Mehdi Adibi is a Research Fellow at Monash University's Department of Physiology and the Biomedicine Discovery Institute. He leads the Neurodigit Lab, focusing on neural coding and sensorimotor processing in rodents and humans. Previously, he held NHMRC CJ Martin and ARC DECRA fellowships. He earned his PhD in Neuroscience (2014, UNSW), MSc in Telecommunications Engineering (2008, Iran University of Science and Technology), and BSc in Electrical Engineering (Isfahan University of Technology). His research integrates electrophysiology, optogenetics, and behavioral paradigms to study tactile perception and sensorimotor integration. Key areas include whisker-mediated touch in rodents, cortical dynamics, and translational applications like stroke rehabilitation. Technological innovations include tactile stimulators and modular behavioral setups. He supervises PhD/Masters students and has received awards such as the ARC DECRA Fellowship (2019) and NHMRC CJ Martin Fellowship (2015). Community contributions include CSIRO's Scientists in Schools program and neuroscience outreach.
Stephen H. Lane is a Teaching Professor at the University of Pennsylvania's School of Engineering and Applied Science, Department of Computer and Information Science. He serves as Director of the Computer Graphics and Game Technology (CGGT) Master's Program and teaches courses such as Computer Animation (CIS462/562), Advanced Topics in Computer Graphics and Animation (CIS660), and Game Design and Development (CIS564). He also supervises the Game Design Practicum (CIS568) capstone course. Education: B.S. in Mechanical and Aerospace Engineering from Cornell University (1980) M.S. in Systems Engineering from UCLA (1982) Ph.D. in Mechanical and Aerospace Engineering from Princeton University (1988) Dr. Lane's research focuses on the intersection of robotics, physically-based character animation, embodied intelligent agents, and virtual reality user interfaces. His work integrates control theory, artificial intelligence, and computer animation techniques to develop advanced simulation and training systems. His publications since 1987 cover topics such as inverse kinematics, neural networks for motion control, B-spline receptive fields, robotic skill acquisition, and gesture recognition systems. His recent work (2010-2011) emphasizes sensor fusion for gesture recognition and immersive training interfaces. Scientific Awards: Co-inventor of four US patents related to robotic animation and motion control systems Contributions to hybrid controller hierarchies and neural network training methods As founder of soVoz, Inc., Dr. Lane commercializes behavioral animation technology for virtual environments. His academic-industry collaboration includes contracts with Microsoft, Disney, and the US Army. He has developed tools like ProScena™ to integrate interactive 3D simulation capabilities into gaming and training applications.
Professor Daniele Condorelli is a faculty member in the Department of Economics at the University of Warwick. His research focuses on Microeconomic Theory, Networks and Platforms, and Mechanism Design. He holds a Professor title and is affiliated with the Department of Economics. His work explores topics such as consumer hold-up in ecosystems, data-driven envelopment, and surplus bounds in Cournot competition. His research interests span strategic models of intermediation networks, auction design, and information economics. Notable publications include studies on vertical mergers in digital ecosystems, privacy-policy impacts on data monetization, and optimal mechanism design for market efficiency. Recent articles highlight his contributions to understanding platform competition, resale networks, and algorithmic game theory. His work often intersects with antitrust policy, digital market governance, and incentive design in networked environments. Professor Condorelli advises students in economics and is involved in academic administration, offering office hours by appointment.
A/Professor Dong Ngoduy is the Head of Transport Engineering and an Associate Professor in Transport Engineering at Monash University's Department of Civil and Environmental Engineering. He holds a PhD in Traffic Flow Theory from TU Delft (Netherlands) and an MSc from Linköping University (Sweden). His research focuses on Connected and Autonomous Vehicles (CAVs), Traffic Flow Theory, Data Fusion, and Urban Network Optimization. He received the EPSRC Advanced Fellow Award (2011-2016) and chairs the Connected Traffic Systems Lab. His current work aims to develop smart city platforms for multi-modal transport infrastructure management. Education: MSc in Traffic Engineering, Linköping University PhD in Traffic Flow Theory, Delft University of Technology Research Expertise: Traffic Flow Theory Data Fusion Techniques Urban Network Optimization CAV Dynamics Grants & Awards: EPSRC Advanced Fellow Award (2011-2016) EU Horizon 2020 Project (~$1.2M) Australian Research Council (ARC) Assessor Teaching: Courses include Transport and Traffic Engineering (CIV2282) and Autonomous Vehicle Systems (CIV4100). Labs & Teams: Leads the Connected Traffic Systems Lab and collaborates on projects like Digital Twins for urban networks.
Yan Kyaw Tun is a Tenure Track Assistant Professor in the Department of Electronic Systems at Aalborg University's Technical Faculty of IT and Design, located in Copenhagen, Denmark. His research lies at the intersection of wireless communications, edge computing, and artificial intelligence, with a strong focus on next-generation networks (5G/6G), UAV-assisted systems, and intelligent resource management. His educational background includes a Ph.D. in Computer Engineering from Kyung Hee University, South Korea, where he was awarded the Best Ph.D. Thesis Award in 2021, and a Bachelor of Engineering in Marine Electrical Systems and Electronic Engineering from Myanmar Maritime University. Dr. Tun's research interests span Edge Computing , Multi-Access Edge Computing (MEC) , Resource Allocation , Unmanned Aerial Vehicles (UAVs) , Reinforcement Learning , Energy Efficiency , and Integrated Sensing and Communication (ISAC) . His work leverages AI and optimization techniques to enhance the performance of wireless networks, particularly in space-air-ground integrated systems and satellite-HAP environments. The recent publications highlight a clear trend toward intelligent and sustainable networking: the integration of STAR-RIS (Simultaneously Transmitting and Reflecting Reconfigurable Intelligent Surfaces), Federated Learning for satellite-HAP systems, and AI-driven optimization for UAV trajectories and beamforming. These works are published in high-impact venues such as IEEE Transactions on Mobile Computing and IEEE ICC , showcasing his leadership in cutting-edge communication technologies. His scientific accolades include: IEEE ComSoc Outstanding Young Researcher Award for EMEA Region (2024) Best Ph.D. Thesis Award (2021) Student Best Paper Award at APNOMS 2019 Korea Network Operation and Management Conference Award (2020) Korea Computer Congress 2018 Award Dr. Tun is actively engaged in the academic community as an advisor and grant participant. Though no direct advisees are listed, his involvement in large collaborative projects—evidenced by co-authorship with senior researchers like Prof. Choong Seon Hong—indicates mentorship and team leadership. He has served on the editorial boards of IEEE Internet of Things Journal , IEEE Open Journal of the Communications Society , and IEEE Network , and has secured research support through participation in IEEE-organized workshops and special issues. He is a key organizer of upcoming workshops, including the 'Sustainable AI for Next-Generation Wireless Communications and Networking' at IEEE GLOBECOM 2025 and the 'Digital Twin Networks' workshop at IEEE/CIC International Communications in China 2025, reflecting his role in shaping future research directions in intelligent and green networking.
Wilfried Gansterer is a Professor at the Faculty of Computer Science, University of Vienna, leading the Theory and Applications of Algorithms research group. His work focuses on numerical algorithms, distributed computing, and machine learning, with notable contributions to graph neural networks and fault-tolerant systems. Active in projects such as Algorithmic Data Science for Computational Drug Discovery (2020–2028) and REPEAL (Resilience vs. Performance in Numerical Linear Algebra, 2016–2020). Research Interests: Dr. Gansterer’s expertise spans graph neural networks, matrix compression, adversarial defense mechanisms, and high-performance computing. His work addresses challenges in efficient computation, resilience against node failures, and optimizing distributed systems. Projects : Algorithmic Data Science for Computational Drug Discovery (2020–2028) REPEAL: Resilience vs. Performance in Numerical Linear Algebra (2016–2020) Verteiltes Rechnen (Distributed Computing, 2007–2014) Awards : 2023 Best Paper Award for work on Crossfire: An Elastic Defense Framework for Graph Neural Networks. Labs/Teams : Directs the Theory and Applications of Algorithms group, focusing on algorithmic innovation in distributed and high-performance computing environments.
Dorsa Sadigh is an Associate Professor of Computer Science and Electrical Engineering at Stanford University, and a Senior Fellow at the Stanford Institute for Human-Centered AI. Her work focuses on advancing robotics , particularly in areas such as human-robot collaboration , reinforcement learning , and vision-language models . She explores how robots can learn from human demonstrations, adapt to dynamic environments, and safely interact with humans in caregiving and assistive tasks. Her research interests span autonomous systems , improving robot generalization , and foundation models for robotics . Key projects include developing policies for dexterous manipulation, proactive human-robot teamwork, and scalable data collection methods. She emphasizes ethical considerations in robotics, including perceived safety and human trust. Recent work highlights include the ProVox framework for personalized collaboration, HoMeR for mobile manipulation, and Octo —an open-source generalist robot policy. Her contributions bridge theoretical advances in AI with real-world robotic applications, leveraging large language models and vision-language integration. Dr. Sadigh’s research is funded by grants from NSF, DARPA, and industry partnerships. She collaborates with interdisciplinary teams to address challenges in assistive robotics, autonomous driving, and socially intelligent AI systems.
Hervé Debar is a Professor and head of the Telecommunications Networks and Services (RST) department at Télécom SudParis. His research focuses on network and information system security, including SIEM systems, automated threat mitigation, SDN security, and resilience against cyber attacks. He coordinates major European projects like NECOMA (EU-Japan cybersecurity collaboration) and PANOPTESEC (industrial control systems security). Research interests span SIEM frameworks, intrusion detection, risk management, and defense mechanisms for critical infrastructures. His work emphasizes practical implementation through projects like MASSIF (SIEM decision support systems) and DEMONS (privacy-aware network monitoring). Recent articles address TLS protocol analysis, DDoS mitigation with SDN, honeypot models, and risk assessment for healthcare systems. He supervises multiple PhD students and collaborates with industry partners via CIFRE theses. His research group is part of SAMOVAR (CNRS UMR 5157). Teaching includes leading the Networks and Systems Security master's program, emphasizing hands-on training with industry partnerships. He actively recruits postdocs and engineers for cybersecurity research.
Mohammad Kamrul Hasan is an Associate Professor and Head of the Network and Communication Technology Research Lab at the Center for Cyber Security, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia (UKM). He holds a Ph.D. in Electrical and Communication Engineering from the International Islamic University Malaysia (IIUM) and has over a decade of prior industry experience in communication systems and network design. He has held academic positions at Universiti Malaysia Sarawak and IIUM, and is currently active in research and leadership at UKM. Ph.D. in Engineering (Electrical and Computer Engineering), International Islamic University Malaysia, 2016 M.Sc. in Communication Engineering, International Islamic University Malaysia, 2012 His research focuses on cutting-edge areas in network and communication technologies. Key interests include Wireless Communication and Network Security , Industrial Internet of Things (IIoT) , Cyber-Physical Systems , 5G and Beyond (6G) Networks , Smart Grids , and AI-driven security . He explores machine learning, federated learning, blockchain, and optimization algorithms to enhance network resilience, privacy, and efficiency in critical infrastructure and consumer electronics. His recent publications (2023–2025) demonstrate a strong trend toward intelligent and secure next-generation networks. Topics include intrusion detection in IIoT, passwordless authentication, federated learning for healthcare IoT, 6G security, and digital twins for SCADA systems. His work is frequently published in high-impact IEEE and Springer journals, reflecting a consistent and influential research output. Gold Medal for research excellence Young Scientist Award Fulbright Scholarship (Ministry of Higher Education Malaysia) Senior Member, IEEE (since 2013) Member, Institution of Engineering and Technology (IET) Member, Internet Society Dr. Hasan has served as an editorial member for prestigious journals including IEEE, IET, and Elsevier. He has led funded research projects such as the design of a two-way wireless communication system for medium-voltage electrical networks at Universiti Malaysia Sarawak. He has mentored students and collaborated widely, with co-authors from Malaysia and international institutions. He has also contributed to professional service as Chairperson of the IEEE IIUM Student Branch and as a peer reviewer for over 13 journals including Computer Networks , Internet of Things , and Soft Computing . He leads the Network and Communication Technology Research Lab at UKM, focusing on secure, intelligent, and scalable communication systems for smart cities, industry, and healthcare. His team works on AI-powered intrusion detection, blockchain for critical infrastructure, and privacy-preserving data fusion in IoT environments.
Jennifer Chayes is Dean of the College of Computing, Data Science, and Society and a Professor at the University of California, Berkeley, with appointments in Electrical Engineering and Computer Sciences, Mathematics, Statistics, and Information. She co-founded Microsoft Research New England, New York City, and Montreal, leading interdisciplinary research for 23 years before joining Berkeley in 2020. Previously, she was a Professor of Mathematics at UCLA, where she received the Distinguished Teaching Award. Education PhD in Mathematical Physics (1983), Princeton University BA in Biology and Physics (1979), Wesleyan University Her research spans network science , machine learning , and theoretical computer science , focusing on phase transitions in networks, graphons for large-scale network modeling, and applications in cancer immunotherapy , ethical AI , and climate change . Her work on graph limits and exchangeable graphs has foundational implications for network analysis. Recent publications highlight trends in sparse graph theory , privacy-preserving algorithms , and fairness in AI . Awards include the Anita Borg Institute Women of Vision Leadership Award (2012), SIAM John von Neumann Lecture Prize (2015), and ACM Distinguished Service Award (2020). She is a member of the National Academy of Sciences and a Fellow of multiple academic societies. Chayes actively promotes Diversity in STEM and serves on advisory boards for institutions like MIT’s Schwarzman College of Computing, the Howard Hughes Medical Institute, and the National Science Foundation’s Institute for AI and Fundamental Interactions.
John Basl is an Associate Professor at the Khoury College of Computer Sciences , Northeastern University , with an affiliate appointment in the Department of Philosophy and Religion. His research focuses on the ethics of technology , particularly artificial intelligence , data ethics , and environmental ethics , while bridging moral philosophy and interdisciplinary collaboration. He holds a PhD in Philosophy (2011) from the University of Wisconsin, Madison . His work includes empirical studies on ethics education in computer science and theoretical explorations of machine moral status and automated decision-making . He co-edited the book Designer Biology: The Ethics of Intensively Engineering Biological and Ecological Systems (2013). Recent publications analyze transparency in AI systems (2025, 2023) and the moral implications of synthetic biology (2013). His research also extends to international climate negotiations (2014) and animal ethics (2018). He leads the Northeastern Ethics Institute , promoting interdisciplinary ethical frameworks.
Brian Ziebart is a Professor in the Department of Computer Science at the University of Illinois at Chicago. He earned his Ph.D. in Machine Learning from Carnegie Mellon University in 2010. Research Interests: Machine Learning, Robotics, Assistive Technologies, Human-Computer Interaction, Adversarial Prediction, Inverse Optimal Control, Structured Prediction. Key Grants: NSF CAREER (RI)-1652530, NSF EAGER (SCH)-1650900, NSF IIS-1526379, NSF III-1514126, Future of Life Institute grant, NSF NRI-1227495. Notable Awards: Best Paper Runner-Up (ECCV, 2012), Best Paper Award (ICML, 2011), CMU School of Computer Science Dissertation Honorable Mention (2011). Teaching & Leadership: Senior Lecturer at CMU, actively involved in mentoring students and leading research teams.
Noah Gans is the Anheuser-Busch Professor of Management Science at the Wharton School of the University of Pennsylvania, where he serves as Professor in the Operations, Information and Decisions department. His research focuses on service operations with particular emphasis on call center management, stochastic processes, and queueing system control. Department Editor, Stochastic Models and Simulation at Management Science President of Manufacturing and Service Operations Management Society (MSOM) PhD Program Coordinator for the OID Department His academic work spans diverse domains including healthcare technology pricing, container inspection security, workforce optimization, and revenue management. He has pioneered adaptive clinical trial designs and developed novel models for customer demand sensitivity in overbooking scenarios. Key research areas include: Bayesian sequential learning for multi-arm clinical trials Value-based pricing under uncertainty Stochastic control in service systems Security policy analysis for global supply chains Risk-sharing mechanisms in healthcare Scientific honors include NSF CAREER Award (1998), INFORMS George E. Nicholson Prize (1995), and multiple teaching awards from the Wharton MBA program (2004, 2010-2011, 1997-2001). His publications bridge theoretical operations research with practical implementation across healthcare, transportation, and service industries.
Steven O. Kimbrough is a Professor of Operations, Information and Decisions at the Wharton School, University of Pennsylvania. His research spans artificial intelligence, computational rationality, and strategic optimization with applications to political science, economics, and service innovation. He teaches courses like Agents, Games, and Evolution and Thinking With Models , focusing on experimental approaches to bounded rationality and uncertainty in decision-making. Primary Email: kimbrough@wharton.upenn.edu Office: 3730 Walnut Street, 565 Jon M. Huntsman Hall, Philadelphia, PA 19104 His research interests include: Artificial intelligence and metaheuristics for constrained optimization Evolutionary computation in electoral redistricting Agent-based modeling of market dynamics Logic modeling for normative reasoning Text mining applications in event analysis Publications demonstrate expertise in computational economics, political modeling, and service analytics. Recent work focuses on: Empirical validation of electoral compactness Strategic learning in oligopolies Multi-objective matching algorithms Feasible-infeasible solution spaces Service network optimization Teaching emphasizes: Game-theoretic approaches to strategic behavior Modeling life-cycle for energy sustainability Computational experiments in social science
Henning Piezunka is an Associate Professor of Management at The Wharton School, University of Pennsylvania. He holds a PhD from Stanford University, a Master of Science from the London School of Economics, and a Diploma Kaufmann from the University of Mannheim. Before academia, he co-founded and led a web design company for 18 years, growing it to 30+ employees serving 80+ countries before its sale in 2016. His research examines: Competition and collaboration dynamics in entrepreneurial firms, family businesses, and sports contexts Crowdsourcing innovation and platform strategies Organizational decision-making structures and learning processes CEO succession planning and its organizational impacts His recent publications (2019-2025) demonstrate methodological diversity, combining archival analysis of Formula One/soccer data, crowdsourcing platform experiments, and organizational case studies. Key thematic focuses include: how competition manifests in collaborative settings, AI's role in strategic learning, and how organizational structures shape individual behavior. Awards & Honors: Wharton Teaching Excellence Award (2023) Emerging Scholar Award, TIM Division, Academy of Management (2022) Poets & Quants Best 40 Under 40 Professor (2019) Multiple teaching commendations for MBA/EMBA courses (2014-2023) He teaches core entrepreneurship courses including MGMT2300 (Entrepreneurship) and MGMT2310 (Entrepreneurship Launchpad), focusing on venture creation, resource acquisition, and scaling strategies. He also leads doctoral seminars on research design and maintains an active advisory practice through the 'Between the Lines' webinar series featuring business school authors.
