Laxmi Kantham Durgam | Deep Learning | Best Scholar Award

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Mr. Laxmi Kantham Durgam | Deep Learning | Best Scholar Award

National Institute of Technology Warangal | India

Publication Profile

Google Scholar

🧑‍🎓 Education

Mr. Laxmi Kantham Durgam is currently pursuing his PhD in Electrical Engineering at National Institute of Technology Warangal, Telangana, India (2021–Present). His research focuses on Speech Recognition, Age and Gender Identification from Speech, and the application of Machine Learning and Deep Learning techniques. He is also a Visiting Researcher at the Technical University of Kosice, Slovakia, as part of the NSP SAIA Fellowship (2024). Mr. Durgam holds an M.Tech in Digital Systems and Computer Electronics from Jawaharlal Nehru Technological University, Hyderabad (2017–2020) and a B.Tech in Electronics and Communication Engineering from the same institution (2011–2015).

📚 Publications

Mr. Durgam has contributed to various publications in the fields of speech processing, deep learning, and edge computing. His notable works include papers on speaker age and gender classification, real-time age estimation from speech, and dress code detection using MobileNetV2 on NVIDIA Jetson Nano. He has been published in journals like Computing and Informatics and Journal of Signal Processing Systems, as well as conferences like ICIT-2023 in Kyoto, Japan.

🔬 Research Experience

Since 2021, Mr. Durgam has been a PhD Research Scholar at NIT Warangal, where his research includes projects on real-time age identification from speech using Edge devices like Jetson Nano and Arduino Nano BLE. He has also worked on real-time projects like vehicle logo classification using Edge Impulse and dress code detection using MobileNetV2. His work is focused on implementing Machine Learning and Deep Learning algorithms for practical, real-time applications.

🏆 Fellowships and Awards

Mr. Durgam was awarded the NSP SAIA Fellowship (2024), an international mobility program funded by the European Union, allowing him to collaborate with the KEMT, Faculty of Electrical Engineering and Informatics at the Technical University of Kosice, Slovakia. He also received the MHRD Fellowship for his PhD from the Government of India. He has passed the NITW PhD Entrance and the GATE exam (2016), and he received financial support as an undergraduate student from the Andhra Pradesh State Government.

📖 Academic Achievements

Mr. Durgam has significantly contributed to the academic environment through his role in conducting hands-on programming sessions in Machine Learning, Deep Learning, and AI applications. He has mentored students in Faculty Development Programs (FDPs), summer and winter internships, and workshops at various institutions. His workshops have reached institutions such as BRIT Vijayanagaram and VBIT Hyderabad, where he focused on advanced deep learning applications on Edge devices.

💻 Technical Skills

Mr. Durgam is highly skilled in programming with languages like Python, C, Embedded C, Matlab, and frameworks such as Keras, TensorFlow, and OpenCV. He has experience working with edge devices like Jetson Nano, Jetson Xavier, and Arduino Nano BLE 33 Sense. His expertise also extends to Machine Learning, Deep Learning, Computer Vision, and Digital Signal Processing.

🧑‍🏫 Teaching and Mentoring

Mr. Durgam has been an active Teaching Assistant and mentor at NIT Warangal, where he has assisted in courses like Artificial Intelligence, Machine Learning, and Digital Signal Processing. He has guided B.Tech students in lab sessions, and his expertise in AI/ML has also been shared through guest lectures and faculty development programs.

🚀 Key Projects

Some of Mr. Durgam’s key projects include age and gender estimation from speech using MFCC features, dress code detection with MobileNetV2 on Edge devices, and real-time object detection using deep learning algorithms. He has successfully developed these applications on devices like Jetson Nano and Arduino Nano BLE for real-time deployment.

🌍 Professional Engagement

Mr. Durgam is an IEEE Student Member and an active participant in IEEE Young Professionals. He has been involved in organizing and coordinating internships, workshops, and training programs related to AI/ML and Deep Learning at NIT Warangal and other institutes. He is passionate about bridging the gap between academia and real-world applications, particularly through Edge Computing and AI deployment.

📚 Top Notes Publications 

Real-Time Dress Code Detection using MobileNetV2 Transfer Learning on NVIDIA Jetson Nano

    • Authors: LK Durgam, RK Jatoth

    • Journal: Proceedings of the 2023 11th International Conference on Information

    • Year: 2023

Real-Time Classification of Vehicle Logos on Arduino Nano BLE using Edge Impulse

    • Authors: D Abhinay, SV Vighnesh, LK Durgam, RK Jatoth

    • Journal: 2023 4th International Conference on Signal Processing and Communication

    • Year: 2023

Age Estimation based on MFCC Speech Features and Machine Learning Algorithms

    • Authors: LK Durgam, RK Jatoth

    • Journal: IEEE International Symposium on Smart Electronic Systems (iSES)

    • Year: 2022

Age Estimation from Speech Using Tuned CNN Model on Edge Devices

    • Authors: LK Durgam, RK Jatoth

    • Journal: Journal of Signal Processing Systems

    • Year: 2024

Age and Gender Estimation from Speech using various Deep Learning and Dimensionality Reduction Techniques

    • Authors: MPJJ Laxmi Kantham Durgam*, Ravi Kumar Jatoth, Daniel Hladek, Stanislav Ondas

    • Journal: Acoustics and Speech Processing at Speech analysis synthesis, Institute of

    • Year: 2024

 

Sherin Zafar | Machine Learning  | Women Researcher Award

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Dr. Sherin Zafar | Machine Learning  | Women Researcher Award

Jamia Hamdard | India

PUBLICATION PROFILE

Scopus

🌟 DR. SHERIN ZAFAR: ACADEMIC AND RESEARCH PIONEER 

👩‍🏫 INTRODUCTION

Dr. Sherin Zafar is an accomplished Assistant Professor in the Department of Computer Science and Engineering at the School of Engineering Sciences and Technology, Jamia Hamdard, New Delhi. Joining the institution in 2015, she has made remarkable contributions to teaching, research, and faculty development. With expertise in network security, machine learning, and health informatics, Dr. Zafar continues to inspire both students and colleagues alike.

🎓 EARLY ACADEMIC PURSUITS

Dr. Zafar’s academic journey began with a Bachelor’s degree in Computer Engineering from Rajiv Gandhi Proudyogiki Vishwavidyalaya (RGPV), Bhopal, followed by a Master’s degree in the same field. Her passion for optimizing network protocols led her to complete her Ph.D. at Manav Rachna International Institute of Research and Studies (MRIIRS) in 2015, where she focused on creating secure protocols for Mobile Ad-Hoc Networks (MANETs) through biometric authentication.

💼 PROFESSIONAL ENDEAVORS

Since joining Jamia Hamdard, Dr. Zafar has been dedicated to academic growth and research excellence. Her professional endeavors span the fields of artificial intelligence (AI), health informatics, and wireless networks. A regular participant in faculty development programs (FDP), workshops, and international conferences, Dr. Zafar stays at the forefront of technological advancements, demonstrating her commitment to personal and professional growth.

🔬 CONTRIBUTIONS AND RESEARCH FOCUS

Dr. Zafar’s research interests are centered around applying AI and computational techniques to real-world problems, especially in health and security. Her work in e-health, including maternal health improvement through AI-based systems, and the development of secure network protocols, highlights her commitment to impactful research. She has also explored the application of machine learning in smart city technologies and water quality monitoring.

🌍 IMPACT AND INFLUENCE

Dr. Zafar has made a significant impact in the academic community through her publications and collaborative research. Her work in healthcare AI, optimization techniques, and network security has been widely recognized and cited by scholars and professionals worldwide. Her contributions have advanced both theoretical and practical aspects of computer science and engineering.

📚 ACADEMIC CITATIONS AND PUBLICATIONS

Dr. Zafar’s academic footprint includes high-quality research papers published in top-tier journals and international conference proceedings. Her studies, including works on AI in healthcare and photo captioning for visually impaired individuals, have been published in journals like Heliyon, Proceedings on Engineering Sciences, and Multimedia Tools and Applications. These works have been indexed in Scopus and Web of Science, contributing to the ongoing academic dialogue.

🏆 HONORS & AWARDS

Throughout her career, Dr. Zafar has received several honors in recognition of her contributions to teaching and research. These accolades showcase her dedication to enhancing the educational landscape and driving innovations in technology and healthcare.

🛠️ LEGACY AND FUTURE CONTRIBUTIONS

As Dr. Zafar continues her work at Jamia Hamdard, her legacy is one of inspiring innovation and fostering academic excellence. With a focus on AI, machine learning, and secure communications, her future research is poised to make lasting contributions to the fields of computer science and healthcare, inspiring future generations of researchers and professionals.

📜 FINAL NOTE

Dr. Sherin Zafar’s career is a testament to her passion for research and teaching. Through her groundbreaking research in AI, network security, and healthcare, Dr. Zafar has earned a well-deserved reputation as a leader in her field. As she continues her academic journey, her influence will undoubtedly shape the future of computer science and engineering, leaving a lasting legacy for years to come.

📚 TOP NOTES PUBLICATIONS 

Internet of things assisted deep learning enabled driver drowsiness monitoring and alert system using CNN-LSTM framework

Authors: S.P. Soman, Sibu Philip G., Senthil Kumar G., S.B. Nuthalapati, Suri Babu S., Zafar Sherin, K.M. Abubeker K.M.
Journal: Engineering Research Express
Year: 2024

Holistic Analysis and Development of a Pregnancy Risk Detection Framework: Unveiling Predictive Insights Beyond Random Forest

Authors: N. Irfan Neha, S. Zafar Sherin, I. Hussain Imran
Journal: SN Computer Science
Year: 2024

Correction to: A transformer based real-time photo captioning framework for visually impaired people with visual attention

Authors: A.K.M. Kunju Abubeker Kiliyanal Muhammed, S. Baskar S., S. Zafar Sherin, S. Rinesh S., A. Shafeena Karim A.
Journal: Multimedia Tools and Applications
Year: 2024

A transformer based real-time photo captioning framework for visually impaired people with visual attention

Authors: K.M. Abubeker K.M., S. Baskar S., S. Zafar Sherin, S. Rinesh S., A. Shafeena Karim A.
Journal: Multimedia Tools and Applications
Year: 2024

 Enhancing Heart Health Prediction with Natural Remedies Through Integration of Hybrid Deep Learning Models

Authors: L.M.S. Akoosh Lamiaa Mohammed Salem, F. Siddiqui Farheen, S. Zafar Sherin, S. Naaz Sameena, M.A. Afshar Alam
Journal: Journal of Natural Remedies
Year: 2024

Synergistic Precision: Integrating Artificial Intelligence and Bioactive Natural Products for Advanced Prediction of Maternal Mental Health During Pregnancy

Authors: N. Irfan Neha, S. Zafar Sherin, I. Hussain Imran
Journal: Journal of Natural Remedies
Year: 2024

Xiaobin Ling | Data Science | Best Researcher Award

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Dr. Xiaobin Ling | Data Science | Best Researcher Award

UMass Medical School | United States

Publication Profile

Orcid

👨‍🔬 Summary

Dr. Xiaobin Ling is a Postdoctoral Researcher at the RNA Therapeutics Institute, UMass Medical School, specializing in lncRNA structure and Cryo-EM. With a Ph.D. in Structural Biology from Fudan University, his work focuses on the mechanisms of RNA structures, molecular biology, and biophysics, with a strong emphasis on cryo-electron microscopy (Cryo-EM).

🧑‍🏫 Current Position

Postdoctoral Researcher
RNA Therapeutics Institute, UMass Medical School (2024–Present)

  • Research on RNA structures, particularly long non-coding RNAs (lncRNAs).
  • Focus on Cryo-EM techniques to elucidate RNA structural dynamics.

🎓 Education

Ph.D. in Structural Biology (2017–2023)
Fudan University, Shanghai, China

  • Research: Mechanisms and regulation of microRNA biogenesis and lncRNA structure.
    Master’s in Chemical Biology (2013–2016)
    Xiamen University, Xiamen, China
  • Research: Drug mechanisms targeting nuclear receptors.
    B.Sc. in Biotechnology (2008–2013)
    Jinggangshan University, Ji’an, China

💼 Professional Experience

Senior Research Assistant (2022–2023)
Cryo-EM Core Facility, Sichuan University, China

  • Managed operations for Titan Krios G3i, Talos Arctica G2, and JEOL1400 microscopes.
  • Applied Cryo-EM techniques for structural research.

Structural Biologist Researcher (2021–2022)
Runjia Pharmaceutical Technology Co., Ltd, Shanghai, China

  • Investigated ADAR inhibitors and their functions.

Research Assistant (2016–2017)
South University of Science and Technology of China, Shenzhen, China

  • Focused on microRNA biogenesis and its regulation.

📚 Academic Publications

Dr. Ling has authored numerous peer-reviewed publications in top journals, including Nature, Nature Structural & Molecular Biology, and Cell Reports. Notable works include:

  1. Cryo-EM structure of a natural RNA nanocage (Nature, 2025)
  2. Circularly permuted group II introns and their mechanisms (Nature Structural & Molecular Biology, 2025)
  3. Human telomeric G-quadruplex DNA binding (BBA – Gene Regulatory Mechanisms, 2023)
  4. ADAR inhibitors and their function (prepint, 2022)

💡 Technical Skills

  • Cryo-EM: Expertise in cryo-electron microscopy for RNA and protein structural analysis.
  • RNA Structure Analysis: Proficient in the study of RNA folding and dynamics.
  • Molecular Biology: Strong background in RNA and DNA manipulation, including G-quadruplexes and microRNA biogenesis.
  • Computational Tools: Skilled in structural bioinformatics and molecular modeling.

👨‍🏫 Teaching Experience

Dr. Ling has contributed to academic training and mentoring at multiple institutions, particularly in structural biology and RNA research.

🔬 Research Interests On Data Science

  • Structural biology of RNA molecules, focusing on lncRNAs and their roles in gene regulation.
  • Application of Cryo-EM to explore the structural dynamics of RNA and protein complexes.
  • Investigating RNA-related therapeutic strategies, including the use of RNA nanocages and RNA-based drug delivery systems.

 📚 Top Notes Publications

Cryo-EM structure of a natural RNA nanocage
    • Authors: Xiaobin Ling*, Dmitrij Golovenko, Jianhua Gan, Jinbiao Ma*, Andrei A. Korostelev*, Wenwen Fang*
    • Journal: Nature
    • Year: 2025 (accepted)
Structures of a natural circularly permuted group II intron reveal mechanisms of branching and back-splicing
    • Authors: Xiaobin Ling*, Yuqi Yao*, Jinbiao Ma*
    • Journal: Nature Structural & Molecular Biology
    • Year: 2025
The mechanism of UP1 binding and unfolding of human telomeric G-quadruplex DNA
    • Authors: Xiaobin Ling#, Yuqi Yao#, Lei Ding, Jinbiao Ma*
    • Journal: Biochimica et Biophysica Acta (BBA) – Gene Regulatory Mechanisms
    • Year: 2023
DHX9 resolves G-quadruplex condensation to prevent DNA double-strand breaks
    • Authors: Juan Chen#, Xiaobin Ling#, Youshan Zhao#, Sheng Li, Manan Li, Hailian Zhao, Xianguang Yang, Chun-kang Chang, Jinbiao Ma*, Yuanchao Xue*
    • Journal: preprint
    • Year: 2022
Phytochrome B inhibits the activity of phytochrome-interacting factor 7 involving phase separation
    • Authors: Yu Xie, Wenbo Liu, Wenjing Liang, Xiaobin Ling, Jinbiao Ma, Chuanwei Yang, Lin Li*
    • Journal: Cell Reports
    • Year: 2023
Modular characterization of SARS-CoV-2 nucleocapsid protein domain functions in nucleocapsid-like assembly
    • Authors: Yan Wang#, Xiaobin Ling#, Jian Zou, Chong Zhang, Bingnan Luo, Yongbo Luo, Xinyu Jia, Guowen Jia, Minghua Zhang, Junchao Hu, Ting Liu, Yuanfeiyi Wang, Kefeng Lu, Dan Li, Jinbiao Ma*, Cong Liu*, Zhaoming Su*
    • Journal: Molecular Biomedicine
    • Year: 2023

 

Shanakar Raman Dhanushkodi | Green electrolysis | Best Researcher Award

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Assoc Prof Dr. Shanakar Raman Dhanushkodi | Green electrolysis | Best Researcher Award

VIT, Vellore | India

Publication Profile

Orcid

ASSOC PROF DR. SHANKAR RAMAN DHANUSHKODI – A LEGACY IN CLEAN ENERGY RESEARCH AND EDUCATION ⚡🌍

INTRODUCTION 🌟

Assoc Prof Dr. Shankar Raman Dhanushkodi is a distinguished academic and researcher currently serving as an Associate Professor at the Vellore Institute of Technology (VIT), Vellore, Tamil Nadu, India. With more than two decades of experience, he has made significant contributions to the field of clean energy, specifically in fuel cell technology, electrolyzers, and the application of machine learning in energy systems. Dr. Dhanushkodi’s journey is marked by a blend of research excellence, academic contributions, and industry collaboration that continues to shape the future of energy solutions.

EARLY ACADEMIC PURSUITS 🎓

Dr. Dhanushkodi’s academic journey began in India, where he completed his Bachelor’s in Chemical Engineering from Alagappa College of Technology, Anna University, Tamil Nadu. He further pursued his Master’s in Process Systems Engineering at the University of Regina, Canada, and his Doctor of Philosophy in Chemical Engineering at the University of Waterloo, Canada. His academic foundation laid the groundwork for his pioneering research in electrochemical systems and fuel cell technologies.

PROFESSIONAL ENDEAVORS 💼

Dr. Dhanushkodi has held numerous prestigious positions across various academic and research institutions. His professional journey spans across countries, including India, Canada, and Germany. As an Associate Professor at VIT, he leads cutting-edge research in hydrogen technologies, focusing on fuel cells and electrolyzers. Additionally, he has served as a research consultant, postdoctoral fellow, and even founded his consulting company, Gandhi Energy Storage Systems and Solutions.

CONTRIBUTIONS AND RESEARCH FOCUS ON Green electrolysis 🔬

Dr. Dhanushkodi’s research expertise covers a wide range of areas such as electro-catalysis, membrane testing, fuel cell components, and the development of AI algorithms for chemical systems. His work in clean energy technologies is critical in advancing the efficiency and sustainability of energy systems. As a leading researcher, he has collaborated on global projects involving fuel cells and electrolyzers, while also contributing significantly to the development of diagnostic tools for electrochemical systems.

IMPACT AND INFLUENCE 🌍

Through his research and teaching, Dr. Dhanushkodi has not only contributed to the academic community but also impacted the global energy industry. His research has influenced the design and performance of fuel cells, electrolyzers, and other energy storage systems, helping to accelerate the transition to clean and sustainable energy sources. His collaborations with international institutions and industries have further reinforced his impact.

ACADEMIC CITATIONS AND PUBLICATIONS 📚

Dr. Dhanushkodi has authored over 15 publications in peer-reviewed journals, contributing to the advancement of knowledge in clean energy technologies and industrial ecology. His work is widely cited in the academic community, underlining the significance and relevance of his research. His focus on developing diagnostic tools for energy systems, particularly for PEM fuel cells and electrolyzers, continues to be a key area of innovation.

HONORS & AWARDS 🏆

Dr. Dhanushkodi’s excellence in research has been recognized through numerous awards and honors, including:

  • Raman Research Award for the paper in desalination and water treatment (2023)
  • Best Paper Award at the International Conference on Art, Education, and Business (2021)
  • Mrs. Chinnamaul Memorial Prize for the Best Technical Paper at CHEMCON (2021)
  • Outstanding Reviewer, Journal of Power Sources (2018)

LEGACY AND FUTURE CONTRIBUTIONS 🔮

Dr. Dhanushkodi’s work is far from over. As he continues to mentor young engineers at VIT and collaborate on international research projects, his legacy will undoubtedly inspire future generations. His ongoing research in fuel cell technology, electrolyzers, and machine learning applications in chemical engineering promises to yield groundbreaking solutions to the world’s energy needs. The future of clean energy is brighter, thanks to his vision and dedication.

FINAL NOTE 📌

Dr. Shankar Raman Dhanushkodi is not just a researcher; he is a mentor and a leader in the field of clean energy. His commitment to advancing energy systems and empowering the next generation of engineers and researchers has left an indelible mark on academia and industry alike. His contributions continue to inspire a future where sustainable energy solutions play a pivotal role in addressing global energy challenges.

 TOP NOTES PUBLICATIONS 📚

Development of Deep Learning Simulation and Density Functional Theory Framework for Electrocatalyst Layers for PEM Electrolyzers
    • Authors: Jaydev Zaveri; Shankar Raman Dhanushkodi; Michael W. Fowler; Brant A. Peppley; Dawid Taler; Tomasz Sobota; Jan Taler
    • Journal: Energies
    • Year: 2025
Machine Learning Framework for the Methyl Chloride Production Process
    • Authors: School of Mechanical Engineering, Vellore Institute of Technology; R. Gollangi; K. NagamalleswaraRao; Dhanushkodi Research group, School of Chemical Engineering, Vellore Institute of Technology; S. R. Dhanushkodi; Dhanushkodi Research group, School of Chemical Engineering, Vellore Institute of Technology; N. Mahinpey; Department of Chemical and Petroleum Engineering, University of Calgary
    • Journal: Journal of Environmental Informatics Letters
    • Year: 2024
Development of Semi-Empirical and Machine Learning Models for Photoelectrochemical Cells
    • Authors: Niranjan Sunderraj; Shankar Raman Dhanushkodi; Ramesh Kumar Chidambaram; Bohdan Węglowski; Dorota Skrzyniowska; Mathias Schmid; Michael William Fowler
    • Journal: Energies
    • Year: 2024
Development of Semi Empirical and Machine Learning Models for Photo-Electrochemical Cells
    • Authors: Niranjan Sunderraj; S.R. Dhanushkodi; Ramesh Kumar Chidambaram; B. Węglowski; Dorota Skrzyniowska; Mathias Schmid; Michael William Fowler
    • Journal: Preprint
    • Year: 2024
Design and Manufacturing Challenges in PEMFC Flow Fields—A Review
    • Authors: Prithvi Raj Pedapati; Shankar Raman Dhanushkodi; Ramesh Kumar Chidambaram; Dawid Taler; Tomasz Sobota; Jan Taler
    • Journal: Energies
    • Year: 2024

 

Olivier Donfouet | intelligence artificielle | Best Scholar Award

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Dr. Olivier Donfouet | intelligence artificielle | Best Scholar Award

Université de Dschang/Cameroun | Cameroon

Publication Profile

Scopus

🌍 Dr. Olivier Donfouet: Bridging Mathematics, AI, and Agriculture 🚀

INTRODUCTION 📚

Dr. Olivier Donfouet is a distinguished mathematical economist, researcher, and entrepreneur dedicated to leveraging Artificial Intelligence (AI) to transform agricultural practices in Africa. With a strong background in mathematical economics, project management, and technology-driven solutions, he has contributed significantly to both academia and industry. His expertise spans economic modeling, agricultural innovation, and AI-driven research, making him a key figure in sustainable agricultural development.

EARLY ACADEMIC PURSUITS 🎓

Dr. Donfouet’s academic journey began at Université de Dschang, where he earned a Ph.D. in Mathematical Economics. His foundational studies included a Master’s and Bachelor’s degree in the same field, equipping him with advanced skills in economic analytics, statistical modeling, and AI applications in economics. His academic excellence was complemented by hands-on experiences with data analysis software such as Stata, SPSS, and LaTeX.

PROFESSIONAL ENDEAVORS 💼

Dr. Donfouet has amassed diverse professional experiences, including:
✔ Academic Internship at the International Center for Artificial Intelligence in Morocco
✔ Drone Technology Training for Agricultural Innovation
✔ Lecturing & Mentorship at Université de Dschang
✔ Entrepreneurship in Sustainable Product Development
✔ Active Participation in International Conferences on AI & Gender Equality

Beyond academia, he is recognized as an entrepreneur and business leader, having successfully developed eco-friendly mosquito-repellent candles—a project that earned him national recognition and innovation awards.

CONTRIBUTIONS AND RESEARCH FOCUS  ON INTELLIGENCE ARTIFICIELLE🔬

Dr. Donfouet’s research focuses on AI’s impact on agricultural productivity, gender equality, and sustainability. His notable contributions include:
🔹 Investigating AI-driven economic models for sustainable agriculture
🔹 Exploring ICT’s role in reducing undernourishment in Africa
🔹 Analyzing AI’s contribution to empowering women in agriculture
🔹 Examining AI’s effect on total factor productivity in agriculture

His innovative approach to precision agriculture and economic modeling makes his work highly relevant to policymakers, researchers, and industry leaders.

IMPACT AND INFLUENCE 🌍

Dr. Donfouet’s work extends beyond research—his influence is seen in:
✅ Educating the next generation of economists and AI researchers
✅ Advancing AI applications in African agriculture
✅ Innovating sustainable solutions for economic development
✅ Shaping policies through data-driven insights

His leadership in youth mentorship, religious associations, and AI-driven economic policies further cements his influence in both academic and community spheres.

ACADEMIC CITATIONS AND PUBLICATIONS 📝

Dr. Donfouet has contributed to leading peer-reviewed journals, including:
1️⃣ “Is Artificial Intelligence Helping to Empower Women in Agriculture in Africa?” (GeoJournal, 2024)
2️⃣ “Impact of AI on Total Productivity of Agricultural Factors in Africa” (Environment, Development and Sustainability, 2024)
3️⃣ “How Important is ICT for Reducing Undernourishment in Africa?” (Telematics and Informatics Reports, 2023)

These publications highlight the intersection of AI, economic growth, and sustainable agriculture.

HONORS & AWARDS 🏅

🏆 4th Place National Innovation Award (Ministry of Small and Medium Enterprises, Yaoundé)
🏆 3rd Place CATI2 Innovation Award (Université de Dschang)
🏆 Recognized AI Researcher at International Conferences
🏆 Leadership & Entrepreneurship Excellence in Agriculture

FINAL NOTE ✨

Dr. Olivier Donfouet is a trailblazer in mathematical economics and AI-driven agricultural solutions. His work continues to push the boundaries of economic theory, AI applications, and sustainable innovation, making him a key player in Africa’s digital agricultural revolution.

LEGACY AND FUTURE CONTRIBUTIONS 🔮

🔸 Future research on AI-driven solutions for climate-resilient agriculture
🔸 Advancing economic policies integrating AI for food security
🔸 Bridging the gap between technological innovations and agricultural practices
🔸 Mentorship programs for emerging scholars in AI & Economics

TOP NOTES PUBLICATIONS 📚

Title: Is artificial intelligence helping to empower women in agriculture in Africa?

Authors: Olivier, D., & Ibrahim, N.
Journal: GeoJournal
Year: 2024

Title: Impact of artificial intelligence on the total productivity of agricultural factors in Africa.

Authors: Donfouet, O., & Ngouhouo, I.
Journal: Environment, Development and Sustainability
Year: 2024

Title: How important is ICT for reducing undernourishment in Africa?

Authors: Domguia, E. N., Hymette, L. F. N., Nzomo, J. T., Ngassam, S. B., & Donfouet, O.
Journal: Telematics and Informatics Reports
Year: 2023

Kwang-Sig Lee | Artificial Intelligence | Excellence in Research

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Dr. Kwang-Sig Lee | Artificial Intelligence | Excellence in Research

Korea University Anam Hospital AI Center | South Korea

Publication Profile

Scopus

Google Scholar

INTRODUCTION 🧑‍🎓

Dr. Kwang-Sig Lee is a distinguished academician, research leader, and innovator specializing in the integration of medical and social informatics. Currently serving as Vice Center Chief at the AI Center of Korea University Anam Hospital, Dr. Lee’s groundbreaking research combines artificial intelligence with diverse datasets, such as genetic, image, numeric, and text data. His expertise in AI-driven systems has led to revolutionary work in healthcare, focusing on predictive AI models and multimodal machine learning. His work has earned significant recognition, influencing both academic circles and real-world medical applications.

EARLY ACADEMIC PURSUITS 🎓

Dr. Lee’s academic journey began at Kon Kuk University in Seoul, South Korea, where he earned a Bachelor’s degree in Economics and Physics (1994-1999), with a GPA of 3.52/4.00. He furthered his studies at Iowa State University (1999-2004), earning dual Master’s degrees in Economics and Sociology, graduating with a GPA of 3.69/4.00. Dr. Lee’s pursuit of advanced studies led him to Johns Hopkins University, where he obtained his Ph.D./MSE in Sociology and Applied Mathematics with a focus on health systems, securing a GPA of 3.63/4.00.

PROFESSIONAL ENDEAVORS 💼

Dr. Lee’s professional career spans across multiple prestigious institutions. At present, he holds the role of Vice Center Chief at Korea University’s AI Center in the Medical School. His previous roles include serving as a Research Associate Professor at the same institution, and Senior Research Fellow positions at various research agencies, including Acorn, Enliple, Agilesoda, and National Health Insurance Service. Dr. Lee has also worked as an Assistant Professor at Yonsei University and Sungkyunkwan University, contributing his expertise in preventive medicine and biostatistics.

CONTRIBUTIONS AND RESEARCH FOCUS ON ARTIFICIAL INTELLIGENCE 🧬

Dr. Lee’s contributions to the field of medical and social informatics are vast and impactful. His research primarily focuses on the application of artificial intelligence (AI) in healthcare, especially through the use of machine learning models, such as Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Transformer models. His work explores the integration of genetic, image, numeric, and text data, thereby providing a more holistic approach to solving complex health-related challenges. Dr. Lee is known for his expertise in “Wide & Deep Learning,” a method that synthesizes multiple AI approaches to offer more powerful insights and predictive models.

IMPACT AND INFLUENCE 🌍

Dr. Lee’s innovative research has earned significant recognition both in academic and industrial circles. His work has been published in over 45 SCIE-indexed journals with a combined impact factor of 168. His Field-Weighted Citation Impact is 1.76, surpassing the average citation impact of KAIST in 2021. His expertise is frequently sought in both teaching and consultation, with Dr. Lee being an influential member of various academic committees. His ability to mentor graduate students and lead multidisciplinary research projects has significantly shaped the landscape of AI and healthcare.

ACADEMIC CITATIONS AND PUBLICATIONS 📚

Dr. Lee’s extensive publication record spans notable journals such as Cancers, European Radiology, International Journal of Surgery, and Journal of Medical Systems. His contributions have greatly impacted the scientific community, with a robust body of work related to medical AI, health informatics, and predictive modeling. In addition to his research articles, Dr. Lee has served as a guest editor for journals like Frontiers in Bioscience and Applied Sciences, as well as a reviewer for top-tier publications such as Nature Communications and Journal of Big Data.

HONORS & AWARDS 🏆

Throughout his academic career, Dr. Lee has been the recipient of numerous accolades, including full financial support during his tenure at Johns Hopkins University and Iowa State University. Additionally, he has been awarded for his academic excellence during his undergraduate studies at Kon-Kuk University. Dr. Lee’s consistent recognition for research excellence is evident from his impactful publications and active participation in the academic community, including his involvement in major research projects funded by government agencies.

FINAL NOTE ✨

Dr. Kwang-Sig Lee’s career is a testament to his dedication to advancing AI in medicine and social sciences. His expertise in combining machine learning with healthcare applications has paved the way for new innovations in predictive medicine, offering vital contributions to global healthcare systems. As he continues to lead research projects at the AI Center at Korea University, Dr. Lee’s legacy will be defined by his commitment to improving public health through cutting-edge technology and interdisciplinary research.

LEGACY AND FUTURE CONTRIBUTIONS 🔮

Dr. Lee’s future endeavors are poised to have a lasting impact on the fields of AI and healthcare. As the Vice Center Chief at one of the top medical schools, his work is expected to advance predictive healthcare models, fostering the development of more personalized and efficient healthcare solutions. With his expertise in “Wide & Deep Learning,” Dr. Lee is likely to continue influencing both the academic community and industry, shaping the future of AI-driven healthcare innovations.

TOP NOTES PUBLICATIONS 📚

Article: Graph Machine Learning With Systematic Hyper-Parameter Selection on Hidden Networks and Mental Health Conditions in the Middle-Aged and Old
  • Authors: K. Lee, Kwang-sig; B. Ham, Byung-joo
    Journal: Psychiatry Investigation
    Year: 2024
Article: A Machine Learning-Based Decision Support System for the Prognostication of Neurological Outcomes in Successfully Resuscitated Out-of-Hospital Cardiac Arrest Patients
  • Authors: S. Lee, Sijin; K. Lee, Kwang-sig; S. Park, Sang-hyun; S. Lee, Sung-woo; S. Kim, Sujin
    Journal: Journal of Clinical Medicine
    Year: 2024
Article: Clinical and Dental Predictors of Preterm Birth Using Machine Learning Methods: The MOHEPI Study
  • Authors: J. Park, Jung-soo; K. Lee, Kwang-sig; J. Heo, Ju-sun; K. Ahn, Ki-hoon
    Journal: Scientific Reports
    Year: 2024
Article: Explainable Artificial Intelligence on Safe Balance and Its Major Determinants in Stroke Patients
  • Authors: S. Lee, Sekwang; E. Lee, Eunyoung; K. Lee, Kwang-sig; S.B. Pyun, Sung Bom
    Journal: Scientific Reports
    Year: 2024

Amin Hekmatmanesh | Algorithm Development | Best Researcher Award

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Dr. Amin Hekmatmanesh l Algorithm Development  | Best Researcher Award

LUT University, Finland

Author Profile

Google Scholar

🔎 Summary

Dr. Amin Hekmatmanesh is a skilled biomedical engineer and data scientist, specializing in wearable sensors, AI, and machine learning applications for health technologies. He has extensive experience in biosignal processing (EEG, ECG, PPG, EMG, GSR, IMU), rehabilitation robotics, and medical device development. With a Ph.D. in Mechanical Engineering (Biomedical Engineering), he has made significant contributions to the field by developing real-time systems for rehabilitation and health monitoring. His research focuses on using AI to advance rehabilitation robotics and human-robot interactions, publishing over 30 peer-reviewed articles. He is also an active reviewer and editorial board member for several high-ranking journals.

🎓 Education

Dr. Hekmatmanesh holds a Ph.D. in Mechanical Engineering (Biomedical Engineering) from LUT University in Finland, where he achieved a GPA of 4.33. His dissertation focused on artificial intelligence and machine learning for EEG signal processing in rehabilitation robotics. He also completed his M.Sc. in Biomedical Engineering at Shahed University in Iran, with a perfect GPA of 4.0, and a B.Sc. in Electrical Engineering from Islamic Azad University, graduating with a GPA of 4.1.

💼 Professional Experience

Dr. Hekmatmanesh has a diverse professional background, having worked as a Lead Project Manager at Mevea Company, where he managed health monitoring system projects, incorporating wearable sensor technology. At Flowgait Company, he contributed to mathematical solutions for horse motion analysis. As a Junior Researcher and Project Manager at LUT University, he focused on wearable sensor systems and health monitoring. Additionally, he worked as a Research Assistant at Tehran University, working on diagnostic algorithms and therapeutic systems in health technologies.

📚 Academic Citations

Dr. Hekmatmanesh has published over 30 peer-reviewed papers, including book chapters and review articles, and his work has contributed significantly to the biomedical engineering and AI fields. His research has received wide recognition, and he is regularly invited to participate in scientific conferences and review for high-impact journals, showcasing his influence and contributions to advancing health technologies.

🔧 Technical Skills

Dr. Hekmatmanesh is highly proficient in biosignal processing, including EEG, ECG, PPG, EMG, GSR, and IMU signals. He is skilled in machine learning and AI, specifically for biosignal classification and real-time system development. His technical expertise extends to embedded electronics, sensor design, and circuit board assembly. He is proficient in Python and Matlab for data analysis and has experience using version control tools like GitHub to manage research projects.

🎓 Teaching Experience

Dr. Hekmatmanesh has been actively involved in teaching and mentoring within the biomedical engineering field. He has supervised PhD students and contributed to academic programs by delivering lectures and guiding research projects in health technologies, machine learning, and rehabilitation robotics.

🔬 Research Interests On Algorithm Development

Dr. Hekmatmanesh’s research interests include the development of wearable sensor systems for health monitoring, AI and machine learning techniques for biosignal classification, and the design and control of rehabilitation robotics. He is also focused on human-robot interactions and improving prosthetics control through innovative AI applications in healthcare.

📖 Top Noted Publications

Nanocaged platforms: modification, drug delivery and nanotoxicity. Opening synthetic cages to release the tiger
    • Authors: PS Zangabad, M Karimi, F Mehdizadeh, H Malekzad, A Ghasemi, …
    • Journal: Nanoscale
    • Year: 2017
Review of the state-of-the-art of brain-controlled vehicles
    • Authors: A Hekmatmanesh, PHJ Nardelli, H Handroos
    • Journal: IEEE Access
    • Year: 2021
Neurosciences and wireless networks: The potential of brain-type communications and their applications
    • Authors: RC Moioli, PHJ Nardelli, MT Barros, W Saad, A Hekmatmanesh, …
    • Journal: IEEE Communications Surveys & Tutorials
    • Year: 2021
A combination of CSP-based method with soft margin SVM classifier and generalized RBF kernel for imagery-based brain computer interface applications
    • Authors: A Hekmatmanesh, H Wu, F Jamaloo, M Li, H Handroos
    • Journal: Multimedia Tools and Applications
    • Year: 2020
EEG control of a bionic hand with imagination based on chaotic approximation of largest Lyapunov exponent: A single trial BCI application study
    • Authors: A Hekmatmanesh, RM Asl, H Wu, H Handroos
    • Journal: IEEE Access
    • Year: 2019

Jing An | Artificial Intelligence | Best Researcher Award

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Dr. Jing An | Artificial Intelligence | Best Researcher Award

Yancheng Institute of Technology, China

👨‍🎓Professional Profile

Scopus Profile

👨‍🏫 Summary

Dr. Jing An is a distinguished professor and master tutor at Yancheng Institute of Technology, China. He specializes in intelligent manufacturing engineering, industrial big data fault diagnosis, and residual life prediction. With numerous patents and software copyrights, Dr. An has published over 20 SCI/EI indexed papers and contributed to key academic texts. His pioneering research in artificial intelligence-based fault diagnosis has earned him prestigious awards, including first-place recognition in the China Commerce Federation Science and Technology Award .

🎓 Education

Dr. An holds a Ph.D. in Computer Science from Hohai University (2021) and a Master’s degree in Computer Science from Harbin University of Science and Technology (2006). His academic foundation has strongly influenced his research in AI and fault diagnosis.

💼 Professional Experience

Having joined Yancheng Institute of Technology in 2006, Dr. An is also the Vice President of Science and Technology for Jiangsu Province’s “Double Innovation Plan.” He has led numerous provincial-level projects, and his expertise has extended to more than 10 industry partnerships 🚀.

📚 Academic Citations

Dr. An has authored over 20 peer-reviewed papers in prestigious journals such as IEEE Access and Mathematical Problems in Engineering. His impactful research on AI-based fault diagnosis methods is frequently cited within the academic community .

🔧 Technical Skills

Dr. An is skilled in AI-based fault diagnosis, deep learning, machine learning, and industrial big data analytics. He has expertise in Convolutional Neural Networks (CNNs) and intelligent manufacturing systems, focusing on improving machinery reliability and efficiency .

🧑‍🏫 Teaching Experience

Dr. An has been recognized as an outstanding teacher twice at Yancheng Institute of Technology. He teaches courses in intelligent manufacturing engineering and industrial big data fault diagnosis, preparing students to advance in the field of AI and data science .

🔍 Research Interests

Dr. An’s research is focused on developing intelligent systems for fault diagnosis in rotating machinery, predictive maintenance, and the application of deep learning techniques in industrial big data. His work aims to enhance manufacturing processes and equipment reliability .

📖Top Noted Publications

Hybrid Mechanism and Data-Driven Approach for Predicting Fatigue Life of MEMS Devices by Physics-Informed Neural Networks

Authors: Cheng, J., Lu, J., Liu, B., An, J., Shen, A.

Journal: Fatigue and Fracture of Engineering Materials and Structures

Year: 2024

Bearing Intelligent Fault Diagnosis Based on Convolutional Neural Networks

Authors: An, J., An, P.

Journal: International Journal of Circuits, Systems and Signal Processing

Year: 2022

Deep Clustering Bearing Fault Diagnosis Method Based on Local Manifold Learning of an Autoencoded Embedding

Authors: An, J., Ai, P., Liu, C., Xu, S., Liu, D.

Journal: IEEE Access

Year: 2021

Deep Domain Adaptation Model for Bearing Fault Diagnosis with Riemann Metric Correlation Alignment

Authors: An, J., Ai, P.

Journal: Mathematical Problems in Engineering

Year: 2020

Deep Domain Adaptation Model for Bearing Fault Diagnosis with Domain Alignment and Discriminative Feature Learning

Authors: An, J., Ai, P., Liu, D.

Journal: Shock and Vibration

Year: 2020

Shubing Dai | Algorithm Development | Best Researcher Award

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Prof. Shubing Dai | Algorithm Development | Best Researcher Award

Prof. Shubing Dai at Northwest A&F University, China

Professional Profile👨‍🎓

👨‍🏫 Summary

Prof. Shubing Dai is an Associate Professor at Northwest A&F University, specializing in Hydraulic Engineering. With a background in Hydraulics and River Dynamics, he has published over 20 research papers and actively participated in over 20 research projects. His work primarily focuses on urban flood management, hydraulic structures, and water flow dynamics. He is also an active member of key professional organizations, including the China Society for Hydroelectric Engineering and the International Association for Hydro-Environment Engineering and Research (IAHR).

🎓 Education

Prof. Dai began his academic career at Northwest A&F University, where he earned his Bachelor’s (2008–2012) and Master’s (2012–2015) degrees in Hydraulic and Hydroelectric Engineering. He then pursued a Ph.D. in Hydraulics and River Dynamics at Dalian University of Technology (2016–2021). Additionally, he worked as a visiting scholar at the University of La Coruña in Spain (2024).

💼 Professional Experience

Prof. Dai has extensive professional experience, both in academia and industry. He currently serves as an Associate Professor at Northwest A&F University and the Department Secretary of the Hydraulic Engineering Department. He also previously worked as an Assistant Engineer at the Changjiang Survey, Planning, and Design Institute (2015–2016), contributing to several major hydropower and hydraulic engineering projects.

📚 Academic Contributions

Prof. Dai is an active contributor to the academic community, serving as a reviewer for several leading journals such as Journal of Hydrology and Physics of Fluids. He also serves as an editorial board member for an international journal. His research focuses on water resources, hydraulic structures, and flow dynamics, with over 20 published papers and several high-impact research projects.

🔧 Technical Skills

Prof. Dai has developed a range of technical skills, including:

  • Hydraulic Engineering: Focus on energy dissipation and optimization of flood discharge systems.
  • Urban Flooding & Drainage: Expertise in urban drainage system design, stormwater management, and flood mitigation.
  • Flow Dynamics: Proficient in Computational Fluid Dynamics (CFD) and non-steady flow simulations for hydraulic applications.
  • Hydropower Engineering: In-depth research on dam-break flood modeling, hydraulic structures, and their interactions with water flow.

👩‍🏫 Teaching Experience

As a dedicated educator, Prof. Dai mentors master’s students and teaches courses on fluid dynamics, hydraulic modeling, and water resource management. He is also responsible for the administration of the Water Resources and Hydroelectric Engineering department at Northwest A&F University, playing a key role in curriculum development and academic planning.

🔬 Research Interests

Prof. Dai’s research interests are focused on:

  • Hydraulic Engineering: Research on energy dissipation in hydraulic structures and optimization of flood discharge processes.
  • Flood Disaster Management: Urban flood management, drainage systems, and dam-break flood evolution.
  • Non-steady Flow & Hydrodynamics: Investigating the dynamics of free-surface flows, wave behavior, and non-constant flow conditions in hydraulic systems.

🔍 Research Projects

Prof. Dai leads and participates in several important research projects, such as:

  • City Flood and Drainage Systems Simulation (2022–2025)
  • Optimization of Urban Drainage Under Extreme Rainfall Conditions (2023–2025)
  • Dam-Break Flood Evolution and Structural Interaction Studies (2024–2026)
    He is also involved in national and regional projects on hydraulic structure optimization, flood forecasting, and water resource management.

 

📖Top Noted Publications

Numerical study of roll wave development for non-uniform initial conditions using steep slope shallow water equations

Authors: Dai, S., Liu, X., Zhang, K., Liu, H., Jin, S.
Journal: Physics of Fluids
Year: 2024

Discharge coefficients formulae of grate inlets of complicated conditions for urban floods simulation and urban drainage systems design

Authors: Dai, S., Hou, J., Jin, S., Hou, J., Liu, G.
Journal: Journal of Hydrology
Year: 2023

Land Degradation Caused by Construction Activity: Investigation, Cause and Control Measures

Authors: Dai, S., Ma, Y., Zhang, K.
Journal: International Journal of Environmental Research and Public Health
Year: 2022

Numerical investigations of unsteady critical flow conditions over an obstacle using three models

Authors: Dai, S., Jin, S.
Journal: Physics of Fluids
Year: 2022

Interception efficiency of grate inlets for sustainable urban drainage systems design under different road slopes and approaching discharges

Authors: Dai, S., Jin, S., Qian, C., Ma, Y., Liang, C.
Journal: Urban Water Journal
Year: 2021

Ying-Chih Sun | Business Intelligence and Analytics | Best Researcher Award

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Assist Prof Dr. Ying-Chih Sun | Business Intelligence and Analytics | Best Researcher Award

Assist Prof Dr. Ying-Chih Sun at East Central University, United States

👨‍🎓Professional Profiles

📚 Summary

Dr. Ying-Chih Sun is an Assistant Professor of Business Administration – Information Technology Management at East Central University. With a Ph.D. in Information Systems Engineering and Management and a strong academic background in economics, data analytics, and IT management, his research focuses on AI applications in healthcare, telehealth, and supply chain management. He is passionate about integrating business analytics with IT solutions to improve operational efficiencies across industries.

🎓 Education

Dr. Sun holds a Ph.D. in Information Systems Engineering and Management (ISEM) from Harrisburg University of Science and Technology (2023), where he graduated with a perfect 4.0 GPA. He also earned M.S. degrees in Economics from the University at Buffalo (2018) and Texas A&M University (2010), and an M.B.A. in Applied Economics (Summa Cum Laude) from National Taiwan Ocean University (2005). He completed his undergraduate studies in International Trade at Tamkang University (2003).

💼 Professional Experience

Dr. Sun is currently serving as an Assistant Professor at East Central University, teaching courses in Business Economics, Data Analytics, and Cloud Management. Before this, he was an Assistant Professor in Residence at Bradley University (2023-2024), where he contributed to research and teaching in business analytics. He also worked as a Research Assistant at Harrisburg University (2019-2023), conducting research on telehealth and healthcare delivery. Previously, he served as an IT Research Data Analyst at SUNY Buffalo and held roles at the Institute of Economics, Academia Sinica and Tri-Service General Hospital in Taiwan.

📝 Academic Publications & Conferences

Dr. Sun has presented at major conferences like the DSI Conference 2024, AMCIS 2024, and MWAIS 2024. His research papers focus on a range of topics, including telehealth efficiency, AI in healthcare, digital reputation in business schools, and supply chain optimization. His recent work on “Evaluating Telehealth Efficiency” and “Enhancing Judicial Decision-Making with AI” exemplifies his interdisciplinary approach to solving complex business and healthcare challenges.

💻 Technical Skills

Dr. Sun possesses advanced proficiency in data analytics tools like SQL, STATA, and Excel for statistical modeling and large data analysis. He is also familiar with Python and has hands-on experience in cloud management and telehealth technology. His technical skills enable him to approach research from both an analytical and technological perspective, focusing on improving efficiency in healthcare and business operations.

👨‍🏫 Teaching Experience

Dr. Sun has extensive teaching experience, having taught courses at East Central University (2024-present) in Business Economics, Data Analytics, and Cloud Management. He previously taught at Bradley University (2023-2024), covering Business Analytics and Business Analytics Software. Additionally, during his time at SUNY at Buffalo (2015-2018), he served as a Grader and Teaching Assistant for various econometrics courses and contributed to graduate-level teaching in Computational Econometrics.

🔬 Research Interests

Dr. Sun’s primary research interests lie at the intersection of AI, telehealth, and business analytics. He explores how data-driven decision-making can enhance healthcare delivery and operational efficiency, with a focus on telemedicine applications and the use of machine learning for healthcare and business management. His work on optimizing AI investments and supply chain management has important implications for improving cost-effectiveness and decision-making in businesses and healthcare systems.

 

📖 Top Noted Publications

A stochastic production frontier model for evaluating the performance efficiency of artificial intelligence investment worldwide

Authors: Sun, Y.-C., Cosgun, O., Sharman, R., Mulgund, P., Delen, D.
Journal: Decision Analytics Journal
Year: 2024

The impact of policy and technology infrastructure on telehealth utilization

Authors: Sun, Y.-C., Cosgun, O., Sharman, R.
Journal: Health Services Management Research
Year: 2024

The Effect of Varying User Risk Levels on Perceived Social Presence in Mental Health Chatbots

Authors: Thimmanayakanapalya, S.S., Singh, R., Mulgund, P., Sun, Y.-C., Sharman, R.
Conference: 29th Annual Americas Conference on Information Systems (AMCIS 2023)
Year: 2023