Dr Shuai Cao, School of Automation, Wuhan University of Technology, China

Dr. Shuai Cao is a dynamic researcher in the field of Computational Intelligence, currently pursuing graduate studies at Kunming University of Science and Technology and engaging in joint research at the Guangdong Academy of Sciences. With a focus on enhancing meta-heuristic algorithms, Dr. Cao has contributed significantly to engineering optimization, especially in AGV path planning and offset printing machine design. He is the mind behind the innovative Piranha Foraging Optimization Algorithm (PFOA) and co-author of several impactful SCI/EI publications. His expertise in algorithm improvement, machine learning, and pattern recognition is reflected through funded projects and hands-on roles in top research institutions like the South China Intelligent Robot Innovation Institute. With a remarkable blend of theoretical insight and practical application, Dr. Cao is a promising candidate for the Best Researcher Award, embodying academic rigor and real-world impact.

Publication Profile

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Education

Dr. Shuai Cao’s academic journey began at Baotou Rare Earth High-tech No. 1 High School (2014–2017), where he laid a strong foundation in the sciences. He pursued his undergraduate degree in Mechanical and Electronic Engineering at Chongqing University of Humanities, Science and Technology (2017–2021), gaining critical insights into systems design and robotics. Since 2021, he has been a postgraduate student in Electronic Information at Kunming University of Science and Technology, further sharpening his expertise in computational theory and algorithmic systems. Complementing his studies, Dr. Cao has been engaged in a joint training program at the Intelligent Manufacturing Institute of the Guangdong Academy of Sciences since 2022. His coursework includes meta-heuristic algorithms, machine learning, digital signal processing, and pattern recognition, all of which feed directly into his research in Computational Intelligence and engineering optimization. His interdisciplinary background empowers him to tackle complex problems with innovative solutions.

Experience

Dr. Shuai Cao has held impactful roles in prestigious research institutions. From May 2022 to July 2023, he worked at the Intelligent Manufacturing Institute of the Guangdong Academy of Sciences, where he conducted advanced research on AGV handling robots. This included applying improved intelligent algorithms for path planning and optimization scheduling—work closely aligned with his master’s thesis. Since July 2023, he has been with the South China Intelligent Robot Innovation Institute, applying swarm intelligence methods to optimize the structure of high-speed multi-color offset printing machines. Dr. Cao’s work integrates theoretical research with industrial application, setting a benchmark for practical relevance. His involvement in key science and innovation projects also reflects his growing leadership in the field. From optimization algorithms to real-world robotic systems, Dr. Cao’s hands-on approach is shaping the future of intelligent manufacturing.

Awards and Honors

Dr. Shuai Cao has earned distinguished recognition in both academic and research circles for his innovative contributions to engineering optimization. As a lead researcher on multiple government-funded projects—including “Research and Application of Intelligent Scheduling of Mobile Collaborative Robot Clusters for Intelligent Manufacturing” (Project Code: 2130218003022) and the “Foshan Science and Technology Innovation Team Project” (Project Code: FS0AA-KJ919-4402-0060)—he has demonstrated expertise in bridging theory with practical industrial solutions. His pioneering research has been published in high-impact SCI and EI journals and conferences, such as IEEE ACCESS and the International Conference on Robotics and Automation Engineering (ICRAE). A highlight of his work is the development of the Piranha Foraging Optimization Algorithm (PFOA), which has garnered considerable attention in the optimization community for its novelty and effectiveness. Dr. Cao’s sustained dedication to cutting-edge innovation, along with his leadership in collaborative, cross-disciplinary projects, makes him a compelling nominee for the Best Researcher Award.

Research Focus

Dr. Shuai Cao’s research is centered on Computational Intelligence, specifically the improvement and engineering application of swarm intelligence algorithms. His work addresses key challenges in traditional optimization methods, such as premature convergence, low population diversity, and slow optimization speeds. He has successfully designed algorithms that overcome these limitations, notably the Piranha Foraging Optimization Algorithm (PFOA). His research extends to practical applications like automated guided vehicle (AGV) path planning, scheduling in smart factories, and mechanical structure optimization for high-speed printing systems. Through interdisciplinary methods, he combines machine learning, pattern recognition, and digital signal processing to bring theoretical advancements into real-world manufacturing challenges. With a clear aim of enhancing intelligent manufacturing systems, his research contributes to both academic knowledge and industrial innovation. His growing body of work reflects originality, technical rigor, and a strong alignment with modern engineering demands.

Publication Top Notes

Research on the Design and Application of Multi-Port Energy Routers

Kaimin Wei | Computer Science and Artificial Intelligence | Best Researcher Award

Posted on 10/02/202510/02/2025 by ScienceFather

Kaimin Wei | Computer Science and Artificial Intelligence | Best Researcher Award

Prof Kaimin Wei, Jinan University, China

Kaimin Wei is a full professor at the College of Information Science and Technology, Jinan University, China 🇨🇳. He earned his Ph.D. in Computer Science from Beihang University (2015), Master’s in Computer Application Technology from Zhengzhou University (2010), and Bachelor’s in Computer Science from Yuncheng University (2007) 🎓. A distinguished Young Pearl River Scholar 🌟, his research focuses on mobile computing, edge intelligence, and AI security 📱🤖🔒. Prof. Wei has published extensively in top journals and conferences, contributing to advancements in algorithm optimization and security techniques 📊📚.

Publication Profile

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Academic Background

Prof. Kaimin Wei 🌟 holds a Ph.D. in Computer Science from Beihang University (2015) 🎓, a Master’s degree from Zhengzhou University (2010) 📚, and a Bachelor’s from Yuncheng University (2007) 🎯. His academic journey showcases dedication and excellence in the field of computer science 💻. Recognized for his outstanding achievements, he was honored as a Young Pearl River Scholar 🌊, reflecting his leadership potential and scholarly impact. Prof. Wei’s contributions to academia continue to inspire, highlighting his commitment to research, innovation, and education 🚀

Research Interests

Prof. Kaimin Wei is a distinguished expert in Mobile Computing 📱, specializing in Edge Intelligence 🌐 and Artificial Intelligence Security 🔐. His research focuses on enhancing the efficiency and security of mobile technologies, leveraging cutting-edge edge intelligence to optimize data processing and real-time decision-making. Prof. Wei’s work in AI security ensures robust protection against emerging cyber threats, contributing to the development of safer, smarter digital ecosystems. His innovative approach bridges the gap between mobile computing and advanced AI applications, driving technological progress and shaping the future of secure, intelligent systems. 🚀🤖

Research Focus

Prof. Kaimin Wei’s research focuses on privacy-preserving technologies, federated learning, mobile crowdsensing, and cybersecurity 🔐📡. His work explores UAV crowdsensing with energy efficiency, gradient inversion attacks in federated learning without prior knowledge, and group task recommendations using neural collaborative approaches 🤖✨. He also investigates secure device pairing through acceleration-based methods with visual tracking and develops robust defense mechanisms against adversarial attacks using feature purification networks 🛡️📊. Prof. Wei’s interdisciplinary research blends Internet of Things (IoT), machine learning, and security protocols to enhance data privacy and system resilience 🌍🔍.

Publication Top Notes

PD-DRL: Towards privacy-preserving and energy-sustainable UAV crowdsensing

GI-SMN: Gradient Inversion Attack Against Federated Learning Without Prior Knowledge

Group Task Recommendation in Mobile Crowdsensing: An Attention-Based Neural Collaborative Approach

Attacks on Acceleration-Based Secure Device Pairing With Automatic Visual Tracking

FePN: A robust feature purification network to defend against adversarial examples

A Survey of Sparse Mobile Crowdsensing: Developments and Opportunities

Automatic Tagging by Leveraging Visual and Annotated Features in Social Media

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

Posted on 22/01/202522/01/2025 by ScienceFather

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

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

Posted on 03/09/202403/09/2024 by ScienceFather

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

Emmanuel Mutabazi | Computer Science and Artificial Intelligence | Best Researcher Award

Posted on 14/08/202414/08/2024 by ScienceFather

Emmanuel Mutabazi | Computer Science and Artificial Intelligence | Best Researcher Award

Mr Emmanuel Mutabazi, Hohai University, China

Based on the information provided, Mr. Emmanuel Mutabazi appears to be a strong candidate for the Best Researcher Award.

Publication profile

google scholar

Education

Mr. Mutabazi is currently pursuing a Ph.D. in Information and Communication Engineering at Hohai University, China, where he has been enrolled since September 2019. He also holds a Master of Engineering in the same field from Hohai University (2016-2019) and a Bachelor of Science in Business Information Technology from the University of Rwanda (2010-2013). His solid educational background has laid a strong foundation for his research endeavors.

Research Interests

Mr. Mutabazi’s research focuses on cutting-edge areas like Natural Language Processing, Machine Learning, Deep Learning, and Computer Vision. His passion for building intelligent systems using AI and ML technologies is evident in his academic and professional work, making him a valuable contributor to these fields.

Skills

He possesses advanced coding skills in multiple programming languages, including Python, MATLAB, C++, Java, and R, among others. His expertise extends to website design, software development, image and video processing, and developing complex systems like Question Answering Systems and Recommender Systems. He is also proficient in using referencing and paper formatting tools such as EndNote, Mendeley, Zotero, and LaTeX.

Experience

Before embarking on his current academic path, Mr. Mutabazi worked as a secondary school teacher at Kiyanza Secondary School (2014-2016), teaching a wide range of subjects. His multilingual abilities (English, French, Swahili, Chinese, and Kinyarwanda) further enhance his capability to engage in global research collaborations.

Publications

Mr. Mutabazi has several peer-reviewed publications, including journal articles and conference papers, showcasing his active participation in research. Notably, his publications include a review on medical textual question-answering systems, a study on SLAM methods, a review of the Marine Predators algorithm, and an improved model for medical forum question classification. His research has been published in reputable journals such as Applied Sciences, Computational Intelligence and Neuroscience, and Machine Learning with Applications.

Conclusion

Considering Mr. Mutabazi’s strong academic background, diverse skill set, significant teaching experience, and impactful research contributions, he is well-suited for the Best Researcher Award. His dedication to advancing knowledge in Information and Communication Engineering, coupled with his proven ability to publish high-quality research, makes him a deserving candidate for this recognition.

Research focus

This researcher focuses on developing advanced deep learning models and algorithms for various applications, particularly in the medical field and computational intelligence. Their work includes creating and improving medical textual question-answering systems and classification models for medical forums using CNN and BiLSTM. Additionally, they explore innovative techniques in marine predator algorithms and direct SLAM methods based on semantic information, highlighting a strong emphasis on machine learning and artificial intelligence in solving complex problems. This research bridges the gap between AI and practical applications in healthcare and robotics. 🤖💡🩺📊

Publication top notes

A review on medical textual question answering systems based on deep learning approaches

Marine predators algorithm: A comprehensive review

An Improved Model for Medical Forum Question Classification Based on CNN and BiLSTM

A variable radius side window direct slam method based on semantic information

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

Posted on 16/07/202416/07/2024 by ScienceFather

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

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

Posted on 13/07/202413/07/2024 by ScienceFather

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. 🌱🐟💻📊

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

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