel genes based on sequence identity and gene expression patterns. Molecules and Cells, 9, 207–218.

Kim, S. J.,(2001). Ovarian expression of melatonin Mel(1) receptor mRNA during mouse development. Molecular Reproduction and Development, 59, 126–132.

Kim, S. J.,(2003). Isolation and culture of human embryonic stem-like cells from abnormal blastocysts. Korean Journal of Fertility and Sterility, 30, 293–301.

Kim, S. J.,(2003). Establishment and maintenance of human embryonic stem cells on STO, a permanently growing cell line. Biology of Reproduction, 69, 2007–2014.

Kim, S. J.,(2004). Establishment of embryonic germ cells from cultured human primordial germ cells and their differentiation into neuronal cells. Molecules and Cells, 17, 309–315.

Kim, S. J.,(2004). Recent advances in human embryonic stem cell research. Journal of the Korean Medical Association, 918–925.

Kim, S. J.,(2004). Effects of type IV collagen and laminin on the cryopreservation of human embryonic stem cells. Stem Cells, 22, 950–961.

Kim, S. J.,(2004). Available human feeder cells for the maintenance of human embryonic stem cells. Reproduction, 128, 727–735.

Pengfei Wei | Computer Science | Best Researcher Award

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Dr. Pengfei Wei | Computer Science | Best Researcher Award 

Senior Engineer at Guangdong University of Technology | China

Dr. Pengfei Wei is a Senior Engineer at Guangdong University of Technology, recognized for his pioneering contributions to the field of computer science, particularly in multimodal learning, knowledge tracing, edge artificial intelligence, and task-oriented dialogue systems. He holds a Ph.D. in Computer Science, where his research focused on integrating deep learning models with practical applications in intelligent education and human–machine interaction. Combining academic rigor with industrial innovation, he brings substantial experience from both enterprise research and academic development, bridging the gap between theory and real-world technology deployment. His work encompasses advanced methods such as visual-enhanced transformers for multimodal named entity recognition, genetic-inspired relation extraction, and the introduction of Kolmogorov–Arnold representations in knowledge tracing, which have improved model interpretability and performance in AI-based learning systems. In addition to his theoretical advancements, he has successfully led projects on real-time lab-safety analytics and large-scale AI deployment using Huawei Ascend, Nvidia, and TPU platforms, contributing to the broader industrial adoption of edge AI technologies. Dr. Pengfei Wei has authored numerous peer-reviewed papers in top-tier international journals and conferences, including Neural Networks, ICMR, and IJCAI, and serves as a reviewer for several prestigious publications such as Neural Networks, Pattern Recognition Letters, AAAI, and IJCNN. His collaborative initiatives with research teams and institutions have fostered multidisciplinary innovation, emphasizing the integration of AI with blockchain, big data, and education systems. A dedicated mentor and research leader, he actively supports student-led research and fosters the development of next-generation AI scholars. His professional memberships with the China Computer Federation (CCF) and the Association for Computing Machinery (ACM) reflect his strong engagement in the global computing community. Dr. Pengfei Wei’s research continues to push the boundaries of multimodal understanding and intelligent systems, driving transformative progress in computational learning and applied artificial intelligence. Through his sustained contributions, he remains committed to advancing the capabilities of intelligent technologies that enhance human productivity, knowledge discovery, and digital transformation.

Profile: Orcid | Google Scholar

Featured Publications:

  • Liao, W., B. Zeng, Yin, X., & Wei, P. (2021). An improved aspect-category sentiment analysis model for text sentiment analysis based on RoBERTa. Applied Intelligence, 51(6), 3522–3533.

  • Liao, W., Zeng, B., Liu, J., Wei, P., Cheng, X., & Zhang, W. (2021). Multi-level graph neural network for text sentiment analysis. Computers & Electrical Engineering, 92, 107096.

  • Liao, W., Zeng, B., Liu, J., Wei, P., & Fang, J. (2022). Image-text interaction graph neural network for image-text sentiment analysis. Applied Intelligence, 52(10), 11184–11198.

  • Liao, W., Zeng, B., Liu, J., Wei, P., & Cheng, X. (2022). Taxi demand forecasting based on the temporal multimodal information fusion graph neural network. Applied Intelligence, 52(10), 12077–12090.

  • Wei, P., Zeng, B., & Liao, W. (2022). Joint intent detection and slot filling with wheel-graph attention networks. Journal of Intelligent & Fuzzy Systems, 42(3), 2409–2420.

  • Wei, P., Ouyang, H., Hu, Q., Zeng, B., Feng, G., & Wen, Q. (2024). VEC-MNER: Hybrid transformer with visual-enhanced cross-modal multi-level interaction for multimodal NER. Proceedings of the International Conference on Multimedia Retrieval (ICMR 2024).

  • Wen, S., Zeng, B., Liao, W., Wei, P., & Pan, Z. (2021). Research and design of credit risk assessment system based on big data and machine learning. Proceedings of the IEEE 6th International Conference on Big Data Analytics (ICBDA 2021), 9–13.

laiba Sultan Dar | Time series analysis | Best Researcher Award

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Ms. laiba Sultan Dar | Time series analysis | Best Researcher Award 

Phd Student at Abdul wali khan university | Pakistan

Ms. Laiba Sultan Dar is a dedicated researcher and Ph.D. scholar at Abdul Wali Khan University, specializing in time series analysis and decomposition techniques. Her academic journey is marked by a strong foundation in applied mathematics and data analytics, enabling her to contribute effectively to statistical modeling, forecasting, and computational research. She has developed expertise in identifying patterns and trends within large datasets, applying modern analytical frameworks to address complex problems in areas such as economics, climate studies, and system optimization. Her research integrates both theoretical and empirical approaches, focusing on improving the precision and interpretability of time-dependent models. Through her doctoral studies, she has actively engaged in institutional research projects and contributed to scholarly publications in recognized international journals, including those indexed by Scopus and ScienceDirect. Her work demonstrates a balance between mathematical rigor and practical application, particularly in designing adaptive models for real-world data forecasting. In addition to her academic pursuits, Ms. Laiba Sultan Dar has shown growing involvement in research collaborations and interdisciplinary studies that bridge statistical science and technological innovation. Her ability to combine methodological sophistication with computational efficiency has made her research relevant to emerging domains such as artificial intelligence-driven data analysis and predictive modeling. She continuously enhances her research capabilities by incorporating advanced tools and techniques, fostering a deeper understanding of time series dynamics. With a citation index reflecting the recognition of her early scholarly efforts, she remains committed to producing impactful research that advances statistical methodologies and contributes to data-driven decision-making. Her intellectual curiosity and analytical acumen position her as a promising researcher in quantitative sciences. Ms. Laiba Sultan Dar’s long-term goal is to strengthen the integration of mathematical modeling with applied sciences, promoting innovation and scientific development in her field. Her commitment to excellence, collaborative mindset, and ongoing pursuit of research excellence make her a deserving candidate for recognition among emerging scholars in data analytics and statistical research.

Profile: Google Scholar

Featured Publications:

  • Dar, L., Akmal, A., Naseem, M. A., & Khan, K. U. D. (2011). Impact of stress on employees’ job performance in the business sector of Pakistan. Global Journal of Management and Business Research, 11(6), 1–4.

  • Dar, L. A., Naseem, M. A., Rehman, R. U., & Niazi, G. S. (2011). Corporate governance and firm performance: A case study of Pakistan oil and gas companies listed in Karachi Stock Exchange. Global Journal of Management and Business Research, 11(8), 1–10.

  • Malik, M., Wan, D., Dar, L., Akbar, A., & Naseem, M. A. (2014). The role of work-life balance in job satisfaction and job benefit. Journal of Applied Business Research (JABR), 30(5), 1627–1638.

  • Dar, L. S., Aamir, M., Khan, Z., Bilal, M., Boonsatit, N., & Jirawattanapanit, A. (2022). Forecasting crude oil price volatility by reconstructing EEMD components using ARIMA and FFNN models. Frontiers in Energy Research, 10, 991602.

  • Dar, L. S., Aamir, M., Bibi, S., & Bilal, M. (2025). A novel robust adaptive decomposition approach for solar energy potential using atmospheric transparency and UV radiation indicators. Journal of Radiation Research and Applied Sciences, 18(4), 101946.

  • Dar, L. S., Aamir, M., Hamraz, M., Faiz, N., Emam, W., & Tashkandy, Y. (2025). A robust adaptive signal decomposition method for enhanced mode extraction in financial time series. IEEE Access.

  • Saleem, Q., Dar, L., Shahid, M., & Rana, S. (2012). A quantitative analysis of the role of human resource development in economic growth in Pakistan. International Journal of Management Sciences and Business Research.

  • Bilal, M., Aamir, M., Abdullah, S., Mahmood, N., Khalil, U., Khalid, N., Ahmed, M., & Dar, L. (2022). Assessment of the COVID-19 pandemic’s impact on gasoline prices in Pakistan. VFAST Transactions on Mathematics, 10(2), 52–67.

Gholamreza Dehghan | Biochemistry | Best Researcher Award

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Prof. Gholamreza Dehghan | Biochemistry | Best Researcher Award

Professor at University of Tabriz, Iran.

🌍Dr. Gholamreza Dehghan is a distinguished Professor of Biochemistry at the University of Tabriz with extensive contributions to enzymology, nanotechnology, and biosensing. His research explores enzyme mechanisms, theranostics for cancer, and the integration of artificial intelligence in drug design and protein structure prediction. With over 270 peer-reviewed publications and multiple awards, including being recognized among the top 2% of scientists globally in biochemistry, Dr. Dehghan exemplifies innovation and academic leadership.

Profile👤

Education 🎓

🎓Dr. Gholamreza Dehghan earned his Ph.D. in Biochemistry in 2007 from the University of Tehran, where he studied the antioxidant and anticancer effects of natural compounds. He holds an M.Sc. in Biochemistry, focusing on innovative diagnostic methods for autoimmune diseases, and a B.Sc. in Biology from the University of Tabriz. His academic foundation combines deep theoretical knowledge and practical expertise, enabling transformative research in enzymology, nanotechnology, and biosensing. 🎓📚

Experience💼

🩺Dr. Dehghan has over 16 years of academic experience, beginning as an Assistant Professor at the University of Tabriz in 2007 and becoming a full Professor in 2016. He has served as Dean and Vice Dean of the Faculty of Natural Sciences, contributing to curriculum development and research strategies. As Director of Student Affairs, he fosters academic excellence and student mentorship. His executive roles in regional science councils and innovation parks highlight his leadership in bridging academia and industry. 🧑‍🔬📈

Awards and Honors 🏆

Dr. Dehghan has received several accolades, including being named among the top 2% of scientists in biochemistry by Elsevier. He was awarded the Outstanding Researcher of the Faculty Award twice and recognized as a distinguished lecturer at the University of Tabriz’s ARAS campus. His pioneering work in theranostics, nanotechnology, and biosensing has earned him global recognition, cementing his reputation as an influential figure in biochemical research. 🏅🌍

Research Interests 🔬

🔬Dr. Dehghan’s research revolves around enzymology, focusing on catalytic mechanisms and protein characterization. He develops nanomaterial-based biosensors for ultra-sensitive detection and theranostic applications in cancer. Leveraging artificial intelligence, his team explores machine learning in drug design and molecular dynamics for protein studies. His work addresses pressing challenges in health, environment, and biotechnology, making impactful advancements in science.🔬🧬

Conclusion 🔚 

Dr. Gholamreza Dehghan is a highly deserving candidate for the Best Researcher Award, showcasing an exceptional career of innovation, mentorship, and academic excellence. While his outreach and diversification efforts could further enhance his profile, his achievements already position him as a leader in biochemistry and interdisciplinary sciences.

Publications Top Notes 📚

PAMAM dendrimers as efficient drug and gene delivery nanosystems for cancer therapy

Authors: F. Abedi-Gaballu, G. Dehghan, M. Ghaffari, R. Yekta, et al.

Citations: 421

Year: 2018

Tin (II)–quercetin complex: Synthesis, spectral characterization and antioxidant activity

Authors: G. Dehghan, Z. Khoshkam

Citations: 269

Year: 2012

Biological treatment of a dye solution by Macroalgae Chara sp.: Effect of operational parameters, intermediates identification and artificial neural network modeling

Authors: A.R. Khataee, G. Dehghan, A. Ebadi, M. Zarei, M. Pourhassan

Citations: 224

Year: 2010

Benefits of Zataria multiflora Boiss in Experimental Model of Mouse Inflammatory Bowel Disease

Authors: L.A. Nakhai, A. Mohammadirad, N. Yasa, B. Minaie, S. Nikfar, G. Ghazanfari, G. Dehghan, et al.

Citations: 182

Year: 2007

Antidiabetic effect of Phlomis anisodonta: effects on hepatic cells lipid peroxidation and antioxidant enzymes in experimental diabetes

Authors: P. Sarkhail, S. Rahmanipour, S. Fadyevatan, A. Mohammadirad, G. Dehghan, et al.

Citations: 151

Year: 2007

In vivo antioxidant potential of Teucrium polium, as compared to α-tocopherol

Authors: P. Hasani, N. Yasa, S. Vosough-Ghanbari, A. Mohammadirad, G. Dehghan, et al.

Citations: 148

Year: 2007

Co-delivery of curcumin and Bcl-2 siRNA by PAMAM dendrimers for enhancement of the therapeutic efficacy in HeLa cancer cells

Authors: M. Ghaffari, G. Dehghan, B. Baradaran, A. Zarebkohan, B. Mansoori, et al.

Citations: 135

Year: 2020

Biochemical and Histopathological Evidences for Beneficial Effects of Satureja Khuzestanica Jamzad Essential Oil on the Mouse Model of Inflammatory Bowel Disease

Authors: G. Ghazanfari, B. Minaie, N. Yasa, L.A. Nakhai, A. Mohammadirad, S. Nikfar, G. Dehghan, et al.

Citations: 133

Year: 2006

Spectroscopic studies on the interaction of quercetin–terbium (III) complex with calf thymus DNA

Authors: G. Dehghan, J.E.N. Dolatabadi, A. Jouyban, K.A. Zeynali, S.M. Ahmadi, et al.

Citations: 117

Year: 2011

Neural network modeling of biotreatment of triphenylmethane dye solution by a green macroalgae

Authors: A.R. Khataee, G. Dehghan, M. Zarei, E. Ebadi, M. Pourhassan

Citations: 115

Year: 2011

 

 

 

Sandhini Agarwal | Medicine | Best Researcher Award

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Ms. Sandhini Agarwal | Medicine | Best Researcher Award

Medical Student at Valley Vein Health Center, Georgetown University School of Medicine, United States.

🌍Sandhini Agarwal is a medical student at Georgetown University, with extensive experience in clinical settings, research, and leadership. She has worked as a research assistant at UChicago Medicine and Stanford Medicine, focusing on neural network-based systems, pediatric cardiology, and thyroid cancer. Her clinical experience spans pediatrics, ambulatory care, and community health outreach. Additionally, she has held leadership roles in organizations such as Georgetown Street Medicine and the Phoenix Biology RSO at UChicago. She has also been an active volunteer with Street Life Ministries and has received numerous academic awards.

Profile👤

Education 🎓

🎓Sandhini Agarwal attended the University of Chicago, where she earned a B.S. in Biological Sciences and a minor in Health and Society, graduating cum laude with a GPA of 3.88/4.0. During her time at UChicago, she was consistently recognized for her academic excellence, making the Dean’s List from 2021 to 2022 and earning the Clinical Excellence Scholars Track recognition. She also received multiple awards during high school, including the Senior Book Award in Biology and the Faculty Cup Nominee. Sandhini is currently pursuing her medical degree at Georgetown University School of Medicine, Class of 2028. Her academic focus continues to center around biology, medicine, and public health, with a particular interest in addressing health disparities and improving healthcare access for underserved communities. Sandhini’s academic achievements reflect her commitment to excellence and her determination to make a meaningful impact in the medical field.

Experience💼

🩺Sandhini Agarwal has extensive clinical and research experience that spans multiple prestigious institutions. She is currently involved in clinical work at Georgetown Med, including shadowing Dr. Sejal Bavishi in pediatric outpatient clinics and assisting with physical exams. She also plays a key role in community health initiatives through Hoya Clinic and Learn2Derm, where she educates underserved children on skincare. Prior to Georgetown, Sandhini gained valuable experience at UChicago Medicine, conducting patient interviews as a research assistant for the Hospitalist Project. She also worked at Valley Vein Health Center as a patient care coordinator, conducting surveys and researching Ozempic’s impact on lymphedema. In addition to her clinical roles, Sandhini has participated in research at institutions such as Stanford, where she worked on developing neural network-based systems for medical imaging, and at Harvard Medicine, where she researched thyroid cancer pathways. Her experiences in both clinical care and research have provided her with a comprehensive understanding of healthcare.👨‍🔬🌍

Awards and Honors 🏆

Sandhini Agarwal has received several prestigious awards for her academic and extracurricular achievements. At the University of Chicago, she earned a spot on the Dean’s List from 2021 to 2022 and participated in the Clinical Excellence Scholars Track, recognizing her academic prowess and commitment to clinical excellence. In high school, she received multiple honors, including the Senior Book Award in Biology and the Faculty Cup Nominee. Sandhini was also recognized as a National AP Scholar for her high AP scores and received the Katen Metcalf Scholar award in 2021. She was honored with the Aspirations Award by the National Center for Women & Information Technology in 2018 and won several medals in the National Spanish Exam, including Gold in 2017. Sandhini’s accomplishments reflect her strong academic background and her commitment to leadership, service, and excellence in healthcare.

Research Interests 🔬

🔬Sandhini Agarwal’s research focuses on the intersection of biology, medicine, and technology, with a particular interest in pediatric cardiology, endocrinology, and neuroimaging. At UChicago Medicine, she researched FoxF1 expression in the second heart field and its role in cardiomyocyte differentiation and heart development. This work contributed to the understanding of heart disease and its underlying mechanisms. She also worked on analyzing thyroid cancer pathways at Harvard Medicine, focusing on the diagnosis-to-treatment process for thyroid cancer patients. Sandhini’s research experience extends to neural networks for medical imaging at Stanford, where she developed a system to segment brain parenchymal metastatic lesions using radiological data. In addition, she contributed to cardiovascular drug discovery at UChicago, analyzing genomic data and supporting the HeartBioPortal database. Sandhini’s research aims to enhance healthcare delivery and outcomes, with a particular focus on improving diagnostic accuracy, treatment pathways, and patient care, especially in underserved populations.🌿🧪

Conclusion 🔚 

Sandhini Agarwal is highly deserving of the Best Researcher Award. Her dedication to both research and clinical practice, combined with her leadership in social initiatives, demonstrates a holistic approach to the field of medicine. Her achievements indicate a future leader in healthcare and research, and her continued contributions promise even greater impacts in the years to come.

Publications Top Notes 📚

A Holistic Approach to Undesired Content Detection in the Real World

Authors: Markov, T., Zhang, C., Agarwal, S., Jiang, A., Weng, L.

Citations: 35

Year: 2023

Training language models to follow instructions with human feedback

Authors: Ouyang, L., Wu, J., Jiang, X., Leike, J., Lowe, R.

Citations: 3,339

Year: 2022

Learning Transferable Visual Models From Natural Language Supervision

Authors: Radford, A., Kim, J.W., Hallacy, C., Krueger, G., Sutskever, I.

Citations: 9,325

Year: 2021

Language models are few-shot learners

Authors: Brown, T.B., Mann, B., Ryder, N., Sutskever, I., Amodei, D.

Citations: 15,410

Year: 2020

Recursive routing networks: Learning to compose modules for language understanding

Authors: Cases, I., Rosenbaum, C., Riemer, M., Potts, C., Karttunen, L.

Citations: 11

Year: 2019