Ms. Raghi K R | Federated Learning | Research Excellence Award

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Ms. Raghi K R | Federated Learning | Research Excellence Award 

Ms. Raghi K R | Federated Learning | Sathyabama Institute of Science and Technology | India

Mrs. Raghi K.R. is a dedicated computer science educator and researcher with strong experience in both teaching and applied research. She holds a B.E. in Computer Science and Engineering (Anna University), an M.E. in Computer Science and Engineering (PSN Engineering College / Anna University), and has submitted her Ph.D. synopsis in Computer Science and Engineering at College of Engineering, Guindy, Anna University. Her professional journey includes roles as Assistant Professor and Teaching Fellow across several institutions: PSN Engineering College (CSE), College of Engineering Guindy, and currently at St. Joseph’s College of Engineering, Chennai giving her over a decade of teaching experience, spanning undergraduate and postgraduate courses. Her research interests lie in Artificial Intelligence, Deep Learning, Machine Learning, Cloud Security, and Web Mining. She possesses robust technical skills including programming in Python, Java, C, C++, web technologies (HTML), and experience with simulation platforms such as NS2 and MATLAB, as well as familiarity with open-source operating systems. Through her career she has mentored and guided multiple innovative and funded projects — for example leading a seed-research project titled “StepSmart: Design and Development of an Affordable IoT and Deep Learning Based Footwear for Diabetic Health Monitoring,” and supervising award-winning student projects such as “Trash Triage: Trailblazing Waste Management with Real-Time Street Waste Monitoring” and “Identification of Fake Medicinal Raw Materials Using Machine Learning.” These recognitions reflect her commitment to practical, socially relevant research. Her academic repertoire includes teaching diverse subjects like Artificial Intelligence, Mobile Computing, Information Security, Web Programming, Soft Computing, Software Project Management, Cyber Security, Web Technology, and more. She has also supervised substantial academic work: a Ph.D. thesis on “Privacy-Preserving Deep NN Classification over Signature Cryptosystem in Cloud Environments,” a secure payment-scheme design in multihop networks, and semantic similarity computation for natural language. As a scholar and mentor, Mrs. Raghi combines strong theoretical foundations with hands-on applied research, striving to develop secure, intelligent, and socially impactful computing solutions. Her involvement in both education and research along with project funding, awards, and diverse technical competencies — positions her as a proactive and forward-looking professional in the fields of AI, cybersecurity, and data-driven intelligent systems, committed to nurturing student talent and contributing to technological advancement.

Professional Profiles: ORCID | Google Scholar 

Selected Publications

  1. Thomas, R. K. L., Sanjay, G. J., Pandeeswaran, C., & Raghi, K. R. (2024). Advanced CCTV Surveillance Anomaly Detection, Alert Generation and Crowd Management using Deep Learning Algorithm.

  2. Vethavikashini, A. M., Jamal, S. M., & Raghi, K. R. (2024). Huntington’s Disease Prediction Using Xception CNN.

  3. Devi, S. R., Geetha Priya, S., Sathi, G., Naveen Kumar, S., Dinesh, M., & Raghi, K. R. (2024). Design and Development of a Touch Free Smart Home Controlling System Based on Virtual Reality (VR) Technology.

  4. Raghi, K. R., Sudha, K., Sreeram, A. M., Steve Joshua, S. (2024). Software Development Automation Using Generative AI.

  5. Raghi, K. R. (2023). Privacy-Preserving Deep NN Classification over Signature Cryptosystem in Cloud Environments.

  6. Anitha, T., Sai Srihitha, G. R. P. Lakshmi Aiswarya, & Raghi, K. R. (2025). Predictive Modeling of Social Media Data Using Machine Learning Techniques.

  7. (As mentor) StepSmart: Design and Development of an Affordable IoT and Deep Learning Based Footwear for Diabetic Health Monitoring.

Mr. Koagne Silas | Neural Networks | Pioneer Researcher Award

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Mr. Koagne Silas | Neural Networks | Pioneer Researcher Award 

Mr. Koagne Silas, University of Dschang, Cameroon

KOAGNE LONGPA TAMO Silas is a Cameroonian researcher and Ph.D. student in Physics at Dschang State University, specializing in medical physics with a strong focus on automation and applied computer science. His academic background spans both physics and electrical engineering, with degrees from the University of Dschang and the University of Bamenda, where he developed expertise in embedded systems, analog artificial neural networks, and electronics. Silas has extensive experience in microcontroller programming, analog and digital circuit simulation, and tools such as MATLAB, Arduino, Proteus, and Cadence Virtuoso. In addition to his research, he has served as an electronics teacher at various technical colleges and as a junior lecturer in computer science. His hands-on experience includes internships in electronics maintenance and electrical network installation. A bilingual communicator in English and French, Silas is known for his leadership, creativity, and commitment to advancing applied technologies in medical physics.

Professional Profile:

SCOPUS

🏅 Summary of Suitability Pioneer Researcher Award 

KOAGNE LONGPA TAMO Silas is an emerging research talent in the field of medical physics and electronics, demonstrating a rare combination of early innovation, technical depth, and applied problem-solving across interdisciplinary domains. As a Ph.D. candidate with an M.Sc. specialization in analog artificial neural networks for medical applications, Silas is pioneering research at the intersection of electronics, embedded systems, and health technologies, aligning closely with the spirit of the Pioneer Researcher Award.

🎓 Education Background

  • Ph.D. in Physics (Medical Physics) – Dschang State University, Cameroon (📅 Dec 2022 – Present)

    • 🧠 Research Focus: Analog Artificial Neural Networks

    • 👨‍🏫 Supervisor: Prof. Geh Wilson Ejuh

  • M.Sc. in Physics, Electronics Speciality – Dschang State University, Cameroon (📅 July 2022)

    • 📘 Thesis: Specification and implementation of multilayer perceptron analog artificial neural networks

    • 👨‍🏫 Supervisor: Dr. Djimeli Tsajio Alain B.

  • B.Sc. in Physics – Dschang State University, Cameroon (📅 Aug 2021)

  • DIPET 2 in Electronics – University of Bamenda (📅 July 2020)

    • 🛰 Dissertation: Design and implementation of a digital breath alcohol detection system with SMS alert and vehicle tracking

  • DIPET 1 in Electronics – University of Bamenda (📅 Aug 2018)

    • 🚪 Project: RFID-based electronic attendance system with automatic door unit

  • GCE A/L – Government Bilingual High School, Mbouda (📅 July 2015)

  • GCE O/L – Government Bilingual High School, Mbouda (📅 June 2013)

  • FSLC – Ecole Primaire Bilingue de la Promotion, Mbouda (📅 June 2008)

💼 Work Experience

  • Electronics Teacher – Government Technical College Ngombo-ku, Cameroon (📅 Jan 2021 – Present)

  • Junior Lecturer in Computer Science – Higher Technical Teacher Training College Bambili (📅 2019–2020)

  • Electronics Teacher – Government Technical High School Bambui (📅 2017–2018)

  • Internship – Electronics & Maintenance

    • 📍 HYTECHS, Yaoundé (📅 2019)

    • 🔧 Worked on printer maintenance & installation

  • Internship – Electrical Network Installation

    • 📍 MEECH CAM Sarl, Yaoundé (📅 2016)

    • ⚡ Focus on underground cable installation and high voltage network

🏆 Achievements & Awards

  • ✅ Successfully designed and implemented:

    • 🤖 An analog artificial neural network (M.Sc. Thesis)

    • 🚘 A breath alcohol detection system with GPS and SMS alerts

    • 🛂 An RFID-based attendance system with automated doors

  • 📚 Published and presented academic work in medical physics and embedded systems

  • 👨‍🏫 Contributed to higher education through teaching and mentoring roles across several institutions

  • 🎓 Admitted to Ph.D. program based on excellent academic performance

  • 💻 Advanced skills in MATLAB, Arduino, MikroC, Cadence Virtuoso, PSPICE & Proteus

  • 🗣️ Bilingual in English and French – great asset for teaching and collaboration

Publication Top Notes:

Breast cancer detection and classification: A study on the specification and implementation of multilayer perceptron analog artificial neural networks

Dr. Peng Zhi | Deep Learning | Best Researcher Award

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Dr. Peng Zhi | Deep Learning | Best Researcher Award 

Dr. Peng Zhi, Lanzhou University, China

Peng Zhi is a Ph.D. candidate in Computer Science at Lanzhou University, China, specializing in computer vision, deep learning, and autonomous driving. He earned his Bachelor’s and Master’s degrees in Computer Science and Technology from Lanzhou University in 2017 and 2020, respectively. His research focuses on LiDAR-camera fusion, 3D object detection, and AI applications in intelligent transportation systems. He has published several high-impact papers in renowned journals and conferences, contributing to advancements in autonomous vehicle perception and artificial intelligence. Additionally, he has co-authored the book Theories and Practices of Self-Driving Vehicles, further solidifying his expertise in the field.

Professional Profile:

ORCID

Summary of Suitability for the Best Researcher Award

Peng Zhi is a strong candidate for the Best Researcher Award, given his innovative contributions to computer vision, deep learning, and autonomous driving. As a Ph.D. candidate at Lanzhou University, he has been actively involved in research that enhances LiDAR-based 3D object detection, cross-domain generalization, and deep learning applications in autonomous systems.

🎓 Education

  • Ph.D. in Computer Application Technology (2021 – Present)
    Lanzhou University, Lanzhou, China
  • Master’s in Computer System Architecture (2017 – 2020)
    Lanzhou University, Lanzhou, China
  • Bachelor’s in Computer Science and Technology (2013 – 2017)
    Lanzhou University, Lanzhou, China

💼 Work Experience

  • Ph.D. Candidate & Researcher (2021 – Present)
    Lanzhou University, Lanzhou, China

    • Conducts advanced research in computer vision, deep learning, and autonomous driving
    • Publishes in top-tier journals and conferences
    • Develops LiDAR and camera fusion models for 3D object detection

🏆 Achievements & Contributions

  • Published Multiple Research Papers 📄 in top journals and conferences, including Tsinghua Science and Technology, Electronic Research Archive, and IEEE ITSC
  • Author of a Book on Self-Driving Vehicles 📘 Theories and Practices of Self-Driving Vehicles (Elsevier, 2022)
  • Developed DefDeN Model 🤖 A deformable denoising-based LiDAR and camera feature fusion model for 3D object detection
  • Research on Autonomous Driving 🚗 Focused on boundary distribution estimation and cross-domain generalization for LiDAR-based 3D object detection

🏅 Awards & Honors

  • Best Paper Award 🏆 at an International Conference on Intelligent Transportation Systems (ITSC)
  • Outstanding Researcher Award 🎖️ at Lanzhou University for contributions to AI and autonomous driving
  • National Scholarship 🏅 for academic excellence in computer science and AI research

Publication Top Notes:

Cross-Domain Generalization for LiDAR-Based 3D Object Detection in Infrastructure and Vehicle Environments

Ms. Congying Sun | Object Detection Awards | Best Researcher Award

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Ms. Congying Sun | Object Detection Awards | Best Researcher Award 

Ms. Congying Sun, Xi’an University of Technology, China

Congying Sun, a native of Xianyang City, Shaanxi Province, is an emerging researcher specializing in control science, engineering, and multi-modal remote sensing technologies. She earned her Bachelor’s degree in Printing Engineering from Xi’an University of Technology in 2022 and is currently pursuing a Master’s degree in Control Science and Engineering at the same institution, expected to graduate in 2025. Her professional experience includes a tenure at the Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, where she played a pivotal role in developing an infrared-visible aircraft image dataset and deploying state-of-the-art infrared small target detection models. Congying has demonstrated her ability to merge academic excellence with practical application through her contributions to national and engineering projects, including research on multi-source collaborative intelligent perception technology for aircraft and non-cooperative multi-target classification and cognition technology.

Professional Profile:

ORCID

Suitability of Congying Sun for the Best Researcher Award

Congying Sun demonstrates exceptional qualifications and accomplishments, making her an outstanding candidate for the Research for Best Researcher Award. Below is a summary of her key achievements and strengths

🎓 Education

  • Master’s Degree in Control Science and Engineering (August 2022 – July 2025)
    🏫 Xi’an University of Technology
  • Bachelor’s Degree in Printing Engineering (September 2018 – July 2022)
    🏫 Xi’an University of Technology

🧑‍💻 Professional Experience

Xi’an Institute of Optics and Precision Mechanics, Chinese Academy of Sciences (July 2023 – August 2024)

  • 📸 Independently created an infrared-visible aircraft image dataset, including camera selection, data collection, and image annotation.
  • 📝 Authored project proposals, research papers, and patents with great precision.
  • 🤖 Developed and deployed infrared small target detection models and multi-modal remote sensing image fusion detection models.

🚀 Research Projects

  • Multi-source Collaborative Intelligent Perception Technology for Aircraft (August 2023 – June 2024) ✈️
  • Non-cooperative Multi-target Classification and Cognition Technology (October 2023 – March 2024) 🎯

🏅 Achievements

  • Granted Invention Patents:
    • 📜 Infrared Small Target Detection Method (CN118762159A)
    • 📜 Multi-modal Feature Fusion Target Detection Model and Method (CN118865046A)

💡 Research Interests

🔍 Machine Learning | 🌍 Multi-modal Remote Sensing | 🎯 Target Detection

Congying Sun’s innovative approach, technical expertise, and impactful contributions to cutting-edge research make her a rising star in the field of control science and engineering. 🌟

Publication Top Notes:

Location-Guided Dense Nested Attention Network for Infrared Small Target Detection

MMYFnet: Multi-Modality YOLO Fusion Network for Object Detection in Remote Sensing Images

Prof. Hsin-Yuan Chen | AI Awards | Outstanding Scientist Award

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Prof. Hsin-Yuan Chen | AI Awards | Outstanding Scientist Award

Prof. Hsin-Yuan Chen, Zhejiang University, China

H.Y. J. Chen is an accomplished researcher with expertise spanning multiple fields including bioengineering, materials science, and guidance system technologies. Holding a Web of Science ResearcherID (JSL-7102-2023) , Chen has an impressive H-index of 58, with over 11,000 citations accumulated from works published between January 2000 and March 2024. Some of Chen’s notable contributions include studies on biochar anodes for lithium-ion batteries, computational fluid dynamics (CFD) analysis of cormorant takeoff mechanisms, and innovations in van der Waals semiconductor photodetectors. Chen’s interdisciplinary work also extends into preprints and collaboration on machine learning applications in conformal field theories.

Professional Profile:

Scopus

Suitability Summary for Research for Outstanding Scientist Award

Researcher: H.Y. J. Chen

Summary:

H.Y. J. Chen stands out as a highly suitable candidate for the Research for Outstanding Scientist Award due to his exceptional contributions and interdisciplinary expertise across multiple scientific domains. Chen’s research spans bioengineering, materials science, and guidance system technologies, showcasing a profound impact on these fields.

🎓Education:

H.Y. J. Chen is an accomplished researcher with expertise in bioengineering, materials science, and guidance system technologies. Chen earned both his Master’s and Bachelor’s degrees, as well as a Ph.D., from National Cheng Kung University, Taiwan.

Publication Top Notes:

  • Protective Effects of an Oligo-Fucoidan-Based Formula Against Osteoarthritis Development via iNOS and COX-2 Suppression Following Monosodium Iodoacetate Injection
    • Citations: 0
  • Hinokitiol Inhibits Breast Cancer Cells In Vitro Stemness-Progression and Self-Renewal with Apoptosis and Autophagy Modulation via the CD44/Nanog/SOX2/Oct4 Pathway
    • Citations: 1
  • Alleviating 3-MCPD-Induced Male Reproductive Toxicity: Mechanistic Insights and Resveratrol Intervention
    • Citations: 1
  • Hinokitiol as a Modulator of TLR4 Signaling and Apoptotic Pathways in Atopic Dermatitis
    • Citations: 1
  • Integrating Explainable Artificial Intelligence and Blockchain to Smart Agriculture: Research Prospects for Decision Making and Improved Security
    • Citations: 7

 

 

Prof Dr. Gulnihal Ozbay | Machine Learning Award | Best Researcher Award

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Prof Dr. Gulnihal Ozbay | Machine Learning Award | Best Researcher Award 

Prof Dr. Gulnihal Ozbay, Delaware State University, United States

Dr. Gulnihal Ozbay is a distinguished Professor and Extension Specialist in Natural Resources at Delaware State University, where she also serves as Director of the Environmental Health & Seafood Safety Lab and the Integrative Ph.D. Program in Agriculture, Food, and Environmental Sciences. Her career is marked by significant achievements in diverse fields, including aquaculture, fisheries, water chemistry, and aquatic ecology. Dr. Ozbay is highly regarded for her expertise in program development, grant writing, and student mentorship. She has built and managed several research labs, including the Mariculture Lab and GIS Lab, and has a strong record of collaboration with various institutions and agencies. Dr. Ozbay holds multiple degrees in relevant fields, including a Ph.D. in Fisheries & Allied Aquacultures from Auburn University and an M.Sc. in Food Science & Biotechnology from Delaware State University. Her leadership extends beyond teaching and research to include roles such as Vice President of DSU AAUP and Chair of the DSU Faculty Research Committee. Her commitment to environmental science is evident in her active participation in programs addressing sustainability, climate change, and seafood safety.

Professional Profile:

Suitability for the Best Researcher Award

Dr. Gulnihal Ozbay’s extensive career demonstrates exceptional proficiency in various fields related to natural resources, including aquaculture, fisheries, water chemistry, aquatic ecology, climate science, seafood chemistry, and microbiology. His role as a Professor and Extension Specialist, combined with his leadership positions, showcases his strong research background and administrative capabilities.

🎓 Professional Preparation

  • Ph.D., Fisheries & Allied Aquacultures (Water Quality)
    Auburn University, 2002
  • Ph.D. Credits, Food Science & Technology
    Dalhousie University, 1999
  • M.Sc., Bio-Resource Engineering (Marine Bio-Resources)
    University of Maine, 1996
  • M.Sc., Food Science & Biotechnology
    Delaware State University, 2016
  • B.Sc., Fisheries & Aquaculture Engineering
    University of Ondokuzmayis, 1991

🏆 Professional Appointments

  • Professor & Extension Specialist, Natural Resources
    Delaware State University, 2012 – Present
  • Adjunct Faculty, Food Science & Biotechnology Graduate Program
    DSU, 2008 – Present
  • Adjunct Faculty, Applied Chemistry Graduate Program
    DSU, 2018 – Present
  • Director, Environmental Health & Seafood Safety Lab
    DSU, 2009 – Present
  • Director, Integrative Ph.D. Program in Agriculture, Food and Environmental Sciences (IAFES)
    DSU, 2021 – Present
  • Vice President, DSU AAUP
    2021 – Present

📚 Teaching Experience

  • Environmental Toxicology
    DSU, 2020-Present
  • Climatology
    DSU, 2012-Present
  • Introduction to Environmental Science
    DSU, 2011-Present
  • Special Problems (Sustainability & Climate Change)
    DSU, 2004-Present
  • Graduate Seminar
    DSU, 2010

Publication top Notes:

CITED: 78
CITED: 74
CITED: 68
CITED:56
CITED: 53
CITED: 51

Dr. Xianchao Zhu | Reinforcement Learning | Best Researcher Award

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Dr. Xianchao Zhu | Reinforcement Learning | Best Researcher Award 

Dr. Xianchao Zhu, School of Artificial Intelligence and Big Data/Henan University of Technology, China

Dr. Xianchao Zhu is a Lecturer at the School of Artificial Intelligence and Big Data at Henan University of Technology, a position he has held since 2022. He completed his Ph.D. in Physics at the Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, where his research focused on “Abstraction-based Reinforcement Learning Algorithms and its Quantization.” Prior to his doctoral studies, Dr. Zhu earned a Master of Science in Computer Architecture from the School of Computer, Central China Normal University, with a thesis on “Research on Dimensionality Reduction Visualization Method of High-Dimensional Biological Data Based on Gradient Descent and Adaptive Learning.” His academic interests span artificial intelligence, reinforcement learning, and high-dimensional data analysis.

Professional Profile:

 

ORCID

Education

  • Ph.D. in Physics
    Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China
    2018 – 2022
    Thesis Title: Abstraction-based Reinforcement Learning Algorithms and its Quantization.
  • M.Sc. in Computer Architecture
    School of Computer, Central China Normal University
    2015 – 2018
    Thesis Title: Research on Dimensionality Reduction Visualization Method of High-Dimensional Biological Data Based on Gradient Descent and Adaptive Learning.

Employment History

  • Lecturer
    School of Artificial Intelligence and Big Data, Henan University of Technology
    2022 – Present

Publication top Notes:

Salience Interest Option: Temporal abstraction with salience interest functions

Generalization Enhancement of Visual Reinforcement Learning through Internal States

Efficient relation extraction via quantum reinforcement learning

MDMD options discovery for accelerating exploration in sparse-reward domains