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. πŸŒŸπŸŽ“πŸ’Ό

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Academic Qualifications

Dr.Β  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 πŸŽ“πŸ“š. 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 πŸ“˜πŸ’‘. Additionally, they graduated with distinction in Computer Science from the University of Minnesota, Twin Cities, USA (1993) πŸŽ“πŸ’».

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) πŸ’», and a Consultant at the Microcomputer Laboratory, University of Minnesota (Sep 1991 – Mar 1993) πŸ“Š. Since Sep 2003, they have been a Lecturer at CPCE, PolyU πŸ“š, and previously held roles as a Lecturer (Sep 1998 – Aug 2000) πŸ‘¨β€πŸ«, Demonstrator (Sep 1996 – Aug 1998) πŸ”¬, and Research Student (Jun 1994 – Jun 1996) πŸŽ“ 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 πŸŽ‰πŸ“š. I have successfully led and contributed to various high-impact projects, including those funded by the Quality Education Fund and CPCE πŸ†πŸ’‘. My roles have ranged from Associate Academic Director to Co-Investigator and Consultant, focusing on innovative technologies like AI, blockchain, and machine learning πŸ€–πŸ”—. 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 πŸŽ“πŸ’Ό.

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. πŸŒπŸ“¦πŸ”—πŸ“ŠπŸŒΏ

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. πŸ”¬πŸ€–πŸ“š

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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. πŸ€–πŸ“ŠπŸ”

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. πŸ“šπŸ€–πŸ’»πŸŒ

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Education

πŸ“š From September 1968 to June 1974, completed secondary education, earning a Certificate of High School Graduation in Science. πŸŽ“ 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. πŸ“œ From February to June 1983, obtained a Certificate of Educational Studies from PATES of SELETE, Greece. πŸ“– Achieved a Bachelor in Theology from the University of Athens, completed between October 1979 and December 1987. πŸŽ“ 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

πŸ“˜ 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. πŸŽ“πŸ”¬

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. πŸŒπŸ“šπŸ’»πŸŽ“

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. πŸŒ±πŸŸπŸ’»πŸ“Š

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