Dr. Annarosa Scalcione | Machine Learning | Research Excellence Award

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Dr. Annarosa Scalcione | Machine Learning | Research Excellence Award 

Dr. Annarosa Scalcione | Machine Learning | Polytechnic University of Turin | Italy

Dr. Annarosa Scalcione is a female biomedical engineer with a strong interdisciplinary background in biomedical instrumentation, sensor-based health monitoring, medical imaging, and digital healthcare solutions, combining engineering rigor with clinical relevance. She completed advanced academic training in biomedical engineering at Politecnico di Torino, with specialization in biomedical instrumentation and sensor systems, supported by foundational education in biomedical engineering from the same institution, where her academic work focused on sustainable biomaterials and applied medical technologies. Her professional experience includes roles as a Junior Application Consultant contributing to the digitalization of hospital clinical and administrative processes, operating room specialist engagement within medical institutions, and academic teaching collaboration supporting undergraduate engineering education. Dr. Annarosa Scalcione has led and contributed to multiple applied and experimental research projects, including the design of a web-based neonatal monitoring platform integrating sensor-derived growth data, dynamic visualization, personalized alerts aligned with international health standards, and telemedicine functionalities. Her research portfolio also includes experimental biomechanics studies using mobile sensors to evaluate neuromuscular performance, automated classification of spinal lesions from medical imaging using machine learning and radiomics, and advanced image segmentation methodologies applied to neurological datasets.

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Prof. Dr. Cornelia Aurora Gyorod | Machine Learning | Research Excellence Award

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Prof. Dr. Cornelia Aurora Gyorod | Machine Learning | Research Excellence Award 

Prof. Dr. Cornelia Aurora Gyorod | Machine Learning | University of Oradea | Romania

Prof. Dr. Cornelia Aurora Gyorod is a senior academic and internationally recognized researcher in Computer Science and Information Technology, specializing in database systems, data mining, expert systems, and large-scale data-driven computing architectures that underpin modern intelligent and sensing-based systems. She holds a Ph.D. in Computer Science from the University of Oradea and currently serves as a Professor in the Faculty of Electrical Engineering and Information Technology, Department of Computers and Information Technology, where she has demonstrated long-standing excellence in teaching, research, and academic leadership. Her educational background is complemented by advanced professional certifications in project management, project evaluation, and enterprise database technologies, reflecting her strong methodological and organizational competence. Her professional experience spans progressive academic roles including junior assistant, assistant professor, lecturer, associate professor, and full professor, during which she has been responsible for delivering core and advanced courses such as Databases, Expert Systems, Computer Programming, Advanced Database Systems, and Data Warehousing, alongside supervising undergraduate, master’s, and doctoral research. Her strengths for this award include a strong international research profile, with 70+ peer-reviewed publications, primarily indexed in Scopus and IEEE-affiliated venues, accumulating 800+ citations and an established Scopus Author ID and ORCID record.

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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. Osheyor Gidiagba | Machine Learning | Best Researcher Award

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Mr. Osheyor Gidiagba | Machine Learning | Best Researcher Award 

Mr. Osheyor Gidiagba | Machine Learning | University of Johannesburg | South Africa

Mr. Osheyor Joachim Gidiagba is an accomplished researcher and engineer whose expertise lies in Mechanical and Industrial Engineering, currently pursuing his Ph.D. at the University of Johannesburg, South Africa, where his research focuses on developing a hybrid model combining Machine Learning and Multi-Criteria Decision-Making (MCDM) to enhance sustainable supplier selection and performance optimization in industrial systems. His academic foundation includes a Master’s in Applied Science Mechanics (Cum Laude) and a Bachelor’s degree in Mechanical Engineering (First Class Honors), underscoring his consistent academic excellence and technical depth. Professionally, Mr. Gidiagba has worked as an Asset Management Engineer at the Ministry of Power and Domestic Water Development, Awka, Nigeria, where he successfully supervised and implemented multiple infrastructure projects, including the installation of electrical transformers and overhead water tanks across several communities. His work emphasized system reliability, supplier evaluation, and maintenance optimization, demonstrating his ability to translate research into impactful real-world engineering applications. His research interests encompass machine learning applications in decision-making, sustainable engineering systems, reliability-centered maintenance, industrial data analytics, and asset integrity management. His technical skills include data modeling, predictive maintenance, statistical analysis, multi-criteria decision-making, and system reliability evaluation, supported by proficiency in computational tools and industrial analytics. Mr. Gidiagba has published 7 Scopus-indexed research papers, accumulating 30 citations with an h-index of 3, reflecting his growing scholarly influence. His key contributions, such as applying fuzzy logic, TOPSIS, and hybrid decision models in sustainable industrial practices, highlight his innovative approach to bridging the gap between artificial intelligence and engineering sustainability. He has also engaged in international research collaborations that focus on improving decision-support systems and operational efficiency in industrial and mining sectors.

Professional Profiles: Scopus

Featured Publications 

  1. Gidiagba, O. J. (2025). Multi-Criteria Decision Support for Sustainable Supplier Evaluation in Mining SMEs: A Fuzzy Logic and TOPSIS Approach. Logistics.

Assist. Prof. Dr. Ali Alfayly | Machine Learning | Best Researcher Award

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Assist. Prof. Dr. Ali Alfayly | Machine Learning | Best Researcher Award 

Assist. Prof. Dr. Ali Alfayly | Machine Learning | Public Authority of Applied Education and Training | Kuwait

Assist. Prof. Dr. Ali Hussain Alfayly, SMIEEE, is a highly accomplished Kuwaiti academic and researcher serving as an Assistant Professor in the Department of Computer Science at the College of Basic Education, Public Authority for Applied Education and Training (PAAET), Kuwait, where he has established himself as a prominent contributor to the fields of computer science, artificial intelligence, cybersecurity, robotics, and educational technologies. He earned his Ph.D. in Computer Science from the University of Plymouth in the United Kingdom, building on his earlier M.Sc. in Advanced Computer Science from the University of Manchester, an M.Sc. in Computer and Network Technology, and a B.Sc. in Computer and Network Technology, both from Northumbria University. His professional career includes serving as Lecturer and Lab Demonstrator at the University of Plymouth in the United Kingdom and as a Network Engineer at Kuwait International Bank, experiences that equipped him with both academic and industry perspectives. Dr. Ali Hussain Alfayly’s research interests encompass Explainable Artificial Intelligence, Machine Learning, UAV systems, cybersecurity and network management, robotics, intelligent systems, and educational technology, reflecting a multidisciplinary approach aimed at solving real-world challenges.

Professional Profile: ORCID | Scopus

Selected Publications

  1. Detection of Fault Events in Software Tools Integrated with Human–Computer Interface Using Machine Learning, 2025 – Citations: 5

  2. Citizens’ Satisfaction Factors in E-Government Services: An Empirical Study from Kuwait, 2024 – Citations: 8

  3. Extended Technology Acceptance Model for Multimedia-Based Learning in Higher Education, 2022 – Citations: 12

  4. Challenges of Applying Semantic Web Approaches on E-Government Web Services: Survey, 2021 – Citations: 15

Assoc. Prof. Dr. Waleed Mahmoud Elsayed | Machine learning Awards | Best Researcher Award

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Assoc. Prof. Dr. Waleed Mahmoud Elsayed | Machine learning Awards | Best Researcher Award 

Assoc. Prof. Dr. Waleed Mahmoud Elsayed, Beni-suef university, Saudi Arabia

Dr. Waleed Mahmoud Ead is an accomplished Assistant Professor in the Faculty of Computing and Information at Al-Baha University, Saudi Arabia, with over 15 years of experience in digital business transformation, data science, and applied research. He holds a Ph.D. in Computers and Informatics from Menoufia University, Egypt, where he focused on privacy-preserving techniques in social networks. Throughout his career, Dr. Ead has developed expertise in business intelligence, data mining, machine learning, cloud computing, and big data analytics, and he is SAS-certified in multiple disciplines, including machine learning and visual analytics. His research interests span social network analysis, distributed databases, precision medicine, and cybersecurity. He has served in various academic roles across prominent Egyptian institutions and has co-supervised doctoral and master’s research in genetics, AI, and privacy in healthcare. A dedicated peer reviewer for renowned journals such as Springer Nature and Inderscience, Dr. Ead is also an active contributor to academic conferences and international workshops. Beyond academia, he is a technology enabler, STEM judge, and entrepreneur, with projects focused on sustainable agriculture and digital innovation.

Professional Profile:

GOOGLE SCHOLAR

ORCID

SCOPUS

✅ Summary of Suitability for Best Researcher Award: Dr. Waleed Mahmoud Ead

Dr. Waleed Mahmoud Ead is highly suitable for the Best Researcher Award, given his exceptional combination of research depth, academic leadership, interdisciplinary engagement, and societal impact. His qualifications are supported by the following key strengths

🎓 Education

  • 🥇 2004: B.Sc. (Honor) in Information and Technology Systems – Zagazig University, Egypt

  • 📚 2012: M.Sc. in Computers and Informatics – Menoufia University, Egypt
      📘 Thesis: “Developing an Intelligent Technique in Web Mining”

  • 🎓 2018: Ph.D. in Computers and Informatics – Menoufia University, Egypt
      📗 Thesis: “Privacy Preserving in Social Networks”

👨‍🏫 Academic Work Experience

  • 🇸🇦 2024–Present: Assistant Professor, Faculty of Computing and Information – Al-Baha University, Saudi Arabia

  • 🇪🇬 2022–2023: Assistant Professor, CSIT – Egypt-Japan University of Science and Technology

  • 🇪🇬 2018–2022: Assistant Professor, Faculty of Computers & AI – Beni-Suef University

  • 🇪🇬 2015–2018: Lecturer Associate, Faculty of Information Technology – MUST University

  • 🇪🇬 2014: Lecturer Associate, Faculty of Computers & Information – Beni-Suef University

  • 🇪🇬 2012: Lecturer Associate, CSC – October 6 University

  • 🇪🇬 2006–2012: Teaching Assistant, CSC – October 6 University

🏆 Achievements & Honors

  • 🧠 SAS Certified: Machine Learning, Visual Analytics, Business Planning

  • 💡 Developed systems for international conferences

  • 🌍 Peer Reviewer for top journals & publishers (Inderscience, Springer, EAI, etc.)

  • 🧬 Co-supervisor for Ph.D. and Master’s students in AI, bioinformatics, and precision medicine

  • 🥇 Honor degree in B.Sc.

  • 👩‍⚖ STEM Judge: INTEL ISEF & Graduation Projects

  • 💼 Speaker and participant in events by DAAD, UNESCO, Microsoft, SAS, Oracle

  • 🌱 Founder of IGreen (Intelligent Adaptive Environmental Farm)

  • 🚀 Participated in entrepreneurship programs (Start Egypt, Flat6Labs)

  • 🧭 Bridging analytics and IT knowledge for social development

Publication Top Notes:

An Optimized Hierarchal Cluster Formation Approach for Management of Smart Cities

ODCS: On-Demand Hierarchical Consistent Synchronization Approach for the IoT

A General Cyber Hygiene Approach for Financial Analytical Environment

Feedforward Deep Learning Optimizer-based RNA-Seq Women’s cancers Detection with a hybrid Classification Models for Biomarker Discovery

Semantic Sentiment Classification for COVID-19 Tweets Using Universal Sentence Encoder

Automated Prediction of Employee Attrition Using Ensemble Model Based on Machine Learning Algorithms

Prof. Dr. Cedric Sueur | Artificial intelligence | Best Researcher Award

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Prof. Dr. Cedric Sueur | Artificial intelligence | Best Researcher Award 

Prof. Dr. Cedric Sueur, Université de Strasbourg, France

Cédric Sueur is a French ethologist and primatologist renowned for his contributions to the study of animal behavior and social ecology. He is a Full Professor at the University of Strasbourg and a Fellow of the Institute for Advanced Study, as well as a member of the French Academic Institute. He holds a Ph.D. in Ethology from Louis Pasteur University, Strasbourg, and the Free University of Brussels, along with an HDR qualification to supervise doctoral theses. Throughout his career, he has held prestigious academic positions, including Associate Professor at the University of Strasbourg, Visiting Professor at Kyoto University, Sun Yat-sen University, and Lille Catholic University. His research has been widely recognized, earning him numerous accolades such as the Changjiang Scholar Program award, the Adolphe Wetrems Award from the Royal Academies for Science and the Arts of Belgium, and recognition among the world’s top 2% of scientists by Stanford University. With a strong academic and research background, Sueur continues to contribute significantly to the field of ethology and primatology.

Professional Profile:

GOOGLE SCHOLAR

Summary of Suitability for Best Researcher Award – Cédric Sueur

Cédric Sueur is a highly accomplished researcher in Ethology and Primatology, making him a strong contender for the Best Researcher Award. His outstanding academic background, extensive research contributions, prestigious honors, and leadership in the scientific community establish him as an influential figure in his field.

🎓 Education

  • 2014: HDR, Habilitation to Supervise Doctoral Theses

  • 2008: PhD in Ethology – Primatology, Louis Pasteur University, Strasbourg & Free University of Brussels

  • 2005: Master’s Degree, University Louis Pasteur, Strasbourg (With Honours)

  • 2003: Bachelor’s in Organisms’ Biology, University 14USTL, Lille (With Honours)

💼 Work Experience

  • Since 2024: Full Professor, University of Strasbourg

  • Since 2021: Invited Professor, Lille Catholic University

  • 2011-2024: Associate Professor, University of Strasbourg (Outstanding since 2022)

  • 2022 (Jan-Mar): Invited Professor, Kyoto University Institute for Advanced Study

  • 2016 (Jul-Aug): Invited Professor, Sun-Yat Sen University, China (Changjiang Scholar Program award)

  • 2008-2012: Research Associate, Unit of Social Ecology, Free University of Brussels

  • 2010-2011: Research Fellow, Primate Research Institute, Kyoto University

  • 2009-2010: Research Associate, Ecology & Evolutionary Biology, Princeton University

  • 2007-2008: Lecturer in Ethology, Strasbourg University

🏆 Awards & Honors

  • 2025: Selected for the Lumexplore Prize by the French Society of Explorers 🏅

  • 2025: Selected for the François Sommer Prize 🏆

  • 2024-2029: Member of the “Institut Universitaire de France” 🎖️

  • 2023: Best Communication Prize at Aramos Congress 🏅

  • 2023: Named Best Scientist by Research.com 🌍

  • 2022: Listed among the World’s Top 2% of Scientists by Stanford University 📊

  • 2022: Named Best Scientist by Research.com 🏅

  • 2019: Adolphe Wetrems Award from the Royal Academies for Science and the Arts of Belgium 🏆

  • 2019-2024: Fellow of the Institut Universitaire de France 🎖️

  • 2017: Primates Social Impact Award 🏅

  • 2016: Changjiang Scholar Program Award (Visiting Professor at Sun-Yat Sen University, China) 🇨🇳

  • 2014: Excellence Award from the French Minister of Higher Education and Research 🎓

  • 2013: Young Scientist Award from the French Society for the Study of Animal Behaviour (SFECA) 🏅

  • 2012: 3 papers among the Top 5 Cited Papers in International Journal of Primatology 📜

  • 2012: Fellow of the University of Strasbourg Institute for Advanced Study (USIAS) 🎓

  • 2010: JSPS Alumni (Japan Society for the Promotion of Science) 🇯🇵

  • 2009: Fulbright Alumni 🇺🇸

  • 2009: Prize of the Society of Biology of Strasbourg for Best Thesis 📜

  • 2009: “Le Monde de la Recherche Universitaire” Prize for Best Thesis 🎓

  • 2006-2010: Member of the European Doctoral College of Strasbourg 🌍

Publication Top Notes:

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GITED:168

Ms. Minkyung Sung | Image Segmentation Awards | Best Researcher Award

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Ms. Minkyung Sung | Image Segmentation Awards | Best Researcher Award 

Ms. Minkyung Sung, Chung-Ang University, South Korea

Min-Kyung Sung is a dedicated Master’s student at the Department of Artificial Intelligence at Chung-Ang University, where she studies under the guidance of Professor Jaesung Lee. With a Bachelor of Science degree in Software from Anyang University, she has developed a strong foundation in artificial intelligence and image segmentation, particularly focusing on on-device AI applications. Min-Kyung has made significant contributions to the field, publishing her work in prominent international conferences such as the IEEE International Conference on Consumer Electronics and presenting research on open vocabulary segmentation based on vision-language pre-trained models. Her recent projects include developing a deep learning CT shortening algorithm for structural adhesive inspection at Hyundai and an AI pediatric behavioral analysis system for children with autism spectrum disorder (ASD). Recognized for her excellence, she received the Best Paper Award at the Spring Academic Conference of the Korean Society for Emotion and Sensibility in 2023. Proficient in Python, LaTeX, and various machine learning tools such as PyTorch and TensorFlow, Min-Kyung is poised to make significant advancements in the artificial intelligence domain.

Professional Profile:

GOOGLE SCHOLAR

Suitability for the Research for Best Researcher Award: Min-Kyung Sung

Min-Kyung Sung is an exemplary candidate for the Research for Best Researcher Award, showcasing significant achievements in artificial intelligence and image segmentation through a blend of rigorous academic training and impactful research contributions.

🎓 Education

  • Master’s Student in Department of AI, Chung-Ang University (2023 – Present)
    Academic Adviser: Prof. Jaesung Lee
  • B.S. in Software Engineering at Anyang University (2019 – 2023)

💼 Work Experience

  • Researcher at Chung-Ang University, focusing on Artificial Intelligence and Image Segmentation.
  • Project Contributor for various AI-related projects including:
    • Development of a Deep Learning CT Shortening Algorithm for Hyundai (2024 – Present)
    • AI Pediatric Behavioral Analysis System for ASD (March 2023 – July 2023)
    • Virtual-based Diet Assistant Application (March 2022 – November 2022)
    • Participation in the AI Bookathon Competition (November 2021)

🏆 Achievements

  • Best Paper Award at the Spring Academic Conference (Korean Society for Emotion and Sensibility, 2023) for outstanding research contributions.

🏅 Awards and Honors

  • 2023: Best Paper Award at the Spring Academic Conference, Korean Society for Emotion and Sensibility.

🛠️ Skills

  • Programming Languages: Python, LaTeX, Git, Android platforms
  • Machine Learning Tools: PyTorch, TensorFlow, scikit-learn

Publication Top Notes:

 

Assoc Prof Dr. Wenlong Hang | Artificial Intelligence Award | Best Researcher Award

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Assoc Prof Dr. Wenlong Hang | Artificial Intelligence Award | Best Researcher Award

Assoc Prof Dr. Wenlong Hang, Nanjing Tech University, China

Wenlong Hang holds a Doctor of Engineering degree from Jiangnan University, where he graduated in June 2017, specializing in Light Industry Information Technology. During his doctoral studies, he visited both Hong Kong Polytechnic University and the Shenzhen Institutes of Advanced Technology. Since September 2017, Dr. Hang has been a faculty member at the School of Computer Science and Technology at Nanjing Tech University. His research interests primarily focus on artificial intelligence and machine learning, with a particular emphasis on medical image analysis and EEG signal processing. He has published more than 30 papers in reputable journals and conferences, contributing significantly to semi-supervised learning, federated learning, and EEG classification techniques. His representative works include research on medical image segmentation, reliability-aware semi-supervised frameworks, and domain-generalized EEG classification.

Professional Profile:

Summary of Suitability for Best Researcher Award :

Wenlong Hang is highly suitable for the Best Researcher Award based on his extensive research and contributions in the fields of artificial intelligence, machine learning, and medical image processing. His academic background, with a Doctor of Engineering degree from Jiangnan University, and professional experiences at institutions like Hong Kong Polytechnic University and Shenzhen Institutes of Advanced Technology, demonstrates his deep involvement in advanced technological research.

Education:

  • Doctor of Engineering (Graduated in June 2017)
    • Major: Light Industry Information Technology
    • Institution: Jiangnan University
    • Doctoral Visits: Hong Kong Polytechnic University, Shenzhen Institutes of Advanced Technology

Work Experience:

  • Since September 2017: Faculty Member
    • Position: Professor at the School of Computer Science and Technology
    • Institution: Nanjing Tech University

Research Areas:

  • Artificial Intelligence (AI)
  • Machine Learning (ML)
  • Medical Image Segmentation
  • EEG Classification

Publication top Notes:

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