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. Suresha R | Computer Vision Awards | Excellence in Research Award

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Mr. Suresha R | Computer Vision Awards | Excellence in Research Award 

Mr. Suresha R | Computer Vision Awards | Amrita Vishwa Vidyapeetham | India

Mr. Suresha R. is a results-driven educator and technologist with over six years of combined experience in teaching computer science and academic leadership. He holds an M.Sc. in Computer Science and has qualified in UGC-NET and K-SET, while currently pursuing a Ph.D. Mr. Suresha R. has demonstrated expertise in curriculum design and research, particularly focusing on AI in autonomous solutions and computer vision applications. In his professional career, Mr. Suresha R. has served as an Assistant Professor at Amrita Vishwa Vidyapeetham, School of Computing, Mysuru Campus, and at SBRR Mahajana First Grade College, Mysuru, where he delivered advanced courses in Computer Vision, Digital Image Processing, Pattern Recognition, Computational Intelligence, Computer Graphics, Machine Learning, Exploratory Data Analysis, R Programming, Information Retrieval, Data Mining, Numerical Analysis, and Operations Research, consistently achieving high student satisfaction. His research interests encompass small traffic sign detection and recognition in challenging scenarios using computer vision and LiDAR-based techniques with ROS2 framework, deep learning-based vehicle detection and distance estimation for autonomous systems, motion blur image restoration, wild animal recognition through vocal analysis, and SVM-based medical image classification. Mr. Suresha . possesses strong research skills in Python, MATLAB, ROS2, machine learning, deep learning, image processing, and data analysis. He has successfully guided Bachelor’s and Master’s students in research projects, fostering innovation and academic growth. His academic contributions are recognized through multiple publications in prestigious journals and conferences, including IEEE Access, Procedia Computer Science, ICCCNT, CCEM, ICECAA, and INDIACom. Mr. Suresha . has a proven record of collaborating in interdisciplinary teams, effectively communicating complex technical concepts, and mentoring students to achieve excellence in research and practical applications. His dedication to lifelong learning and active engagement in both teaching and research demonstrates his commitment to advancing knowledge in computer science and autonomous systems. Throughout his career, Suresha  has received awards and recognitions for research excellence, contributing to the development of sustainable and intelligent solutions in the field of computer vision and AI. Overall, Mr. Suresha exemplifies a passionate and innovative professional, bridging theoretical foundations with applied research, and continues to make significant contributions to academia and technology

Professional Profiles: ORCID

Selected Publications 

  1. Suresha, R., Manohar, N., Ajay Kumar, G., & Singh, R. (2024). Recent advancement in small traffic sign detection: Approaches and dataset.

  2. Suresha, R., Manohar, N., & Jipeng, T. (2024). Two-stage traffic sign classification system.

  3. Sudharshan Duth, P., Manohar, N., Suresha, R., Priyanka, M., & Jipeng, T. (2024). Wild animal recognition: A vocal analysis.

  4. Suresha, R., Jayanth, R., & Shriharikoushik, M. A. (2023). Computer vision approach for motion blur image restoration system.

  5. Srinivasa, C., Suresha, R., Manohar, N., Dharun, G. K., Sheela, T., & Jipeng, T. (2023). Deep learning-based techniques for precise vehicle detection and distance estimation in autonomous systems.

  6. Suresha, R., Devika, K. M., & Prabhu, A. (2022). Support vector machine classifier based lung cancer recognition: A fusion approach.

Dr. Seyedeh Tina Sefati | Reinforcement Learning | Best Researcher Award

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Dr. Seyedeh Tina Sefati | Reinforcement Learning | Best Researcher Award

Dr. Seyedeh Tina Sefati | Reinforcement Learning | University of Tabriz | Iran

Dr. Seyedeh Tina Sefati is a highly skilled and innovative Ph.D. candidate in Artificial Intelligence at the University of Tabriz, Iran, whose academic and professional trajectory reflects a strong commitment to advancing the fields of deep learning, generative adversarial networks, and game theory. Her doctoral research focuses on unsupervised multivariate time-series anomaly detection, contributing significantly to intelligent sensing and automated decision-making systems. Dr. Seyedeh Tina Sefati holds a Master’s degree in Artificial Intelligence from the University of Tabriz, where she explored spam filtering through game theory, an MBA from the Iran Technical and Vocational Training Organization, and a Bachelor’s degree in Computer Engineering from Seraj University with a thesis on solving optimization problems using ant colony algorithms. Professionally, Dr. Seyedeh Tina Sefati serves as the CEO and AI Architect at Saman Digital Eurasia, leading high-impact projects that integrate deep learning, natural language processing, and image analysis for clients across more than ten countries. Her prior experience as an AI Project Manager at Rayin Samaneh Arta and as a Programming Instructor at MFTabriz showcases her multifaceted expertise in both applied and academic contexts. Her research interests center around deep learning architectures, machine learning, NLP, image processing, and federated reinforcement learning for secure data transmission in wireless sensor networks. She has been involved in several international collaborations and industrial projects, including data-driven solutions for HepsiBurada and AndMe in Turkey, where she developed large-scale AI-based recommendation and forecasting systems. Dr. Seyedeh Tina Sefati’s technical skill set includes advanced proficiency in Python, TensorFlow, PyTorch, CNN, LSTM, GANs, and Transformers, demonstrating her ability to bridge theoretical concepts with real-world applications. Her research excellence is reflected in publications in Scopus and IEEE-indexed journals such as The Journal of Supercomputing and Mathematics. She is a recognized member of professional organizations such as IEEE and ACM and has received honors for her research contributions in deep learning and anomaly detection.

Professional Profiles: Google Scholar

Featured Publications 

  1. Sefati, S. T., Razavi, S. N., & Salehpour, P. (2025). Enhancing autoencoder models for multivariate time series anomaly detection: The role of noise and data amount. The Journal of Supercomputing, 81(4), 559. (2 citations)

  2. Sefati, S. T., Feizi-Derakhshi, M. R., & Razavi, S. N. (2016). Improvement of Persian spam filtering by game theory. International Journal of Advanced Computer Science and Applications, 7(6). (1 citation)

  3. Sefati, S. S., Sefati, S. T., Nazir, S., Farkhady, R. Z., & Obreja, S. G. (2025). Federated reinforcement learning with hybrid optimization for secure and reliable data transmission in wireless sensor networks (WSNs). Mathematics, 13(19), 1–37.

  4. Sefati, S. T., Razavi, S. N. (2024). Hybrid deep learning approach for intelligent anomaly detection in IoT sensor data. IEEE Internet of Things Journal. (3 citations)

  5. Sefati, S. T., Salehpour, P. (2023). GAN-based synthetic data generation for anomaly detection in multivariate time series. Expert Systems with Applications. (4 citations)

  6. Sefati, S. T., Feizi-Derakhshi, M. R. (2022). Game-theoretic optimization in distributed deep learning systems. Applied Intelligence. (2 citations)

  7. Sefati, S. T., Nazir, S. (2021). Deep learning-based adaptive framework for real-time sensor data analysis. IEEE Access. (3 citations)

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

Ms. Devinder Kaur | Computer Science | Women Researcher Award

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Ms. Devinder Kaur | Computer Science | Women Researcher Award 

Ms. Devinder Kaur, Mata Gujri College, India

Dr. Devinder Kaur is an experienced academician currently serving as an Assistant Professor in the Department of Computer Applications at Mata Gujri College, Fatehgarh Sahib, with over 20 years of teaching experience. She holds a Bachelor’s degree in Computer Applications from Punjabi University, Patiala, and a Master’s degree in Computer Applications from Punjab Technical University, Jalandhar. She is presently pursuing her Ph.D. in Computer Science at Sri Guru Granth Sahib World University, Fatehgarh Sahib. Dr. Kaur has authored two academic books—A Practical Approach to Java Programming and An Introduction to System Software—and contributed numerous research papers and book chapters in both national and international journals and conference proceedings. Her recent research interests focus on IoT and machine learning applications in livestock health monitoring, cybersecurity, environmental sustainability, and green computing. She has also actively participated in national-level conferences, addressing critical topics like social media addiction, privacy concerns, and e-waste management. Dr. Kaur’s scholarly contributions reflect her dedication to bridging practical technology with real-world challenges in both academic and agricultural domains.

Professional Profile:

GOOGLE SCHOLAR

SCOPUS

Summary of Suitability for Women Researcher Award 

Dr. Devinder Kaur is a highly qualified and accomplished academic with over 20 years of teaching experience in Computer Science, currently serving as an Assistant Professor at Mata Gujri College, Fatehgarh Sahib. She holds Bachelor’s and Master’s degrees in Computer Applications and is currently pursuing her Ph.D. in Computer Science from Sri Granth Sahib World University, highlighting her continuous academic advancement.

🎓 Education

  • 🎓 Bachelors of Computer Applications (BCA) from Punjabi University, Patiala.

  • 🎓 Masters of Computer Applications (MCA) from Punjab Technical University, Jalandhar.

  • 📚 Pursuing PhD in Computer Science from Sri Granth Sahib World University, Fatehgarh Sahib.

👩‍🏫 Work Experience

  • 🏫 Assistant Professor at Mata Gujri College, Fatehgarh Sahib.

  • 📅 20 years of teaching experience in the field of Computer Science.

🏆 Achievements, Awards & Honors

  • 📖 Published Books:

    • “A Practical Approach to Java Programming” – 📘 Unistar Books Pvt Ltd (2018)

    • “An Introduction to System Software” – 📗 Narosa Publishing House (2020)

  • 📝 Research Contributions:

    • 📚 Multiple book chapters and conference papers on topics such as:

      • Green Computing 🌱

      • Social Media Psychology 📱

      • E-Waste Management ♻️

      • IoT and Machine Learning in Livestock Health 🐄💡

      • Breast Cancer Classification Using ML 🎗️🧠

  • 🔗 Featured in IEEE, Auerbach Publications, and peer-reviewed journals like Discover Internet of Things, IJIRAE, Journal of Electrical Systems.

  • 🌐 Contributed to multidisciplinary and international conferences on smart tech, computing trends, and innovative research in AI & IoT.

Publication Top Notes:

CITED:409
CITED:135
CITED:118
CITED:102
CITED:97
CITED:87
CITED:81

Mr. Xi Tianyu | Automation Award | Best Researcher Award

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Mr. Xi Tianyu | Automation Award | Best Researcher Award

Mr. Xi Tianyu, Northeastern University, China

Dr. Xi Tianyu is a professor and doctoral supervisor at the Northeastern University School of Architecture, specializing in sustainable architecture, architectural technology, and green living. He has led over 10 national and provincial research projects, published more than 50 papers, and holds three authorized patents. He has contributed to national and industry standards, authored textbooks, and received multiple awards for teaching and research excellence. Dr. Xi is actively involved in several professional committees, including the China Urban Science Research Association and the China Engineering Construction Standardization Association, and is a member of international organizations such as ISIAQ and AIJ.

Professional Profile:

ORCID

Summary of Suitability for Best Researcher Award

Dr. Xi Tianyu is a highly accomplished researcher in sustainable architecture, with extensive contributions to green building technologies, energy conservation, and thermal comfort optimization. His leadership in over 10 national and provincial research projects, along with 50+ published papers and multiple patents, demonstrates his strong research impact. His involvement in national standards development, textbook authorship, and architectural design competitions further highlights his influence in academia and industry. Given his outstanding research, academic leadership, and numerous accolades, Dr. Xi Tianyu is a highly suitable candidate for the Best Researcher Award.

📚 Education & Work Experience

🎓 Doctor of Engineering
🏫 Professor & Doctoral Supervisor at Northeastern University School of Architecture

🏆 Achievements

🔬 Led 10+ research projects (national, provincial, and local), including:

  • 🇨🇳 National Natural Science Foundation Key Project sub-projects
  • 🎯 National Natural Science Foundation Youth Fund

📄 Published 50+ research papers
📜 3 authorized patents
📘 Co-authored 5 national & industry standards
📖 Contributed to 2 textbooks & authored 1 book (funded by National Publishing Fund)

🎨 Guided 10+ international & domestic architectural design competitions, winning:
🥇 Gu Yu Cup First Prize
🏅 AIM Cup Special Prize
🥉 China Habitat Environment Design Annual Award Bronze Award (2023)

🎖️ Awards & Honors

🏆 Northeastern University Teaching Achievement Awards:

  • 🥇 First Prize (2024)
  • 🥈 Second Prize (2022)
    🎓 Excellent Teaching Plan Award
    📜 Excellent Homework Guide Award
    📖 Excellent Paper Award (Chinese Higher Education Architecture Teaching Guidance Committee)

Publication Top Notes:

Analysis of the Characteristics of Heat Island Intensity Based on Local Climate Zones in the Transitional Season of Shenyang

 

Optimization of Residential Indoor Thermal Environment by Passive Design and Mechanical Ventilation in Tropical Savanna Climate Zone in Nigeria, Africa

 

A preliminary study of multidimensional semantic evaluation of outdoor thermal comfort in Chinese

 

Preliminary Research on Outdoor Thermal Comfort Evaluation in Severe Cold Regions by Machine Learning

A Review of Thermal Comfort Evaluation and Improvement in Urban Outdoor Spaces

Mr. Mohammed Aljamal | Artificial Intelligence | Best Researcher Award

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Mr. Mohammed Aljamal | Artificial Intelligence | Best Researcher Award 

Mr. Mohammed Aljamal, University of Bridgeport, United States

Mohammed Aljamal is a Laboratory Engineer and Ph.D. candidate in Computer Science & Engineering, based in the New York City Metropolitan Area. He holds a Master’s degree in Artificial Intelligence from the University of Bridgeport and is actively engaged in academic and professional communities as the President of the UB Robotics Club and a member of AIAA, UPE, and the Honor Society. With over four years of experience at the University of Bridgeport, he has contributed as a Laboratory Engineer, Graduate Research Assistant, and Teaching Assistant, specializing in laboratory management, hardware and software solutions, and IT infrastructure. His expertise spans project leadership, problem-solving, cross-functional team management, and innovative solution design. Beyond academia, Mohammed has a strong background in consulting, resource allocation, and international collaboration, having successfully led and completed critical projects. Passionate about technology and innovation, he continuously seeks opportunities to develop solutions that enhance user experiences and drive technological advancement.

Professional Profile:

GOOGLE SCHOLAR

Suitability of Mohammed Aljamal for the Best Researcher Award

Mohammed Aljamal is a highly skilled and innovative researcher with a strong background in Artificial Intelligence, Computer Science, and Engineering. His Ph.D. candidacy, extensive teaching experience, and leadership roles at the University of Bridgeport demonstrate his dedication to academic excellence and technological advancements.

Education 🎓

  • Ph.D. Candidate in Computer Science & Engineering – University of Bridgeport (Ongoing)
  • Master’s Degree in Artificial Intelligence – University of Bridgeport
  • Bachelor’s Degree in [Field Not Specified] – [University Not Specified]

Work Experience 💼

University of Bridgeport (4 years 1 month)

  • Labs Engineer (Feb 2022 – Present) ⚙️

    • Improved and maintained laboratory equipment.
    • Developed detailed hardware and software data for lab management.
    • Conducted inspections and routine maintenance on lab equipment.
    • Implemented new technology solutions and disaster recovery plans.
    • Coordinated IT services to ensure data availability and security.

  • Graduate Research & Teaching Assistant (Jan 2022 – Feb 2022) 📚

    • Assisted in research projects and student instruction.

  • Teaching and Laboratory Assistant (Feb 2021 – Dec 2021) 🏫

    • Assisted undergraduate and graduate students in Intro to Robotics.
    • Managed lab hours, discussions, assignments, and exams.

Achievements & Leadership 🌟

  • President of UB Robotics Club 🤖 – Leading robotics initiatives and student projects.
  • Successfully completed two delayed projects 🎯 – Resolved critical issues and met client satisfaction.
  • Consulted and collaborated with international vendors 🌍 – Gained experience in global tech solutions.
  • Designed and implemented innovative lab solutions 🔧 – Optimized university lab resources.

Awards & Honors 🏆

  • Member of AIAA (American Institute of Aeronautics and Astronautics) 🚀
  • Member of UPE (Upsilon Pi Epsilon – International Honor Society for Computing) 🖥️
  • Honor Society Member 🎖️

Publication Top Notes:

 

 

Mr. CEYHUN YILMAZ | Smart Devices | Best Researcher Award

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Mr. CEYHUN YILMAZ | Smart Devices | Best Researcher Award 

Mr. CEYHUN YILMAZ, Sakarya University, Turkey

Assoc. Prof. Dr. Ceyhun Yılmaz is a distinguished mechanical engineer specializing in thermodynamic modeling, renewable energy systems, and hydrogen fuel cells. He earned his Ph.D., M.Sc., and B.Sc. in Mechanical Engineering (English) from the University of Gaziantep. With over a decade of academic and research experience, he has served as a Research Assistant, Assistant Professor, and now an Associate Professor at Afyon Kocatepe University. His expertise includes thermoeconomic analysis, optimization of energy systems, and hydrogen production technologies. Dr. Yılmaz has supervised multiple graduate theses and led numerous TÜBİTAK-funded projects on sustainable energy solutions. He is an active member of ASME and the Turkish Thermal Science and Technique Association, contributing to high-impact scientific publications in top-tier journals. His dedication to advancing energy technologies continues to make a significant impact in the field.

Professional Profile:

GOOGLE SCHOLAR

SCOPUS

ORCID

Suitability for Best Researcher Award

Assoc. Prof. Dr. Ceyhun Yılmaz has extensive experience in mechanical engineering, energy systems, and thermoeconomic optimization. His contributions to hydrogen fuel cells, renewable energy, and sustainability demonstrate significant impact in his field. Given his strong academic background, leadership in research, and international training, he is a strong candidate for the Best Researcher Award.

Education 🎓

  • Bachelor of Science in Mechanical Engineering (English)
    University of Gaziantep, 2009
  • Master of Science in Mechanical Engineering (English)
    University of Gaziantep, 2011
  • Ph.D. in Mechanical Engineering (English)
    University of Gaziantep, 2016
    (Includes training at American Mechanical Engineering Society-Hydrogen and Fuel Cell, San Diego, USA, 2014 – 5 months)

Work Experience 💼

  • Research Assistant
    Department of Mechanical Engineering, University of Gaziantep, 2010-2016
  • Assistant Professor
    Department of Mechanical Engineering, Afyon Kocatepe University, 2017-2020
  • Associate Professor
    Department of Mechanical Engineering, Afyon Kocatepe University, 2020–present

Achievements 🏆

  • Supervised several Ph.D. and M.Sc. theses, including:
    • Ömer Faruk Güler: Numerical Modeling of Hydrogen PEM Fuel Cell and Thermoeconomic Optimization (Ph.D., 2022)
    • Muhammed Arslan: Thermodynamic Modeling of a Biogas Power Plant (Ph.D., 2022)
    • Ozan Şen: Thermoeconomic Analysis of Geothermal and Solar Energy (M.Sc., 2021)
    • Ali Hasan Abbas: Thermodynamic Analysis of Natural Gas Liquefaction (M.Sc., 2021)
  • Involved in multiple TÜBİTAK projects (Turkey’s scientific and technological research body), including:
    • Hydrogen Production Simulation using renewable energy and water electrolysis (2022-2023)
    • Concentrated Solar Collector for Afyon Province solar data (2022-2023)
    • Vanadium Redox Flow Battery Performance Evaluation (2023-2025)

Awards & Honors 🏅

  • Received TÜBİTAK project scholarships and executed high-impact research projects related to geothermal energy, hydrogen production, and renewable energy optimization.

Publication Top Notes:

Drought-induced oxidative damage and antioxidant responses in peanut (Arachis hypogaea L.) seedlings

CITED:162

Thermodynamic evaluation of geothermal energy powered hydrogen production by PEM water electrolysisEconomics of hydrogen production and liquefaction by geothermal energy

CITED:152

Economics of hydrogen production and liquefaction by geothermal energy

CITED:126

CITED:124
CITED:111

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

Mr. Heon-Sung Park | Neural Networks Awards | Best Researcher Award

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Mr. Heon-Sung Park | Neural Networks Awards | Best Researcher Award 

Mr. Heon-Sung Park, School of Computer Science and Engineering, Chung-Ang University, South Korea

Heon-Sung Park is a Ph.D. student in the School of Computer Science and Engineering at Chung-Ang University, South Korea, under the guidance of Professor Dae-Won Kim. His research interests focus on artificial intelligence, continual learning, and on-device AI. He previously completed his Master’s degree in the same department and earned his Bachelor’s degree in Information Technology from Silla University. Heon-Sung has contributed to international conferences, including the IEEE International Conference on Consumer Electronics, where he presented his work on a Continual Gesture Recognition System. He has been involved in various projects, such as developing deep learning algorithms for structural adhesive inspection and creating frameworks for on-device AI. He has received several accolades, including the Chung-Ang University Graduate Research Scholarship and the Best Paper Award at the Winter Academic Conference of the Korean Society of Computer and Information. Proficient in Python, LaTeX, and machine learning tools like PyTorch and TensorFlow, Heon-Sung is committed to advancing research in AI and its applications in real-world scenarios.

Professional Profile:

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Summary of Suitability for the Best Researcher Award: Heon-Sung Park

Heon-Sung Park is a highly qualified candidate for the Best Researcher Award, showcasing an exceptional academic background, significant research contributions, and a commitment to advancing the field of artificial intelligence.

Education 🎓

  • Ph.D. in Computer Science and Engineering
    Chung-Ang University (2022 – Present)
    Academic Adviser: Prof. Dae-Won Kim
  • Master’s in Computer Science and Engineering
    Chung-Ang University (2020 – 2022)
    Academic Adviser: Prof. Dae-Won Kim
  • Bachelor of Science in Information Technology
    Silla University (2014 – 2020)

Work Experience 💼

  • Ph.D. Student
    School of Computer Science and Engineering, Chung-Ang University (2022 – Present)

Achievements 🏆

  • Best Paper Award at the Winter Academic Conference, Korean Society of Computer and Information (2019)
  • Chung-Ang University Graduate Research Scholarship (2022 – 2024)

Awards and Honors 🌟

  • Chung-Ang University Graduate Research Scholarship (2022 – 2024)
  • Best Paper Award (2019) for the research paper presented at the Winter Academic Conference of the Korean Society of Computer and Information

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