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. ๐Ÿ”ฌ๐Ÿค–๐Ÿ“š

Publication profile

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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. ๐Ÿค–๐Ÿ“Š๐Ÿ”

Publication top notes

Shannon Holes, Black Holes, and Knowledge: The Essential Tension for Autonomous Humanโ€“Machine Teams Facing Uncertainty

A Quantum-like Model of Interdependence for Embodied Humanโ€“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. ๐Ÿ“š๐Ÿค–๐Ÿ’ป๐ŸŒ

Publication profile

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Education

๐Ÿ“š From September 1968 to June 1974, completed secondary education, earning a Certificate of High School Graduation in Science. ๐ŸŽ“ 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. ๐Ÿ“œ From February to June 1983, obtained a Certificate of Educational Studies from PATES of SELETE, Greece. ๐Ÿ“– Achieved a Bachelor in Theology from the University of Athens, completed between October 1979 and December 1987. ๐ŸŽ“ 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. ๐Ÿง  Thesis: “Integrating Logic and Objects for Knowledge Representation and Reasoning.”

Experience

๐Ÿ“˜ 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. ๐ŸŽ“๐Ÿ”ฌ

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. ๐ŸŒ๐Ÿ“š๐Ÿ’ป๐ŸŽ“

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. ๐ŸŒฑ๐ŸŸ๐Ÿ’ป๐Ÿ“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