Prof. Dr. Loizos Michael
Title: Human-Centered AI through Machine Coaching
The availability of vast amounts of data made possible by the Internet of Things, and the demonstrable ability of modern Machine Learning techniques to solve problems across diverse domains, might suggest that the AI problem is all but solved. But the currently trending data-driven solutions to AI have largely kept humans out of the loop, practically diminishing their role to that of data annotators. Not only has this approach failed to utilize the full potential of what humans have to offer in building smart machines, but it has also led to the inadvertent propagation of human biases into machines. A considerably more interactive form of machine learning, where humans actively engage with, and personalize, a machine, has the potential to address both shortcomings. This talk presents machine coaching, a human-machine interaction paradigm according to which the end user enters into a dialogue with the machine and acts as the machine’s coach. During a coaching session, the machine makes a prediction or takes an action in a certain context, and, if prompted, offers an argument in support of its decision. If not convinced by the argument, the end user may offer a counter-argument in support of what decision the user thinks the machine should have reached. Using formal argumentation as the underlying language for knowledge representation and reasoning, and adopting the probably approximately correct semantics for learning, we show how machine coaching can naturally support human-machine interactions that are cognitively compatible, while also being accompanied by quantifiable guarantees on their efficacy and efficiency.
Dr. Loizos Michael is an Associate Professor at Open University of Cyprus, where he founded and directs the Computational Cognition Lab, while also serving as the academic head of the cross-institutional M.Sc. Program in Cognitive Systems. He is a founding member of the Research Center of Excellence RISE, within which he leads the research pillar on Artificial Intelligence and Communications. His research focuses on the development of formal computational models for cognitive processes associated with individual or collective intelligence, drawing inspiration and using techniques from the research areas of computational learning theory, symbolic knowledge representation, and commonsense reasoning.
He received a B.Sc. in Computer Science with a minor degree in Mathematics from University of Cyprus, graduating top of the class of 2002, and receiving the Republic of Cyprus Presidential Award. He continued his education at Harvard University, where he received an M.Sc. and a Ph.D. in Computer Science (Artificial Intelligence) in 2008, under the supervision of Leslie Valiant. Before joining Open University of Cyprus in 2009, he held a visiting faculty appointment at University of Cyprus. Among others, he served as the PC chair of the 15th European Conference on Logics in Artificial Intelligence in 2016, and he has been organizing a workshop series on Cognitive Knowledge Acquisition since 2015.
Prof. Dr.Stelios Timotheou
Title: Ambient Intelligence in Intelligent Transportation Systems
Traffic congestion causes several adverse effects that lower our quality-of-life, harm the environment and negatively impact the economy. Intelligent transportation systems promise to alleviate congestion by employing information and communication technologies, while the emergence of connected and automated vehicles is expected to enhance safety and user convenience. Despite these advancements, maximization of the social, economic and environmental traffic-related benefits can only be achieved if different users (e.g. car-travellers, cyclists, pedestrians), are intelligently integrated in the ambient environment. This talk will discuss how ambient intelligence in intelligent transportation systems can enhance the experience and safety of different users and investigate the impact of user collaboration towards socially optimal operation of the traffic network. In this context, a novel traffic management architecture will be introduced that decomposes the road infrastructure in the spatial and temporal domains and makes appropriate route reservations for each vehicle to maximize traveller convenience and network efficiency. This is achieved by routing vehicles through congestion-free paths and advising travellers to wait at their origin prior to departure.
Stelios Timotheou is an Assistant Professor at the Department of Electrical and Computer Engineering and a faculty member at the KIOS Research and Innovation Center of Excellence, of the University of Cyprus. He holds a Dipl.-Ing. from the Electrical and Computer Engineering School of the National Technical University of Athens, and M.Sc. and Ph.D. diplomas from the Electrical and Electronic Engineering Department of Imperial College London. In previous appointments, he was a Research Associate at KIOS, a Visiting Lecturer at the Department of Electrical and Computer Engineering of the University of Cyprus, and a Postdoctoral Researcher at the Computer Laboratory of the University of Cambridge. His research focuses on analysing data and making informed decisions in challenging environments, with the purpose of enhancing efficiency and delivering new capabilities in situational awareness and decision making. Towards this direction, he develops customised, real-time, distributed and cooperative methodologies and algorithms, drawing on theory from mathematical optimization, machine learning, statistical data processing and computational intelligence. The main application area of his research is critical infrastructure systems, with emphasis on intelligent transportation systems and wireless communications. Dr. Timotheou is the recipient of the 2017 ‘Cyprus Young Researcher in Physical Sciences & Engineering’ Award, by the Cyprus Research Promotion Foundation. He is a member of ACM and a Senior Member of IEEE