Dr. Michael Mühlebach is a Lecturer at the Department of Information Technology and Electrical Engineering, ETH Zurich, and affiliated with the Max Planck Institute for Intelligent Systems in Tübingen, Germany. He holds a Bachelor's (2010) and Master's (2013) from ETH Zurich, recognized with awards for academic excellence in Robotics, Systems, and Control. His research focuses on multibody dynamics, nonlinear system control, and model predictive control, with applications in robotics and aerospace systems. His work spans theoretical advancements in variational integrators and practical implementations in systems like the Cubli (a reaction wheel-based 3D inverted pendulum) and flying platforms for ducted fan actuation. Publications highlight contributions to model predictive control schemes with stability guarantees, nonlinear analysis, and distributed event-based state estimation. Key awards include the Outstanding D-MAVT Bachelor Award and Willi-Studer Prize. His research integrates control theory with real-world applications, emphasizing both foundational mathematics and engineering implementations. No grants or lab affiliations are explicitly listed in the provided text.
Marta Kwiatkowska is a Professor of Computing Systems at the University of Oxford and a Fellow of Trinity College. Her research focuses on probabilistic verification , quantitative model checking , and formal methods for complex systems including autonomous robots, medical devices, and biological systems. She leads the development of the PRISM and PRISM-games probabilistic model checkers. Key research areas: Probabilistic systems, formal verification, autonomous robotics, medical device analysis, systems biology Grants: ERC Advanced Grant VERIWARE, EPSRC Programme Grant Mobile Autonomy Awards: 2024 ETAPS Test-of-Time Tool Award for PRISM Students: Current and former advisees in topics spanning formal methods, robotics, and quantitative verification The PRISM-games extension enables verification of stochastic multi-player games with applications in network protocols, autonomous systems, and game theory. Her work bridges theory, algorithms, and practical implementation, with real-world applications in ubiquitous computing and nanotechnology.
Lam James is a Chair Professor of Control Engineering at the University of Hong Kong (HKU), affiliated with the Faculty of Engineering. He holds a BSc (1st Hons.) in Mechanical Engineering from the University of Manchester, and MPhil/PhD degrees from the University of Cambridge. His academic journey includes roles as a Croucher Fellow, Lecturer at the University of Melbourne, and faculty member at City University of Hong Kong before joining HKU in 1993. Professor Lam serves as Editor-in-Chief for four international journals including IET Control Theory and Applications and Journal of The Franklin Institute . His research focuses on networked control systems, vibration control, control theory, and multi-agent systems. With 600+ peer-reviewed publications, he maintains an H-index of 102 (Web of Science) and 108 (Scopus), recognized as a Highly Cited Researcher in multiple fields. Education: BSc Manchester (Mechanical Engineering), MPhil/PhD Cambridge Editorial Roles: 20+ journals, including leadership roles since 2012 His awards include Foreign Membership of Academia Europaea (2024), National Academy of Artificial Intelligence membership (2025), and two State Natural Science Awards (2015, 2019). He is a Fellow of multiple institutions including IEEE, IMechE, and HKIE.
John Baillieul is Distinguished Professor at Boston University with joint appointments in Mechanical Engineering, Systems Engineering and Electrical & Computer Engineering. He directs experimental laboratories for real-time control of lightweight robotic systems and applies nonlinear control theory to complex multi-body, networked, and bio-inspired systems. Education: Ph.D., Harvard University Research Interests: Baillieul’s work spans robotics, nonlinear control, and networked systems. Early contributions resolved motion-planning for kinematically redundant manipulators; current themes include neuromimetic learning, vision-based navigation, and resilience of infrastructure networks such as power grids. His group couples rigorous geometric control with real-time hardware to create lightweight, high-performance robots and to uncover fundamental information limits in feedback systems. Recent Publication Trends (2021-2025): Over the past five years his output has concentrated on three synergistic directions: (i) neuromimetic and Koopman-based data-driven methods for estimating and controlling nonlinear systems, (ii) vision-based guidance and sparse optical-flow primitives for agile autonomous flight, and (iii) network-theoretic decomposition and information-rate studies for resilient operation of power grids and collective dynamics. Honors & Awards: IEEE Fellow 2025 Roger W. Brockett Control Systems Award Former Editor-in-Chief, IEEE Transactions on Automatic Control Affiliations & Service: He is a member of Boston University’s Center for Information and Systems Engineering (CISE), has served as Editor-in-Chief of IEEE Transactions on Automatic Control, and remains active in editorial and organizational roles across the IEEE control systems community.
Antonia Holzapfel is a doctoral researcher at the Institute for Data Science in Mechanical Engineering (DSME) of RWTH Aachen University. Supervised by Prof. Sebastian Trimpe, her work focuses on safe and explainable machine learning (XAI) for robotics and time-series modeling, with applications in mechanical engineering and medical technology. Bachelor's in Mechanical Engineering (Design Engineering specialization) Master's in General Mechanical Engineering (Simulation Technology and Medical Technology specializations) Her research addresses safety in learning processes , including Bayesian optimization for quadcopters and concept extraction for model interpretability. Her Friedrich-Wilhelm Award -winning thesis (2024) explored safe online learning in time-varying environments, presented at the L4DC conference. She contributes to DFG-funded projects on data-driven process modeling in forming technology. Key scientific contributions include: Advancing safe Bayesian optimization for autonomous systems Developing explainable AI methods for time-series analysis Improving model robustness through internal representation patterns Scientific awards: Friedrich-Wilhelm Award for outstanding Master's thesis (2024) Antonia's work bridges machine learning safety with practical applications in robotics and industrial processes.
Professor Yan (Lindsay) Sun is a faculty member at the University of Rhode Island in the College of Engineering under the Department of Electrical, Computer and Biomedical Engineering . She is the founding director of the Center for Cyber-Physical Intelligence and Security (CYPHER) and an IEEE Fellow . Her research focuses on cyber-physical systems security , power grid security , network security , and trustworthy social computing , with a particular emphasis on trust modeling and management in complex systems. Her publications span smart grid security , microgrid control , machine learning applications in power systems, and blockchain-based security mechanisms . The work often explores adversarial threats , resilient control strategies , and data augmentation techniques for improved grid monitoring. NSF CAREER Award (2007) IET Wireless Sensor Systems Premium Award (2018) EURASIP Best Paper Award (2015) IEEE Fellow (2019) URI College of Engineering Outstanding Research Award (2022) She actively leads interdisciplinary CYPHER Lab initiatives involving cyber-physical system resilience , network security , and smart grid analysis , collaborating with government and industry partners.
Professor Marta Zofia Kwiatkowska is Professor of Computing Systems and Fellow of Trinity College at the University of Oxford, where she has held a faculty position since 2007. She previously served as Professor of Computer Science at the University of Birmingham (2001–2007), Reader and Lecturer at the University of Birmingham (1994–2001), and Lecturer at the University of Leicester (1986–1994). Her academic career began as Assistant Professor at the Jagiellonian University in Kraków, Poland (1980–1988). Education: BSc/MSc in Computer Science, Jagiellonian University, Kraków MA, University of Oxford PhD, University of Leicester Research Interests: Professor Kwiatkowska spearheaded the development of probabilistic and quantitative verification methods on the international stage. Her work bridges theory and practice through the PRISM model checker—the leading software tool in probabilistic model checking—used worldwide for research and teaching. Application domains include communication and security protocols , nanotechnology designs , power management , ubiquitous computing and systems biology . She investigates automated verification , temporal logics , semantic models for concurrency , real-time systems , and biological process modelling . Current grant funding exceeds £3.7 million from EPSRC, EU and ERC, including the prestigious ERC Advanced Grant VERIWARE. Scientific Awards & Honours: Fellow of the Royal Society Fellow of the ACM Fellow of the European Association for Theoretical Computer Science (EATCS) Fellow of the British Computer Society (BCS) Fellow of the Polish Society of Arts & Sciences Abroad ERC Advanced Grant VERIWARE (€2.046 M, 2010–2015) Top Cited Article Award, Theoretical Computer Science (2005–2010) Best Paper Award, QEST 2006 Doctoral Supervision & Grants: Professor Kwiatkowska actively supervises doctoral students (D.Phil. at Oxford) and post-doctoral researchers. She welcomes applications in areas aligned with her research interests, detailed here . Current students include Charlie Griffin, Daqian Shao, Matthew Yuan and Minghao Liu; past students and researchers number over twenty, many now in faculty or industry leadership roles. Laboratory & Teams: She leads the Oxford Quantitative Verification group within the Department of Computer Science. Ongoing projects include FUN2MODEL, ELSA, FAIR and the flagship PRISM probabilistic model checker. The group maintains strong collaborations with biological, robotics and engineering teams worldwide.
Tamer Başar is a Maybelle Leland Swanlund Endowed Chair Emeritus and Professor Emeritus of Electrical and Computer Engineering at the University of Illinois' College of Engineering. He leads research in game theory, control systems, and networked systems through the Coordinated Science Lab. His work focuses on stochastic processes, multi-agent systems, and optimization under uncertainty. Research interests include Nash equilibrium analysis, mean-field theory, and reinforcement learning applications in dynamic systems. Recent publications explore strategic incentives in large population games, nonstationary reinforcement learning, and coupled bi-virus models. Notable honors include the IEEE Control Systems Award (2014), American Academy of Arts and Sciences Membership (2023), and honorary doctorates from multiple institutions. His work bridges theoretical foundations with practical applications in socio-technical networks and edge computing systems. Basar's contributions span over 900 publications, focusing on distributed control algorithms, network security, and strategic information design. His research lab at Illinois addresses challenges in timely computation, resilient systems, and decentralized decision-making frameworks.
Ji-Quan Shi is a Research Fellow in the Department of Earth Science & Engineering at Imperial College London's Faculty of Engineering. His affiliations include the Energy Futures Lab, Minerals, Energy and Environmental Engineering, and Petroleum Geoscience and Engineering. His research focuses on geomechanical and coupled THM (thermo-hydro-mechanical) modeling for CO2 storage, geothermal energy systems, and mining-induced seismicity. Key interests include induced seismicity risk assessment, reservoir simulation, and fracture mechanics in subsurface energy systems. Education background not explicitly stated in text, but his expertise spans geoscience, civil engineering, and environmental systems. Research areas emphasize interdisciplinary approaches to subsurface energy challenges, including carbon capture and storage (CCS), geothermal reservoir management, and coal mining hazards. His work combines field observations, numerical modeling, and laboratory experiments to address challenges like CO2 plume tracking, fault activation mechanisms, and microseismic event forecasting. Recent studies focus on Iceland's geothermal fields (Hellisheiði) and North African CO2 storage sites (In Salah). He has pioneered methods for integrating microseismic data with reservoir models to improve safety and efficiency in subsurface operations. Notable contributions include probabilistic frameworks for hazardous microseismicity prediction in coal mines and coupled modeling of thermal effects on induced seismicity. His research also explores innovative monitoring technologies like distributed fiber optic sensing for CO2 plume tracking.
Zhong-Ping Jiang is an Institute Professor at New York University Tandon School of Engineering, affiliated with the Department of Electrical and Computer Engineering, and holds cross appointments in Civil and Urban Engineering. He leads the Control and Network (CAN) Lab and contributes to research centers like the Center for Advanced Technology in Telecommunications (CATT) and C2SMARTER. His work focuses on nonlinear control, adaptive dynamic programming, and learning-based control with applications to autonomous systems, urban mobility, and computational neuroscience. He serves as Deputy Editor-in-Chief of the IEEE/CAA Journal of Automatica Sinica and has held editorial roles in multiple journals. Research interests include model-based and learning-based control for network systems, with emphasis on robotics, connected vehicles, and urban infrastructure. His contributions to nonlinear small-gain theory and robust reinforcement learning have advanced control methodologies for complex systems. Recent publications highlight trends in resilient control under cyberattacks, data-driven optimal control, and reinforcement learning applications in traffic signal optimization and autonomous driving. His work bridges theoretical advancements with real-world challenges in transportation and cyber-physical systems. Awards: Elected to the European Academy of Sciences and Arts (2024). Grants/Projects: Includes RAPID-funded studies on high-resolution agent-based modeling of epidemic spread and NSF-supported research on urban traffic networks. Labs/Teams: CAN Lab (focusing on control theory and networked systems), CATT (telecommunications innovations), and C2SMARTER (urban mobility solutions).
Sally Gibson is a researcher at the Department of Earth Sciences, University of Cambridge, specializing in mantle geodynamics and volatile cycling processes. Her work integrates field observations, geochemical analysis, and numerical modeling to investigate how deep Earth processes influence surface environments over 3.5 billion years of planetary evolution. Research focuses on volatile cycling (CO₂, H₂O, F, Cl, S) in mantle systems Key projects include mantle plume-ridge interactions with collaborators in the US and Ecuador Operates a LA-ICP-MS laboratory for high-resolution geochemical analyses Supervises PhD students in petrology, geochemistry, and numerical modeling Her research addresses fundamental questions about Earth's habitability through studies of mantle-derived volatiles critical for climate regulation and energy transition metal deposits. Fieldwork in remote regions like Antarctica, Lesotho, and the Galápagos Islands provides empirical data for her interdisciplinary approach. Recent publications highlight her expertise in mantle xenolith analysis, plume dynamics, and volatile quantification in large igneous provinces. Her group's work combines 3He/4He isotopic analysis with seismic tomography to constrain lithospheric evolution and mineral deposit formation. Students under her supervision develop expertise in petrology and geochemical modeling while engaging with environmental and societal impacts of geological research. She actively promotes scientific outreach and community engagement, fostering connections between academia and broader society.
Ahmad Al-Dabbagh is an Assistant Professor in Manufacturing Engineering and holds a Principal's Research Chair in Control Systems (Tier 2) with the School of Engineering at The University of British Columbia. As a Senior Member of IEEE and ISA, he contributes significantly to the field of resilient automation and control systems through research, teaching, and professional service. His academic journey includes postdoctoral fellowships at Imperial College London, the University of Toronto, and the University of Alberta, where he also earned his PhD in Electrical and Computer Engineering. Dr. Al-Dabbagh's research focuses on designing resilient automation and control systems by addressing critical challenges in fault diagnosis, cyber security, and alarm management. His work spans theoretical foundations and practical applications in industrial control systems, with particular emphasis on detection and isolation of faults and cyber attacks, control reconfiguration, event-triggered control, remote state estimation, and alarm systems design. His research interests also extend to causality analysis, prediction methods, and root cause analysis for industrial processes. His extensive publication record demonstrates consistent contributions to control systems security and reliability, with recent work focusing on sophisticated methods for detecting false data injection attacks, analyzing alarm correlations using advanced machine learning techniques, and developing recommender systems for human operators in industrial environments. The trajectory of his research shows an evolution from foundational control theory toward increasingly complex applications in cyber-physical security and human-system interaction in industrial settings. NSERC Postdoctoral Fellowship NSERC Alexander Graham Bell Canada Graduate Scholarship (CGS – D3) Queen Elizabeth II Graduate Scholarship Governor General's Academic Medal (Gold) As a graduate student supervisor, Dr. Al-Dabbagh mentors the next generation of control systems engineers while maintaining an active research program. He serves as an Associate Editor on the IEEE Control Systems Society Conference Editorial Board and is a licensed Professional Engineer in British Columbia and Ontario. His teaching portfolio includes courses such as System Identification, Digital Enterprise, Systems and Control, and Internet of Things, reflecting the breadth of his expertise. Dr. Al-Dabbagh leads the Okanagan Laboratory for Control Systems Research, where his team develops innovative approaches to enhance the security and reliability of industrial automation systems. The laboratory serves as a hub for interdisciplinary research that bridges theoretical control engineering with practical industrial applications, particularly in the energy, manufacturing, and process industries.
Marios Polycarpou is a Professor of Electrical and Computer Engineering and Director of the KIOS Research and Innovation Center of Excellence at the University of Cyprus. He holds honorary positions at Imperial College London and is a member of Academia Europaea. His expertise spans intelligent systems, adaptive control, machine learning, and critical infrastructure. Education: B.A. Computer Science (Rice University, 1987) B.Sc. Electrical Engineering (Rice University, 1987) M.S. Electrical Engineering (University of Southern California, 1989) Ph.D. Electrical Engineering (University of Southern California, 1992) Research Focus: Polycarpou’s work emphasizes fault diagnosis in cyber-physical systems, water distribution networks, and adaptive control. He pioneers digital twin technologies for infrastructure resilience and develops algorithms for real-time anomaly detection and system optimization. Article Trends: His recent publications address adaptive control strategies, cybersecurity in networked systems, and AI-driven solutions for water management. Key themes include distributed control, event-triggered mechanisms, and transformer-based anomaly localization. Awards: 2023 IEEE Frank Rosenblatt Technical Field Award 2016 IEEE Neural Networks Pioneer Award Fellow of IEEE and IFAC Grants & Leadership: He secured prestigious grants including ERC Advanced and Synergy Grants. He led KIOS CoE’s Horizon 2020 projects and served as IEEE Computational Intelligence Society President (2012–2013). Labs & Teams: Directs the KIOS CoE, a hub for AI in critical infrastructure. Collaborates on projects like ERC Water-Futures, focusing on long-term water system transitions and contamination mitigation.
Professor Susan Thorp is a Finance academic at the University of Sydney Business School . With a PhD in Economics from UNSW and prior roles at University of Technology Sydney and the Reserve Bank of Australia, she focuses on household finance , retirement planning , and financial market behavior . BEc (Hons) - University of Sydney Dip. Ed. - University of New England PhD - University of New South Wales Her research interests include: Life-cycle financial decision-making Behavioral influences on savings and investments Superannuation policy and market integration Commodity market dynamics Economic impacts of financial literacy Crises-driven market contagion Recent publications analyze retirement decumulation , financial trust , and commodity-equity market correlations . She leads cross-disciplinary teams applying dynamic programming , econometric modeling , and experimental design to financial challenges. Her grants include ARC Linkage Projects and ASIC commissions for improving financial communication and regulatory frameworks . Media outlets frequently cite her expertise on superannuation policy , market volatility , and retirement savings behavior .
Professor Daniel Quevedo is a leading academic in Electrical and Computer Engineering at The University of Sydney. Previously, he held positions at Queensland University of Technology and Paderborn University, Germany, where he founded the Chair in Automatic Control. He earned his PhD from the University of Newcastle (Australia) and MSc/Ing. degrees from Universidad Técnica Federico Santa María (Chile). His research focuses on networked control systems, cyber-physical systems, and cybersecurity, with contributions to state estimation, control of power converters, and human-in-the-loop systems. He has pioneered work integrating machine learning, behavioral economics, and advanced mathematics to address challenges in interconnected digital-physical environments. Quevedo serves as Associate Editor for IEEE Transactions on Control of Networked Systems and IEEE Control Systems. He chairs the Committee of Experts for Germany’s Excellence Strategy on Digital Methods and has held leadership roles in IEEE technical committees. Notable awards include the IEEE Axelby Outstanding Paper Award (2018) and multiple fellowships. Teaching includes advanced control systems courses like Reinforcement Learning and Optimal Control. He is a Fellow of the IEEE and has published over 200 peer-reviewed articles, with recent work emphasizing privacy-preserving state estimation, resilient control systems, and energy-efficient wireless control. His research labs explore topics such as human-machine collaboration, cybersecurity in Industry 5.0, and data-driven control strategies. Current projects include secure remote state estimation frameworks and adaptive control under adversarial conditions.
