Sinem Coleri
Bio: Sinem Coleri is a Professor in the Department of Electrical and Electronics Engineering at Koc University. She is also the founding director of Wireless Networks Laboratory (WNL) and director of Ford Otosan Automotive Technologies Laboratory. Sinem Coleri received the BS degree in electrical and electronics engineering from Bilkent University in 2000, the M.S. and Ph.D. degrees in electrical engineering and computer sciences from University of California Berkeley in 2002 and 2005. She worked as a research scientist in Wireless Sensor Networks Berkeley Lab under sponsorship of Pirelli and Telecom Italia from 2006 to 2009. Since September 2009, she has been a faculty member in the department of Electrical and Electronics Engineering at Koc University. Her research interests are in 6G wireless communication systems and networking, machine learning for wireless networks, machine-to-machine communications, wireless networked control systems and vehicular networks.Dr. Coleri currently holds the position of Editor-in-Chief at the IEEE Open Journal of the Communications Society. Dr. Coleri is an IEEE Fellow, AAIA Fellow and IEEE ComSoc Distinguished Lecturer.
Title: AI Based Ultra-Reliable Wireless Networked Control Systems in 6G
Abstract: Unlike previous generations of networks, which were primarily designed to meet the requirements of human communications, 5G networks enable the collection of data from the machines as well. As per the Ericsson Mobility Report, the estimated number of connected devices is projected to reach 26 billion in 2026. Looking forward to 6G systems, the focus shifts towards leveraging this data for a new spectrum of control applications, including extended reality, remote surgery and autonomous vehicle platoons. Designing communication systems for these control applications poses unique challenges. It requires meeting stringent requirements for delay and reliability, addressing the semantics of control systems and ensuring robust resource management. In the first part of this talk, we delve into ultra-reliable channel modeling and communication techniques based on extreme value theory and generative artificial intelligence (AI). Generative AI enables predicting the channel parameters with higher accuracy while incorporating various system inputs and providing adaptivity to dynamic scenarios. In the second part of the talk, we explore the benefits of employing optimization theory based, explainable and safe AI in radio resource management for the joint design of control and communication systems in 6G networks. These approaches offer a systematic methodology to enhance robustness and interpret decisions made by black-box AI models.
Prof. Tufan Kumbasar
Artificial Intelligence and Intelligent Systems (AI2S) Laboratory, Istanbul Technical University, Türkiye
Bio: TUFAN KUMBASAR received B.Sc., M.Sc., and Ph.D. degrees in Control and Automation Engineering from Istanbul Technical University. He is currently a Professor and the director of Artificial Intelligence and Intelligent Systems (AI2S) Laboratory, Faculty of Electrical and Electronics Engineering, Istanbul Technical University.
He has currently authored more than 150 papers in international conferences, journals, and books. His major research interests are in artificial and computational intelligence, notably type-2 fuzzy logic, fuzzy control, neural networks, intelligent systems, robotics, and machine learning. He has served as a Publication Co-Chair, Panel Session Co-Chair, Special Session Co-Chair and PC, IPC, and TPC in various conferences. Dr. Kumbasar is currently an Associate Editor for the IEEE Transactions on Fuzzy Systems and an Area Editor for the International Journal of Approximate Reasoning.
Dr. Kumbasar received the Best Paper Awards from the IEEE International Conference on Fuzzy Systems in 2015 and the 6th International Conference on Control Engineering & Information Technology in 2018. He is the recipient of the ODTÜ Mustafa N. Parlar Research and Education Foundation Research Incentive Award in 2020, the Turkish Academy of Sciences Outstanding Young Scientists Award in 2021, the Istanbul Technical University Young Scientists Achievement Award in 2022, the Science Academy Young Scientist Award in 2023 and the IEEE Turkey Research Incentive Award in 2023.
Abstract: This talk explores the design of Artificial Intelligence (AI) methodologies, specifically deep learning and fuzzy logic systems, for various engineering problems through an analogy between intelligent systems and RLC circuits. In this context, we examine how AI-driven design, characterized by autonomy, flexibility, and high accuracy, can be represented via reasoning, learning, and control. Highlighting successful applications in various domains, I demonstrate the significant potential of AI-driven design approaches to enhance efficiency and reliability in developing intelligent systems. My talk will also showcase various successful applications of intelligent systems with real-time settings such as in UAVs, computer games, robotics, pursuit-evasion games, and autonomous vehicles. The presented experimental results underscore the solutions that AI-driven design can offer for complex engineering challenges. Finally, I will point out some future research topics related to intelligent systems.\
Kostas Karpouzis
Bio: Kostas Karpouzis is an Assistant Professor at the Department of Communication, Media and Culture. In his research, he’s looking for ways to make computer systems more aware of and responsive to the way people interact with each other. He is also investigating how gamification and digital games can be used in classroom and informal settings to assist conventional teaching and help teach social issues and STEAM subjects to children and adults. Since 1998, he has participated in more than twenty research projects funded by Greek and European bodies; most notably the Humaine Network of Excellence, leading research efforts in emotion modelling and recognition, the FP6 IP CALLAS project, where he served as Area Leader of Affective applications, the FP7 TeL Siren project (Technical Manager), which was voted Best Learning Game in Europe for 2013 by the Games and Learning Alliance Network of Excellence, the H2020 iRead project, which produced Navigo, the winner of the GALA Serious Games competition for 2018 and the H2020 ECoWeB project which builds engaging and personalized mobile applications to promote emotional wellbeing and prevent mental health problems in adolescents and young adults.
He is a member of the BoD for the gi-Cluster of Corallia, which consists of industrial and academic members of the game and creative ecosystem in Greece, a member of the Hellenic Bioethics and Technoethics committee and Chairman of the Board of the Hellenic Association of Computer Engineers. He co-edited a book on “Emotion in Games: Theory and Practice” published by Springer in late 2016. Besides this, he is involved in a number of science communication activities, most notably Famelab Greece and openscience.gr. He’s also an advocate for technology and CS in primary schools, participating in the Girls Go Coding initiative and serving as an Ambassador of EU Code Week in Greece (until 2018). He has participated as a speaker in 3 TEDx events, including TEDxAthens in 2019, while in 2016, he authored a lesson on the TED-ed platform titled “Can machines read your emotions?”; the lesson surpassed 300.000 views in its first week.
Abstract: This talk examines the impact of Artificial Intelligence (AI) on research ethics, exploring both the challenges and opportunities presented in academic contexts. AI, as a subject of research ethics, creates a number of challenges faced by Institutional Review Boards in evaluating research proposals; this talk elaborates on the influence of AI on data collection and analysis, discussing privacy concerns and the implications of regulations such as GDPR and the EU AI Act. In addition, we explore the ethical dimensions of AI-generated content in academic research, including literature reviews and meta-analyses, as well as in peer review and publication processes. Finally, we examine future directions and regulatory challenges, emphasizing the need for adaptive ethical frameworks and highlighting the balance between leveraging AI’s potential to enhance research capabilities and the need to uphold ethical standards and human values in academic inquiry.
