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[\/et_pb_text][et_pb_divider _builder_version=”4.16″ global_colors_info=”{}”][\/et_pb_divider][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=”1_3,2_3″ _builder_version=”4.24.2″ _module_preset=”default” global_colors_info=”{}”][et_pb_column type=”1_3″ _builder_version=”4.21.0″ _module_preset=”default” global_colors_info=”{}”][et_pb_image src=”https:\/\/cyprusconferences.org\/iceccs2024\/wp-content\/uploads\/2024\/04\/691.jpg” title_text=”691″ _builder_version=”4.24.2″ _module_preset=”default” global_colors_info=”{}”][\/et_pb_image][\/et_pb_column][et_pb_column type=”2_3″ _builder_version=”4.21.0″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.24.2″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n
Professor and Director of CaSToRC \u2013 The Cyprus Institute\u00a0<\/a><\/em> Title:<\/strong> Emergence and evolution of hierarchical structure in complex systems<\/p>\n Abstract:<\/strong> It is well known that many complex systems, both in technology and nature, exhibit hierarchical modularity: simple and general modules, each of them providing a certain function, are used within more complex modules that perform more sophisticated functions. This is the case for instance with protocol stacks in computer networking. What is not well understood however is how this hierarchical structure (which is fundamentally a network property) emerges, and how it evolves over time. We propose a modeling framework, called Evo-Lexis, that provides insight to some fundamental questions about evolving hierarchical systems. We show that deep hierarchies emerge when the population of top-layer modules evolves through tinkering and mutation. Strong selection on the cost of new top-layer modules results in reuse of more complex (longer) nodes in an optimized hierarchy. The bias towards reuse of complex nodes results in an \u201chourglass architecture\u201d (i.e., few intermediate nodes that cover almost all source\u2013target paths). With such bias, the core nodes are conserved for relatively long time periods although still being vulnerable to major transitions and punctuated equilibria. Finally, we analyze the differences in terms of cost and structure between incrementally designed hierarchies and the corresponding \u201cclean-slate\u201d hierarchies which result when the system is designed from scratch after a change<\/p>\n Bio <\/strong>Dr. Constantine Dovrolis is the Director of the center for Computational Science and Technology (CaSToRC) at The Cyprus Institute (CyI) as of 1\/1\/2023. He is also a Professor at the School of Computer Science at the Georgia Institute of Technology (Georgia Tech). He is a graduate of the Technical University of Crete (Engr.Dipl. 1995), University of Rochester (M.S. 1996), and University of Wisconsin-Madison (Ph.D. 2000).<\/p>\n His research is highly inter-disciplinary, combining\u00a0Network Theory, Data Mining and Machine Learning.<\/strong>\u00a0Together with his collaborators and students, they have published in a wide range of scientific disciplines, including\u00a0climate science, biology, and neuroscience<\/strong>. More recently, his group has been focusing on\u00a0neuro-inspired architectures for machine learning<\/strong> based on what is currently known about the structure and function of brain networks.Read More<\/a><\/span>\n According to Google Scholar, his publications have received more than 15,000 citations with an h-index of 56. His research has been sponsored by US agencies such as NSF, NIH, DOE, DARPA, and by companies such as Google, Microsoft and Cisco. He has published at diverse peer-reviewed conference and journals such as the International Conference on Machine Learning (ICML), the ACM SIGKDD conference, PLOS Computational Biology, Network Neuroscience, Climate Dynamics, the Journal of Computational Social Networks, and others.<\/div><\/p>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row column_structure=”1_3,2_3″ _builder_version=”4.24.2″ _module_preset=”default” global_colors_info=”{}”][et_pb_column type=”1_3″ _builder_version=”4.21.0″ _module_preset=”default” global_colors_info=”{}”][et_pb_image src=”https:\/\/cyprusconferences.org\/iceccs2024\/wp-content\/uploads\/2024\/05\/New-Project-2-1.png” title_text=”New-Project-2 (1)” _builder_version=”4.25.0″ _module_preset=”default” hover_enabled=”0″ global_colors_info=”{}” sticky_enabled=”0″][\/et_pb_image][\/et_pb_column][et_pb_column type=”2_3″ _builder_version=”4.21.0″ _module_preset=”default” global_colors_info=”{}”][et_pb_text _builder_version=”4.24.2″ _module_preset=”default” global_colors_info=”{}”]<\/p>\n University of Cyprus<\/em> Title:<\/strong> Intelligent Transportation Systems: A Large-Scale and Complex Cyber-physical System<\/p>\n Abstract:<\/strong> Transportation systems have always been a complex system with many agents (vehicles) interacting on the road network. Historically, a huge problem of these systems has been congestion with all its adverse effects: waste of time and energy, green-house emissions, accidents, and frustration. The emergence of autonomous and connected vehicles promises to solve these problems, however, they cannot solve the problem unless there is also paradigm shift from \u201cselfish\u201d driving to a more \u201csocial\u201d driving. During this talk, we will address some of the problems associated with congestion and present innovative solution approaches that are based on route reservation architecture aimed not only at alleviating congestion but also at enhancing the overall efficiency of the road network in terms of the average time vehicles spend within it.<\/p>\n Bio: <\/strong>Christos Panayiotou is a Professor with the Electrical and Computer Engineering (ECE) Department at the University of Cyprus (UCY). He is also the Deputy Director of the KIOS Research and Innovation Center of Excellence for which he is also a founding member. Christos has received a B.Sc. and a Ph.D. degree in Electrical and Computer Engineering from the University of Massachusetts at Amherst, in 1994 and 1999 respectively. He also received an MBA from the Isenberg School of Management, at the aforementioned university in 1999. Before joining the University of Cyprus in 2002, he was a Research Associate at the Center for Information and System Engineering (CISE) and the Manufacturing Engineering Department at Boston University (1999 – 2002). His research interests include modeling, control, optimization and performance evaluation of discrete event and hybrid systems, intelligent transportation systems, cyber-physical systems, event detection and localization, fault diagnosis, machine learning, wireless, ad hoc and sensor networks, resource allocation, and intelligent buildings. His research has been funded with more than 45 million euros from national and European funding agencies, governmental organizations and private companies. Read More<\/a><\/span>\n [\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":" Keynote SpeakersConstantine Dovrolis Professor and Director of CaSToRC \u2013 The Cyprus Institute\u00a0 Title: Emergence and evolution of hierarchical structure in complex systems Abstract: It is well known that many complex systems, both in technology and nature, exhibit hierarchical modularity: simple and general modules, each of them providing a certain function, are used within more complex modules that perform more sophisticated functions. This is the case for instance with protocol stacks in computer networking. What is not well understood however is how this hierarchical structure (which is fundamentally a network property) emerges, and how it evolves over time. We propose a modeling framework, called Evo-Lexis, that provides insight to some fundamental questions about evolving hierarchical systems. We show that deep hierarchies emerge when the population of top-layer modules evolves through tinkering and mutation. Strong selection on the cost of new top-layer modules results in reuse of more complex (longer) nodes in an optimized hierarchy. The bias towards reuse of complex nodes results in an \u201chourglass architecture\u201d (i.e., few intermediate nodes that cover almost all source\u2013target paths). With such bias, the core nodes are conserved for relatively long time periods although still being vulnerable to major transitions and punctuated equilibria. 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<\/strong><\/p>\nChristos Panayiotou<\/h3>\n
<\/strong><\/p>\n
Christos has published more than 340 papers in international refereed journals and conferences and is the recipient of the 2014 Best Paper Award for the journal Building and Environment (Elsevier). His students and research team have received a number of distinctions and awards, including the First Prize in the Competition \u201cCooperative Aerial Robots Inspection Challenge\u201d during the 62nd IEEE Conference on Decision and Control (CDC2023). He is an Associate Editor for the IEEE Transactions of Intelligent Transportation Systems, and the Journal of Discrete Event Dynamical Systems. He had a long tenure on the Conference Editorial Board of the IEEE Control Systems Society (2001-2023) and served as an Associate Editor of the IEEE Transactions on Control Systems Technology during 2016-2020 and of the European Journal of Control during 2014-2021. He held several positions in organizing committees and technical program committees of numerous international conferences, including General Chair of the 31st Mediterranean Conference on Control and Automation (MED2023), General Chair of the 23rd European Working Group on Transportation (EWGT2020), and General Co-Chair of the 2018 European Control Conference (ECC2018). He has also served as Chair of various subcommittees of the Education Committee of the IEEE Computational Intelligence Society.<\/div>
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