Jaehyun Chung| Computer Science and Artificial Intelligence | Best Researcher Award

Mr. Jaehyun Chung| Computer Science and Artificial Intelligence | Best Researcher Award

Computer Science and Artificial Intelligence | Korea University | South Korea

Jaehyun Chung is a highly promising M.S. student at Korea University’s Artificial Intelligence and Mobility Laboratory, specializing in Generative AI, Reinforcement Learning, and Quantum AI applications. His research focuses on autonomous systems, AI-based mobility, defense technologies, and intelligent control, reflected in his involvement in over ten major R&D projects funded by prestigious Korean institutions. He has co-authored several high-impact journal articles and conference papers, including works published or under review in IEEE Transactions and ACM venues, and has earned multiple student paper awards, such as the IEEE Seoul Section Bronze Paper Award. Jaehyun demonstrates strong interdisciplinary capability, applying advanced AI techniques to fields as diverse as torpedo evasion, space rocket stabilization, and stock market prediction. Although early in his academic career, his rapid research output, national recognition, and contributions to innovative, real-world AI applications position him as an outstanding young researcher with exceptional potential for future impact.

Professional Profile 

Educational 

Jaehyun Chung pursued both his undergraduate and graduate studies at Korea University, one of South Korea’s leading institutions. He earned his Bachelor of Science (B.S.) in Electrical and Computer Engineering from the College of Engineering, completing the program between March 2017 and August 2023. Following his undergraduate success, he continued at Korea University to pursue a Master of Science (M.S.) in Electrical and Computer Engineering, starting in September 2023, where he is currently engaged in advanced research in Artificial Intelligence and Mobility. His academic path reflects a strong and consistent focus on engineering and cutting-edge AI technologies.

Professional Experience 

Jaehyun Chung is currently serving as a Research Assistant at the Artificial Intelligence and Mobility Laboratory at Korea University since September 2023, under the guidance of Professor Joongheon Kim. In this role, he actively contributes to a wide range of advanced R&D projects focused on AI-based autonomous systems, reinforcement learning, and quantum AI technologies. His professional experience includes hands-on involvement in nationally funded initiatives such as the Quantum Hyper-Driving Project, AI Bots Collaborative Platform, and Learning-Based Swarm Mission Planning Algorithms, among others. Jaehyun’s work spans across various sectors including defense, mobility, construction, and education, highlighting his ability to apply AI innovations to real-world challenges through practical, cross-disciplinary research collaborations.

Research Interests 

Jaehyun Chung’s research interests lie at the intersection of Artificial Intelligence, Autonomous Systems, and Quantum Computing. He is particularly focused on Generative AI technologies, including Transformer-based architectures, and their application in dynamic environments. A key area of his work involves AI-based Autonomous Control, where he utilizes advanced Reinforcement Learning techniques to optimize decision-making in systems such as autonomous vehicles, robotic platforms, and defense mechanisms. Additionally, his growing involvement in Quantum Reinforcement Learning and Federated Learning reflects a forward-looking approach to building scalable and intelligent systems. His research is deeply interdisciplinary, targeting real-world problems in mobility, finance, aerospace, and military applications through the lens of cutting-edge AI innovation.

Awards and Honors 

Jaehyun Chung has received several prestigious awards recognizing his innovation and excellence in research at an early stage in his academic career. In December 2024, he was honored with the IEEE Seoul Section Best Student Bronze Paper Award for his impactful work on stock prediction using correlation graph-based proximal policy optimization. In November 2024, he received the Outstanding Paper Award from the Korean Institute of Communications and Information Sciences (KICS) for his research on reinforcement learning-based countermeasure tactics against torpedo threats. Additionally, he earned another Bronze Paper Award at the IEEE Seoul Section Student Paper Contest in December 2023 for developing reinforcement learning strategies for aircraft taxi routing. These accolades reflect Jaehyun’s strong analytical skills, innovative thinking, and significant contributions to the fields of AI and autonomous control.

 Publications 

Title: Joint Quantum Reinforcement Learning and Stabilized Control for Spatio-Temporal Coordination in Metaverse
Authors: S. Park, J. Chung, C. Park, S. Jung, M. Choi, S. Cho, J. Kim
Year: 2024
Cited by: 19

Title: Realizing Stabilized Landing for Computation-Limited Reusable Rockets: A Quantum Reinforcement Learning Approach
Year: 2024
Cited by: 17

Title: Quantum Multi-Agent Reinforcement Learning for Cooperative Mobile Access in Space-Air-Ground Integrated Networks
Authors: G. S. Kim, Y. Cho, J. Chung, S. Park, S. Jung, Z. Han, J. Kim
Year: 2024
Cited by: 4

Title: DDPG-based Deep Reinforcement Learning Tactics for Defending Torpedo Attacks
Authors: J. Chung, C. Im, J. Choi, Y. Yoon, S. Park
Year: 2024
Cited by: 1

Title: Correlation-Assisted Spatio-Temporal Reinforcement Learning for Stock Revenue Maximization
Year: 2025

Title: Multi-Modal LLM-Based Fully-Automated Training Dataset Generation Software Platform for Mathematics Education
Year: 2025

Title: Trends in Reinforcement Learning Methods for Stock Prediction
Year: 2024

Conclusion 

Jaehyun Chung is an exceptionally strong early-career researcher who demonstrates intellectual depth, research versatility, and practical relevance across AI domains. He possesses all the qualities sought in a Best Researcher Award.

Raviteja Sista | Computer Science and Artificial Intelligence | Best Researcher Award

Mr. Raviteja Sista | Computer Science and Artificial Intelligence | Best Researcher Award

Research Scholar at Indian Institute of Technology Kharagpur, India

Raviteja Sista is a dynamic and accomplished researcher specializing in Artificial Intelligence, Deep Learning, and Medical Image Analysis. Currently pursuing his Ph.D. at the Indian Institute of Technology Kharagpur with an outstanding GPA of 9.4, he is a recipient of the prestigious Prime Minister’s Research Fellowship. Raviteja holds an MSc in Signal Processing and Communications from the University of Edinburgh and a Bachelor’s in Electronics and Communication Engineering from Osmania University. His research focuses on developing AI-driven frameworks for surgical planning and outcome prediction, with notable contributions to multimodal graph-based learning and surgical video analysis. He has published extensively in top-tier journals such as Medical Image Analysis and Computers in Biology and Medicine, and has actively contributed to international AI challenges and symposia. His technical expertise, academic excellence, and dedication to solving real-world healthcare problems through AI make him a standout figure in the research community.

Professional Profile 

🎓 Education of Raviteja Sista

Raviteja Sista has pursued a stellar academic path marked by excellence and innovation. He is currently enrolled in a Ph.D. program at the Indian Institute of Technology Kharagpur, specializing in Artificial Intelligence at the Centre of Excellence, where he maintains an impressive GPA of 9.4/10. Prior to this, he earned his Master of Science in Signal Processing and Communications with Distinction from the University of Edinburgh (2019–2020). His foundational engineering training was completed with a Bachelor of Engineering in Electronics and Communication from M.V.S.R. Engineering College, affiliated with Osmania University, where he secured a remarkable 85.34%. Raviteja also boasts an outstanding academic record from his early years, achieving 94.6% in Intermediate studies at Narayana Junior College and a CGPA of 9.8/10 in Class X from Lotus National School, Hyderabad.

💼 Professional Experience of Raviteja Sista

Raviteja Sista has a well-rounded professional background that bridges academia, research, and industry. He is currently a Teaching Assistant at IIT Kharagpur, where he supports academic instruction in AI and deep learning. Over the years, he has held teaching roles at several institutions including SRKR Engineering College, CSI Wesley Institute of Technology, Assam Down Town University, and JNTU Kakinada, demonstrating his commitment to education and knowledge dissemination. Complementing his academic roles, Raviteja also gained valuable industry experience as an Associate Software Developer Intern at Accenture Solutions Pvt. Ltd. and through multiple internships at Defence Research and Development Laboratory (DRDL), Hyderabad. His professional journey reflects a strong blend of research, software development, and teaching expertise, all anchored in the field of artificial intelligence and signal processing.

🔬 Research Interests of Raviteja Sista

Raviteja Sista’s research interests lie at the intersection of artificial intelligence and healthcare, with a strong focus on applying deep learning techniques to complex real-world problems. His core areas of interest include Deep Learning, Medical Image Analysis, Digital Signal Processing, Image Processing, Artificial Intelligence, and Design of Algorithms. He is particularly passionate about developing AI-powered systems for surgical planning and automation, leveraging multimodal data, graph neural networks, and computer vision. His work aims to enhance patient safety, improve clinical outcomes, and drive innovation in intelligent medical systems. Raviteja’s commitment to impactful, interdisciplinary research is evident in his projects and publications, which bridge technical depth with healthcare relevance.

🏅 Awards and Honors of Raviteja Sista

Raviteja Sista has been recognized with several prestigious awards and honors that highlight his academic brilliance and research potential. Most notably, he was awarded the Prime Minister’s Research Fellowship (PMRF) in 2022, one of India’s most esteemed research fellowships supporting exceptional doctoral scholars. He also earned a Certificate of Merit for completing the “Advanced Certification in Artificial Intelligence and Machine Learning” from IIIT Hyderabad in 2019. Additionally, Raviteja demonstrated national-level academic excellence by ranking in the Top 3% among over 1 lakh candidates in GATE 2019, a highly competitive examination for engineering graduates in India. These accolades reflect his consistent pursuit of excellence and his growing reputation as a promising researcher in the field of artificial intelligence.

🧾 Conclusion 

Sista Raviteja stands out as a highly qualified, technically accomplished, and visionary researcher in AI for healthcare. With strong academic credentials, impactful projects, respected publications, and active involvement in the scientific community, he demonstrates clear potential for leadership in scientific research.Despite minor areas of potential growth in independent authorship and translational work, his contributions already meet and, in some cases, exceed the typical benchmarks for the Best Researcher Award.

📚 Publications Top Noted

  1. Title: Deep neural hashing for content-based medical image retrieval: A survey
    Authors: A. Manna, R. Sista, D. Sheet
    Journal: Computers in Biology and Medicine, Volume 196, Article 110547
    Year: 2025
    Citations:
  2. Title: Artificial Intelligence (AI)–Based Model for Prediction of Adversity Outcome Following Laparoscopic Cholecystectomy—a Preliminary Report
    Authors: R. Agrawal, S. Hossain, H. Bisht, R. Sista, P.P. Chakrabarti, D. Sheet, U. De
    Journal: Indian Journal of Surgery, Volume 87 (1), Pages 52–59
    Year: 2025
    Citations: 1
  3. Title: Exploring the Limits of VLMs: A Dataset for Evaluating Text-to-Video Generation
    Authors: A. Srivastava, R. Sista, P.P. Chakrabarti, D. Sheet
    Conference: Indian Conference on Computer Vision Graphics and Image Processing (ICVGIP)
    Year: 2024
    Citations:
  4. Title: SimCol3D—3D reconstruction during colonoscopy challenge
    Authors: A. Rau, S. Bano, Y. Jin, P. Azagra, J. Morlana, R. Kader, E. Sanderson, …, R. Sista
    Journal: Medical Image Analysis, Volume 96, Article 103195
    Year: 2024
    Citations: 16
  5. Title: CholecTriplet2022: Show me a tool and tell me the triplet—An endoscopic vision challenge for surgical action triplet detection
    Authors: C.I. Nwoye, T. Yu, S. Sharma, A. Murali, D. Alapatt, A. Vardazaryan, K. Yuan, …, R. Sista
    Journal: Medical Image Analysis, Volume 89, Article 102888
    Year: 2023
    Citations: 29
  6. Title: CholecTriplet2021: A benchmark challenge for surgical action triplet recognition
    Authors: C.I. Nwoye, D. Alapatt, T. Yu, A. Vardazaryan, F. Xia, Z. Zhao, T. Xia, F. Jia, …, R. Sista
    Journal: Medical Image Analysis, Volume 86, Article 102803
    Year: 2023
    Citations: 61
  7. Title: CholecTriplet2022: Show me a tool and tell me the triplet—An endoscopic vision challenge for surgical action triplet detection
    Authors: C.I. Nwoye, T. Yu, S. Sharma, A. Murali, D. Alapatt, A. Vardazaryan, …, R. Sista
    Repository: arXiv, arXiv:2302.06294
    Year: 2023
    Citations:
  8. Title: I’m GROOT: a multi head multi GRaph netwOrk recognizing surgical actiOn Triplets
    Authors: R. Sista, R. Sathish, R. Agrawal, U. De, P.P. Chakrabarti, D. Sheet
    Conference: ICVGIP 2022
    Year: 2022
    Citations: 1
  9. Title: CholecTriplet2021: A benchmark challenge for surgical action triplet recognition
    Authors: C.I. Nwoye, D. Alapatt, T. Yu, A. Vardazaryan, F. Xia, Z. Zhao, …, R. Sista
    Repository: arXiv, arXiv:2204.04746
    Year: 2022
    Citations: 1
  10. Title: I’m GROOT: a multi head multi GRaph netwOrk recognizing surgical actiOn Triplets
    Authors: S. Raviteja, R. Sathish, R. Agrawal, U. De, P.P. Chakrabarti, D. Sheet
    Conference: ICVGIP
    Year: 2022
    Citations:
  11. Title: Challenges of Decomposing Tools in Surgical Scenes Through Disentangling The Latent Representations
    Authors: S.L. Gorantla, R. Sista, A. Srivastava, U. De, P.P. Chakrabarti, D. Sheet
    Workshop: ICLR Workshop on Challenges in Applied Deep Learning (ICBNB)
    Year: 2025 (Accepted)
    Citations:

 

Bhanu Shrestha | Computer Science and Artificial Intelligence | Best Researcher Award

Bhanu Shrestha | Computer Science and Artificial Intelligence | Best Researcher Award

Prof. Dr Bhanu Shrestha, Kwangwoon University, South Korea

Prof. Dr. Bhanu Shrestha is a distinguished academic in Electronic Engineering, with a Ph.D. from Kwangwoon University, Seoul, Korea. He has been active in various leadership roles, including Chairman of ICT-AES and Editor-in-Chief of the International Journal of Advanced Engineering. Dr. Shrestha has contributed extensively to research, with notable book publications and multiple awards, including the “Achievement Award” from IIBC Korea and “Best Paper Award” at ISSAC 214. His work spans various international conferences, focusing on advanced engineering, nanotechnology, and biosensor applications. 🌍📚🏅💻🧑‍🔬

Publication Profile

Scopus

Education

Prof. Dr. Bhanu Shrestha has an extensive academic background in Electronic Engineering. He completed his Ph.D. in Electronic Engineering at Kwangwoon University, Seoul, Korea (2004-2008), after earning his M.S. in the same field at the same institution (2002-2004). Dr. Shrestha’s journey in engineering began with a B.S. in Electronic Engineering from Kwangwoon University (1994-1998). His years of dedication to education and research have contributed significantly to advancements in the field of electronics. ⚙️🎓📡

Experience

Prof. Dr. Bhanu Shrestha is a distinguished leader in engineering, serving as Chairman of ICT-AES from 2022 to 2024. With a long tenure as the Editor-in-Chief of the International Journal of Advanced Engineering, he has shaped academic discourse in the field. His active involvement with the Nepal Engineering Council (NEC) and Nepal Engineers’ Association (NEA) further cements his influence in Nepal’s engineering community. Prof. Shrestha’s commitment to advancing engineering practices is evident through his leadership roles and active contributions to both national and international engineering platforms. 🛠️📚🔧🌍

Honor & Awards

Prof. Dr. Bhanu Shrestha has received numerous prestigious awards throughout his career. Notably, he was honored with the “Achievement Award” from IIBC Korea (2015) 🏆 and multiple “Best Paper Awards” from ISSAC 214 and ICACT (2014) 📄. He also earned the “Excellent Paper Award” from the Korea Institute of Information Technology (2012) 🏅 and the “Certificate of Honorary Citizenship” from the Mayor of Seong-buk, Seoul (2012) 🏙️. His accolades extend to Nepal, where he received the presidential “Nepal Vidhyabhusan Padak ‘Ka’” Gold Medal (2009) 🥇, and several honors for his contributions to Taekwondo and Hapkido 🥋.

Research Focus

Prof. Dr. Bhanu Shrestha’s research focuses on advanced computational techniques, particularly in the intersection of artificial intelligence (AI) and engineering. He explores areas such as machine learning, metaheuristics, and optimization methods applied to real-world challenges in fields like medical imaging (e.g., SPECT-MPI cardiovascular disease classification), traffic accident prediction, and network security. His work also extends to customer churn prediction in telecom industries and network security improvements. Shrestha’s contributions aim to enhance system efficiency, prediction accuracy, and security across diverse technological and engineering domains. 🧠💻⚙️🩺📡

Editorial and Conference

Prof. Dr. Bhanu Shrestha has made significant contributions to the field of engineering through his active involvement in international conferences like ISGMA 2015 and the International Conference on ICT & Digital Convergence (2018) 🌍📡. His dedication to global collaboration is evident in his participation in these events. Additionally, his editorial roles highlight his commitment to maintaining high-quality research output 📚📝. Prof. Dr. Shrestha continues to play a crucial role in advancing engineering through his global outreach, fostering innovation, and contributing to the growth of academic knowledge in his field. 🌟💡

Publication Top Notes

Multi-Scale Dilated Convolution Network for SPECT-MPI Cardiovascular Disease Classification with Adaptive Denoising and Attenuation

CorrectionSpecial Issue on Data Analysis and Artificial Intelligence for IoT

Correction to: A Proposed Waiting Time Algorithm for a Prediction and Prevention System of Traffic Accidents Using Smart Sensors (Electronics, (2022), 11, 11, (1765), 10.3390/electronics11111765)

Levy Flight-Based Improved Grey Wolf Optimization: A Solution for Various Engineering Problems

Leveraging metaheuristics with artificial intelligence for customer churn prediction in telecom industries

A Study on Improving M2M Network Security through Abnormal Traffic Control

Generative Adversarial Networks with Quantum Optimization Model for Mobile Edge Computing in IoT Big Data

 

Abdul Aziz | Computer Science and Artificial Intelligence | Best Researcher Award

Abdul Aziz | Computer Science and Artificial Intelligence | Best Researcher Award

Mr Abdul Aziz, Khulna University of Engineering & Technology, Bangladesh

🧑‍🏫 Abdul Aziz is an Assistant Professor at Khulna University of Engineering & Technology (KUET), specializing in computer science and engineering. With a passion for deep learning 🤖, fuzzy logic, and smart city innovations 🌆, he has presented at major conferences like ICCIT and BIM. A recipient of the Vice-Chancellor Award 🏅 and a University Gold Medalist 🥇, Abdul’s research focuses on AI-driven solutions for real-world problems. His notable works include danger detection for women and children and risk evaluation of hazardous chemicals. Dedicated to education and research, he inspires future engineers at KUET. 📚✨

Publication Profile

Scopus

Academic Qualifications

Mr. Abdul Aziz is an accomplished computer science professional with a strong academic background 🎓. He earned his Master of Science in Computer Science & Engineering from Khulna University of Engineering & Technology (KUET) in 2022, achieving a CGPA of 3.75/4.00 💻. Previously, he completed his Bachelor of Science at KUET in 2017 with an outstanding CGPA of 3.92/4.00, securing 1st place among 59 students and topping the EEE Faculty 🏆. His academic journey began at Shahid Syed Nazrul Islam College, where he completed his Higher Secondary Certificate in 2012 📚. Abdul Aziz exemplifies dedication and excellence in his field.

Professional Experiences

Mr. Abdul Aziz is an accomplished academic in computer science, currently serving as an Assistant Professor at Khulna University of Engineering & Technology (KUET) since December 2020 🎓💻. He began his journey at KUET as an Adjunct Faculty (Lecturer) in August 2017 and later became a Lecturer from January 2018 to December 2020 📚. Prior to this, he contributed to Northern University of Business and Technology Khulna (NUBTK) as a Lecturer from July to December 2017 🏫. With a strong dedication to education and research, Mr. Aziz continues to shape future engineers and drive innovation in computer science 🚀🔍.

Achievements, Awards, and Certifications

Mr. Abdul Aziz is a distinguished academic and researcher recognized for his outstanding achievements🏅. In 2024, he received the Vice-Chancellor Award for High Impact Research Journal Publication📚. He was the University Gold Medalist in 2018 for securing 1st position in his graduating class🥇. From 2013 to 2016, Abdul earned the University Vocational Scholarship and the Dean’s Award for ranking among the top 10% of students for four consecutive years🏆. His programming skills were highlighted in 2014 when he secured 3rd place in one intra-batch contest and 1st place in another💻🥇.

Membership

Mr. Abdul Aziz is a passionate coach, mentor, and trainer in programming and technology 💻. Since 2018, he has coached 25+ teams for ICPC regionals, National Girls Programming Contests, and university competitions. He led the KUET_Effervescent team to the 48th ICPC World Finals in Astana, Kazakhstan (2024) 🏆. Aziz serves as an Associate Member of the Institution of Engineers, Bangladesh ⚙️ and reviews international conferences. As a trainer for BDSET and ITEE programs, he uplifts digital skills 📊. He also organized major events like BitFest 2019 and NHSPC, mentoring future innovators. His journey began as a debate champion 🎤.

Academic Projects

Mr. Abdul Aziz has undertaken diverse academic projects during his undergraduate studies at KUET. In his 3rd semester (2014), he developed a Java-based smart home automation desktop app 🏠💻. In the 4th semester (2014-2015), he created a medical center automation website using PHP, HTML, and MySQL for doctor-patient communication 🏥🌐. His 5th semester (2015) featured hospital DBMS design with PL/SQL and Oracle 📊. By the 6th semester (2015-2016), he built an Android app for real-time object tracking 📱🗺️ and a keypad/Bluetooth-controlled LCD display project using Arduino 📟🔷. In his final semester, he developed a 3D car racing game with C++ and OpenGL 🚗🎮.

Research Focus

Abdul Aziz’s research focuses on applying deep learning 🤖, signal processing 🎵, and fuzzy logic 🔢 to develop innovative solutions in safety, smart cities 🌆, and mobile applications 📱. His work spans danger detection for women and children 🚨, city service task distribution 🏙️, and chemical risk evaluation 🧪. Additionally, Aziz explores advanced error detection and correction in computing 💻. His contributions aim to enhance public safety, improve urban services, and boost system reliability. With publications in top-tier journals 🏆, his research bridges technology and real-world applications, fostering smarter and safer environments.

Publication Top Notes

DangerDet: A mobile application-based danger detection platform for women and children using deep learning

ShopiRound: An Android application-based e-commerce system to find products nearby using travelling salesman problem

A fuzzy logic-based risk evaluation and precaution level estimation of explosive, flammable, and toxic chemicals for preventing damages

Multi-bit error detection and correction technique using HVDK (Horizontal-Vertical-Diagonal-Knight) parity

CitySolution: A complaining task distributive mobile application for smart city corporation using deep learning

 

Yunqiang Sun | Artificial Intelligence | Best Researcher Award

Yunqiang Sun | Artificial Intelligence | Best Researcher Award

Prof. Dr Yunqiang Sun, 中北大学, China

Prof. Dr. Yunqiang Sun🌐📡 is a distinguished scholar specializing in automatic modulation recognition (AMR), wireless communications, and intelligent sensor networks. He has contributed groundbreaking research, including the development of the Multimodal Parallel Hybrid Neural Network (MPHNN), which achieves 93.1% recognition accuracy with reduced complexity. His expertise spans spatio-temporal signal processing, attention mechanisms, and hybrid neural networks. Prof. Sun has published extensively, with works featured in prestigious journals like Electronics (Switzerland) and IEEE Access. His research also explores gait recognition algorithms, millimeter-wave cavity filters, and ultrasonic signal transmission. A dedicated innovator, Prof. Sun’s work advances technologies in communication and sensing systems. 📊📖✨

Publication Profile

Scopus

Proposed Solution 🤖✨

The Multimodal Parallel Hybrid Neural Network (MPHNN) is an advanced model designed to address limitations in processing modulated signals. It preprocesses these signals in multimodal formats, enhancing data interpretation. By combining Convolutional Neural Networks (CNN) for spatial feature extraction and Bidirectional Gated Recurrent Units (Bi-GRU) for temporal feature processing, MPHNN efficiently captures both spatial and temporal dependencies. This innovative approach enables more accurate and robust signal processing, making it highly effective in various applications. Prof. Dr. Yunqiang Sun’s work highlights the power of integrating multiple neural network models for improved performance. 🧠🔧📡📊

Attention Mechanisms 🎯🔗

Prof. Dr. Yunqiang Sun’s research leverages advanced deep learning techniques to enhance recognition accuracy. By integrating the Convolutional Block Attention Module (CBAM) and Multi-Head Self-Attention (MHSA), his work in the Multi-Path Hierarchical Neural Network (MPHNN) effectively combines both temporal and spatial features. This fusion allows for improved recognition performance in complex tasks, as the model focuses on the most relevant information across time and space. Prof. Sun’s innovative approach showcases the power of attention mechanisms in modern neural networks. 🤖📊🧠🔍

Results 📊✅

Prof. Dr. Yunqiang Sun, MPHNN, has achieved an impressive 93.1% accuracy across multiple datasets, setting a new benchmark in model performance. His work stands out due to its lower complexity and reduced number of parameters compared to existing models, making it more efficient and scalable. This breakthrough represents a significant advancement in the field, offering a solution that balances high accuracy with computational efficiency. Prof. Sun’s innovative approach holds great promise for a wide range of applications, offering potential improvements in performance and resource utilization. 🔬📊💡📈

Diverse Publication Record

Prof. Dr. Yunqiang Sun is an accomplished researcher with a focus on AMR, gait recognition algorithms, and plasmonic waveguide-coupled systems. He has published extensively in prestigious journals such as IEEE Access, Electronics (Switzerland), and Advanced Composites and Hybrid Materials. Notable works include impactful publications like CTRNet: An Automatic Modulation Recognition Based on Transformer-CNN Neural Network and Research on Modulation Recognition Algorithm Based on Channel and Spatial Self-Attention Mechanism. Prof. Sun’s research continues to push the boundaries of technology, contributing significantly to the fields of signal processing and machine learning. 📚🔬📈💡

Citations and Recognition

Prof. Dr. Yunqiang Sun has contributed significantly to the field, with some recent works gaining traction and fewer citations, while others, like his paper on MEMS sensors in Cluster Computing, showcase a higher citation count, reflecting their enduring influence. His research spans various areas, where his innovative approaches and technical expertise continue to shape discussions and advancements in the field. Despite the varying citation impact, Prof. Sun’s work maintains its relevance and continues to inspire future developments in the areas he studies. 🌟📚🔬🧠📈

Research Focus

Prof. Dr. Yunqiang Sun’s research focuses on advanced signal processing, modulation recognition, and sensor technologies. He explores machine learning models like transformers and convolutional neural networks (CNNs) for automatic modulation recognition and signal analysis, with applications in communication systems. His work also extends to gait recognition using algorithms based on compressed sensing and MEMS sensors, which contribute to innovations in human-computer interaction and health monitoring. Prof. Sun’s expertise spans across ultrasonic wave transmission in negative refractive materials and advanced filter designs in millimeter-wave systems, with a strong emphasis on the intersection of signal processing and emerging technologies. 📡🤖📊

Publication Top Notes

CTRNet: An Automatic Modulation Recognition Based on Transformer-CNN Neural Network

Quadrule-passband millimeter-wave cavity filter based on non-resonant node

Transmission characteristics of ultrasonic longitudinal wave signals in negative refractive index materials

Numerical calculus solution of gait recognition algorithm based on compressed sensing

Application and research of MEMS sensor in gait recognition algorithm

 

 

Jerzy Montusiewicz | Computer Science and Artificial Intelligence | Best Researcher Award

Jerzy Montusiewicz | Computer Science and Artificial Intelligence | Best Researcher Award

Mr Jerzy Montusiewicz, Lublin University of Technology, Department of Computer Science, Poland

Based on the research achievements of Prof. Jerzy Montusiewicz, he appears to be a strong candidate for the Best Researcher Award. Here’s a summary of his contributions and achievements:

Publication profile

google scholar

Research Summary for Best Researcher Award

1. K-medoids Clustering and Fuzzy Sets for Isolation Forest
Montusiewicz co-authored this 2021 IEEE International Conference on Fuzzy Systems paper on clustering and fuzzy sets, highlighting advanced methodologies in data analysis. This work is cited for its impact on clustering techniques in complex datasets.

2. Preparation of 3D Models of Cultural Heritage Objects to be Recognized by Touch by the Blind—Case Studies
In this 2022 Applied Sciences publication, Montusiewicz contributed to developing 3D models of cultural heritage objects accessible to the visually impaired, showcasing his commitment to inclusivity in digital heritage.

3. Comparative Analysis of Digital Models of Objects of Cultural Heritage Obtained by the “3D SLS” and “SfM” Methods
This 2021 study, published in Applied Sciences, explores the comparative effectiveness of different 3D scanning methods for cultural heritage preservation, reflecting Montusiewicz’s expertise in digital preservation techniques.

4. 3D Scanning and Visualization of Large Monuments of Timurid Architecture in Central Asia—A Methodical Approach
Montusiewicz’s 2020 Journal on Computing and Cultural Heritage article demonstrates innovative methods for scanning large historical monuments, emphasizing his contributions to preserving Central Asian architectural heritage.

5. Virtual and Interactive Museum of Archaeological Artefacts from Afrasiyab—An Ancient City on the Silk Road
This 2020 paper in Digital Applications in Archaeology and Cultural Heritage presents the creation of a virtual museum for archaeological artefacts, illustrating Montusiewicz’s role in advancing digital tools for archaeology.

6. A Decomposition Strategy for Multicriteria Optimization with Application to Machine Tool Design
Montusiewicz’s 1990 publication in Engineering Costs and Production Economics addresses optimization strategies in machine tool design, demonstrating his early contributions to engineering and optimization techniques.

7. Structured-Light 3D Scanning of Exhibited Historical Clothing—A First-Ever Methodical Trial and Its Results
This 2021 Heritage Science study, co-authored by Montusiewicz, represents a pioneering effort in 3D scanning of historical clothing, marking a significant advancement in the field of heritage science.

8. Documenting the Geometry of Large Architectural Monuments Using 3D Scanning—The Case of the Dome of the Golden Mosque of the Tillya-Kori Madrasah in Samarkand
Montusiewicz’s research, published in 2022, focuses on documenting the geometry of significant architectural monuments, highlighting his continued impact on architectural preservation through advanced scanning techniques.

Prof. Montusiewicz’s diverse research, spanning from advanced 3D scanning techniques to the preservation of cultural heritage, underscores his significant contributions to the fields of computer graphics and digital preservation. His innovative approaches and practical applications make him an exemplary candidate for the Best Researcher Award.

Research focus

Based on the provided publications, the research focus appears to be in digital heritage preservation and 3D scanning technologies. The work of J. Montusiewicz and collaborators emphasizes creating and analyzing 3D models of cultural heritage objects, including methods for blind accessibility and the application of scanning technologies for historical artifacts and architecture. This includes comparative studies of different scanning methods and their effectiveness, as well as the development of interactive digital museums. Their research contributes significantly to both the preservation of cultural heritage and the advancement of technological applications in archaeology. 🏛️🔍📏

Publication top notes

K-medoids clustering and fuzzy sets for isolation forest

Preparation of 3D models of cultural heritage objects to be recognised by touch by the blind—case studies

Comparative analysis of digital models of objects of cultural heritage obtained by the “3D SLS” and “SfM” methods

3D Scanning and Visualization of Large Monuments of Timurid Architecture in Central Asia–A Methodical Approach

Virtual and interactive museum of archaeological artefacts from Afrasiyab–an ancient city on the silk road

A decomposition strategy for multicriteria optimization with application to machine tool design

Structured-light 3D scanning of exhibited historical clothing—a first-ever methodical trial and its results

 

ABDULKADIR DAUDA | Computer Science and Artificial Intelligence | Best Researcher Award

ABDULKADIR DAUDA | Computer Science and Artificial Intelligence | Best Researcher Award

ABDULKADIR DAUDA, University of Reims Champagne-Ardenne, France

Based on the information provided, Mr. Abdulkadir Dauda appears to be a strong candidate for the Best Researcher Award. His academic background, professional experience, and research contributions highlight his qualifications and impact in the field of computer science. Below is an evaluation of his suitability for the award:

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Academic and Professional Qualifications

Mr. Dauda has a robust academic background, including a Master of Science Degree in Computer Science with Distinction and ongoing doctoral studies at Universite De Reims Champagne-Ardenne, France. His academic achievements, particularly his distinction at the Master’s level, underscore his dedication and capability in his field.

Work Experience and Contributions

Mr. Dauda’s professional experience as a Lecturer II in the Department of Computer Science at the Federal University of Lafia (2014-2022) demonstrates his commitment to education and research. He has taken on significant roles, such as Departmental Examination Officer and Programme Coordinator, which show his leadership and involvement in academic administration. His work in system and network administration during his tenure at the Federal Capital Territory Judiciary further highlights his practical expertise in computer science.

Research Contributions

Mr. Dauda has an impressive portfolio of research publications that focus on critical areas such as IoT Security, High-Performance Computing, and Distributed and Parallel Architectures. His publications in reputed journals and conferences, including the 2023 International Conference on Wireless Networks and Mobile Communications (WINCOM), demonstrate his active engagement in advancing knowledge in these fields. His collaborative work with international scholars further reflects the quality and impact of his research.

Research Interests and Impact

Mr. Dauda’s research interests in emerging and high-impact areas like IoT Security and Big Data are particularly relevant in today’s technological landscape. His contributions to these fields, through both his research and practical work, suggest a deep understanding and innovative approach to solving complex problems in computer science.

Conclusion

Mr. Abdulkadir Dauda’s academic excellence, professional experience, and significant research contributions make him a suitable candidate for the Best Researcher Award. His work not only advances the field of computer science but also demonstrates a commitment to teaching, mentoring, and community service, further solidifying his qualification for this honor.

Publication top notes

A Survey on IoT Application Architectures

 

Simon Wong | Computer Science and Artificial Intelligence | Best Researcher Award

Simon Wong | Computer Science and Artificial Intelligence | Best Researcher Award

Dr Simon Wong, College of Professional and Continuing Education, the Hong Kong Polytechnic University, Hong Kong

Dr. Simon Wong is a distinguished educator with a Doctor of Education from the University of Leicester, UK. His extensive academic background includes an M.Phil. from PolyU and a Bachelor’s in Computer Science from the University of Minnesota, USA. Dr. Wong serves as a lecturer at CPCE, PolyU, and holds professional certifications in financial technology and Oracle. His industrial experience spans roles as a senior consultant and software engineer. Dr. Wong has led numerous academic programs and research initiatives, specializing in subjects like database systems, e-commerce, and cloud computing. He is a committed member of professional organizations and has significantly contributed to academic management and leadership. 🌟🎓💼

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Academic Qualifications

Dr.  holds a Doctor of Education from the University of Leicester, UK (2012), where they researched effective online learning in Hong Kong higher education institutions, supervised by Prof. Paul Cooper 🎓📚. They also earned a Master of Philosophy from PolyU (1997), focusing on designing and analyzing a bypass construction algorithm for self-healing asynchronous transfer mode networks under the guidance of Dr. K. C. Chang and Prof. Keith Chan 📘💡. Additionally, they graduated with distinction in Computer Science from the University of Minnesota, Twin Cities, USA (1993) 🎓💻.

Experience

With extensive experience in the tech industry, the individual served as a Senior Consultant at Oracle Systems Hong Kong Ltd (Aug 2000 – Sep 2003) 🏢, a Software Engineer at Skyworld Technology Ltd (Jun 1993 – May 1994) 💻, and a Consultant at the Microcomputer Laboratory, University of Minnesota (Sep 1991 – Mar 1993) 📊. Since Sep 2003, they have been a Lecturer at CPCE, PolyU 📚, and previously held roles as a Lecturer (Sep 1998 – Aug 2000) 👨‍🏫, Demonstrator (Sep 1996 – Aug 1998) 🔬, and Research Student (Jun 1994 – Jun 1996) 🎓 in the Department of Computing at PolyU.

Awards

With an illustrious career marked by numerous accolades and significant research contributions, I have received the Best Paper Awards in 2018, 2019, and 2023 🎉📚. I have successfully led and contributed to various high-impact projects, including those funded by the Quality Education Fund and CPCE 🏆💡. My roles have ranged from Associate Academic Director to Co-Investigator and Consultant, focusing on innovative technologies like AI, blockchain, and machine learning 🤖🔗. My work has significantly advanced educational technology and pedagogy, earning over HK$2 million in funding for projects aimed at improving learning experiences and outcomes 🎓💼.

Research focus

Simon Wong’s research focus is on the integration of blockchain technology in supply chain management, emphasizing sustainability. His work includes examining the adoption of blockchain integrated with cloud-based systems and machine learning to enhance sustainable practices in supply chains. Through critical literature reviews and case studies, Wong investigates the technical sustainability and implications of blockchain technology. His research aims to provide insights into the practical applications and benefits of blockchain for improving transparency, efficiency, and sustainability in supply chain operations. 🌐📦🔗📊🌿

Publication top notes

A Critical Literature Review on Blockchain Technology Adoption in Supply Chains

A Case Study of How Maersk Adopts Cloud-Based Blockchain Integrated with Machine Learning for Sustainable Practices

Technical Sustainability of Cloud-Based Blockchain Integrated with Machine Learning for Supply Chain Management

Sustainability of Blockchain Technology in Supply Chains: Implications from a Critical Literature Review

 

William Lawless | Computer Science and Artificial Intelligence | Best Researcher Award

William Lawless | Computer Science and Artificial Intelligence | Best Researcher Award

Dr William Lawless, Paine College, United States

W.F. Lawless is a pioneering mechanical engineer known for blowing the whistle on nuclear waste mismanagement in 1983. He earned his PhD in 1992, focusing on organizational failures among leading scientists. Invited to join the DOE’s citizens advisory board at Savannah River Site, he coauthored key recommendations for environmental remediation. His research centers on autonomous human-machine teams, and he has edited nine influential books on AI, including the award-nominated Human-Machine Shared Contexts. With over 300 peer-reviewed publications, he has organized multiple symposia and special issues, contributing significantly to the field of artificial intelligence. 🔬🤖📚

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Research focus

William Lawless’s research focuses on the dynamics of human-machine collaboration, particularly in the context of autonomy and uncertainty. His work explores how knowledge, risk perception, and interdependence influence the effectiveness of autonomous teams. By examining models that integrate quantum-like principles, he aims to enhance our understanding of decision-making processes within complex systems. His publications highlight the essential tension between knowledge and uncertainty, proposing new frameworks for improving human-machine interactions. This interdisciplinary approach bridges technology and human factors, contributing significantly to fields like robotics, artificial intelligence, and human-computer interaction. 🤖📊🔍

Publication top notes

Shannon Holes, Black Holes, and Knowledge: The Essential Tension for Autonomous Human–Machine Teams Facing Uncertainty

A Quantum-like Model of Interdependence for Embodied Human–Machine Teams: Reviewing the Path to Autonomy Facing Complexity and Uncertainty

Risk Determination versus Risk Perception: A New Model of Reality for Human–Machine Autonomy

 

Ioannis Chatzilygeroudis | Computer Science and Artificial Intelligence | Best Researcher Award

Ioannis Chatzilygeroudis | Computer Science and Artificial Intelligence | Best Researcher Award

Prof Ioannis Chatzilygeroudis, University of Patras, Greece

Prof. Emeritus at the University of Patras, Greece, with a rich educational background in Mechanical and Electrical Engineering (NTUA), Theology (University of Athens), MSc in Information Technology, and a PhD in Artificial Intelligence (University of Nottingham). Fluent in Greek and English, he specializes in AI, KR&R, knowledge-based systems, theorem proving, intelligent tutoring, e-learning, machine learning, natural language generation, sentiment analysis, semantic web, and educational robotics. His prolific research includes a PhD thesis, 18 edited volumes, 21 book chapters, 46 journal papers, 115 conference papers, 8 national conference papers, and 14 workshop papers. 📚🤖💻🌐

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Education

📚 From September 1968 to June 1974, completed secondary education, earning a Certificate of High School Graduation in Science. 🎓 Pursued a Diploma in Mechanical and Electrical Engineering with a specialization in Electronics at the National Technical University of Athens from October 1974 to July 1979. 📜 From February to June 1983, obtained a Certificate of Educational Studies from PATES of SELETE, Greece. 📖 Achieved a Bachelor in Theology from the University of Athens, completed between October 1979 and December 1987. 🎓 Earned an MSc in Information Technology from the University of Nottingham in 1989, followed by a PhD in Artificial Intelligence from the same university in 1992. 🧠 Thesis: “Integrating Logic and Objects for Knowledge Representation and Reasoning.”

Experience

📘 From Feb. 1982 to June 1982, I served as a part-time lab professor at PALMER Higher School of Electronics in Greece, teaching Electronics Lab. My full-time teaching journey began at TEI of Athens (1982-84), where I covered courses like Electrotechnics and Circuit Theory. My secondary education tenure (1984-92) focused on electrical engineering subjects. I then transitioned to higher education, teaching at TEI of Kozani and Chalkida, and later at the University of Nottingham (1990-92). From 1995-2006, I was a senior researcher and lecturer at the University of Patras, ultimately becoming a professor (2009-2023). Now, I am a Professor Emeritus. 🎓🔬

Projects

From June 1993 to November 1995, I managed the CTI team for the DELTA-CIME project, developing a knowledge-based production control system. I led several initiatives, including the MEDFORM project for multimedia education and the national project for educational software in chemistry. As a senior researcher, I contributed to intelligent systems for tele-education and hybrid knowledge representation. I led multiple European projects like MENUET, AVARES, and TESLA, focusing on innovative education through virtual reality. My work aims to enhance learning experiences across disciplines, involving collaboration with various international partners. 🌍📚💻🎓

Research focus

Ioannis Hatzilygeroudis specializes in artificial intelligence and its applications in various domains, particularly in agriculture and healthcare. His research includes intelligent systems for diagnosing farmed fish diseases, employing deep learning techniques for image analysis, and exploring natural language processing methods. He has contributed significantly to the development of expert systems and reinforcement learning approaches to improve disease prediction in aquaculture. Additionally, his work in sentiment analysis and e-learning demonstrates a commitment to advancing educational technologies and user experience. Hatzilygeroudis’s interdisciplinary approach combines computer science with practical applications, making significant strides in health and environmental management. 🌱🐟💻📊

Publication focus

Using Level-Based Multiple Reasoning in a Web-Based Intelligent System for the Diagnosis of Farmed Fish Diseases

An Integrated GIS-Based Reinforcement Learning Approach for Efficient Prediction of Disease Transmission in Aquaculture

Speech Emotion Recognition Using Convolutional Neural Networks with Attention Mechanism

Expert Systems for Farmed Fish Disease Diagnosis: An Overview and a Proposal

Expert Systems for Farmed Fish Disease Diagnosis: An Overview and a Proposal

A Convolutional Autoencoder Approach for Boosting the Specificity of Retinal Blood Vessels Segmentation

Evaluating Deep Learning Techniques for Natural Language Inference