Brooks Butler is a Postdoctoral Fellow at the University of California, Irvine, where he is a participant in the Intelligence Community Postdoctoral Research Fellowship Program administered by Oak Ridge Institute for Science and Education (ORISE) through an interagency agreement between the U.S. Department of Energy and the Office of the Director of National Intelligence (ODNI). He received his Ph.D. in Electrical and Computer Engineering from Purdue University in 2024. He received his M.S. in Computer Science and his B.S. in Applied Physics from Brigham Young University in 2020 and 2019, respectively.

Leonardo Toso is a Presidential and CAIRFI (Center for AI and Responsible Financial Innovation) fellow and a third-year Ph.D. student in the Department of Electrical Engineering at Columbia University. Before joining Columbia, he was a research assistant in the Department of Engineering Science at the University of Oxford. He holds an M.S. degree in Control, Signal, and Image Processing from the University of Paris-Saclay and an M.Eng. degree in Electrical Engineering from CentraleSupélec. In addition, he also holds a B.Eng. in Electrical Engineering from the University of Campinas (Unicamp).

Anastasia Bizyaeva joined the Sibley School of Mechanical and Aerospace Engineering faculty at Cornell University as an assistant professor in July 2024. Her research develops new design principles for flexible multi-agent autonomy inspired by the emergent properties of complex, collectively intelligent biological and socio-cognitive groups. Prior to joining Cornell, she was a postdoctoral scholar at the AI Institute in Dynamic Systems at the University of Washington. She received her Ph.D. in mechanical and aerospace engineering from Princeton University in September 2022 and her B.A. in physics with a minor in mechanical engineering from the University of California, Berkeley in 2016.

Philip E. Paré is the Rita Lane and Norma Fries Assistant Professor in the Elmore Family School of Electrical and Computer Engineering at Purdue University. He received his Ph.D. in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign in 2018, after which he went to KTH Royal Institute of Technology in Stockholm, Sweden to be a Post-Doctoral Scholar. He received his B.S. in Mathematics with University Honors and his M.S. in Computer Science from Brigham Young University in 2012 and 2014, respectively. He was a recipient of the NSF CAREER award in 2023, a 2023-2024 Teaching for Tomorrow Fellow at Purdue, and an inaugural Societal Impact Fellow at Purdue in 2021 as well. He served as IEEE CSS Student Activity Chair (SAC) 2022-2023, IEEE CDC 2023 SAC, IEEE CDC 2024 SAC, the ACC 2026 Publicity Chair. He served as NextCom's Faculty Advisor in its first year and now serves as a member of the Steering Committee. His research focuses on networked control systems, namely modeling, analysis, and control of spreading processes over networks.

Miguel Castroviejo-Fernandez received his B.Sc. and  M.A.Sc. in Aeronautical Engineering from the Université libre de Bruxelles, Brussels, Belgium, in 2019. He is currently pursuing a Ph.D. in Aerospace engineering at the University of Michigan.

His research interests are on constrained control and optimization.

Pelin Sekercioglu is a Postdoctoral Researcher at the Department of Decision and Control Systems at the KTH Royal Institute of Technology, Stockholm, Sweden. She obtained her Ph.D. in Automatic Control in November 2024 from Paris-Saclay University, France. Her work was carried out at ONERA - The French Aerospace Lab and L2S - Laboratory of signals and systems. Her PhD thesis was selected as a finalist for the 2025 Best PhD Thesis Award by GDR MACS. She received her B.Sc. degree in Mechanical Engineering in 2019 and her M.Sc. degree in Advanced Systems and Robotics in 2021, both from the Faculty of Science and Engineering, Sorbonne University, Paris, France. In 2023, she was a visiting researcher at the University of Groningen, The Netherlands. Her research interests include multi-agent systems, signed graph theory, networked and nonlinear control with application to robotics and social networks.

M. Umar B. Niazi is a researcher at KTH Royal Institute of Technology (Sweden). Prior to that, he held postdoctoral positions at MIT (USA) and KTH. He received his Ph.D. in automatic control engineering from Grenoble INP, Université Grenoble Alpes (France) in 2021, where he was affiliated with INRIA Grenoble and GIPSA-Lab as a graduate research assistant. He earned his bachelor's and master's degrees in electrical and electronics engineering from COMSATS Institute of Information Technology (Pakistan) and Bilkent University (Turkey), respectively.

Dr. Niazi is a recipient of the Marie-Curie postdoctoral fellowship from the European Commission. He is a full member of Sigma Xi, nominated in 2025. During his doctoral studies, he received a six-month grant from INRIA under the Mission COVID-19 framework. Both his bachelor's and master's degrees were funded by national and TUBITAK scholarships. He was a finalist for the Best Student Paper Award at the 2019 European Control Conference (ECC). 

Dr. Niazi serves on the Conference Editorial Board of the IEEE Control Systems Society. He is the Finance Chair of the NextCom committee for students and early career researchers in the IEEE Control Systems Society. He also served as a mentor in the Fatima Al-Fihri Predoctoral Fellowship program, supporting students from underrepresented backgrounds.

Urmee Maitra is a PhD candidate attached to the Electrical Engineering department at the Indian Institute of Technology (IIT), Kharagpur. Currently, she is in her fifth year of her course. Prior to that she was attached to the Electrical Engineering department at Jadavpur University, India. To name a few, her research interests include game theory, spreading processes and optimal control. She has attended and presented her work in several international workshops and conferences. She is the finance co-chair (2025) of the IEEE CSS supported NextCom. She is also interested in playing chess, and in the past has represented her school and district in various chess competitions. 

Mehdi Hosseinzadeh joined the School of Mechanical and Materials Engineering at Washington State University, Pullman, WA, in August 2022. His research focuses on safety, resilience, and long-term autonomy of autonomous cyber–physical systems, drawing on tools from control and systems theory, optimization, artificial intelligence, learning-based control, and data-driven control. His work spans applications in autonomous robotics, autonomous vehicles, unmanned aerial systems, energy systems, video streaming, and autonomous drug delivery. Prior to joining Washington State University, he was a postdoctoral research associate at Washington University in St. Louis, MO, USA, and a postdoctoral researcher at the Free University of Brussels, Belgium. 

Tanushree Roy joined the Department of Mechanical Engineering at Texas Tech University as an Assistant Professor in Fall 2022. Her research goal is to build a resilient future for human-centric smart cities. The high‐level goal of such smart cities is to provide better value of services by optimally using the available resources, minimizing the operational cost, maximizing the safety and security, and improving quality of life. Her current research is focused on the resilience of socio-technical systems, such as smart transportation and energy storage systems. She combines control theoretic techniques, mathematical modeling, and machine learning to ensure the safety and the cybersecurity of such human-centric smart city infrastructures. Tanushree received her Ph.D. in Mechanical Engineering from The Pennsylvania State University in the year of 2022. Previously, she has also received the M.S. degree in Mathematics from University of Central Florida in 2015 and the M.E. degree in Electrical Engineering from the Indian Institute of Engineering Science and Technology (IIEST), Shibpur, India in 2011. Between 2011-13, she worked as a Research Consultant for Indian Institute of Technology (IIT), Kharagpur.

Debdipta Goswami joined the Department of Mechanical and Aerospace Engineering, the Ohio State University, in 2022 as an assistant professor. He received his Ph.D. degree in Electrical and Computer Engineering from the University of Maryland in 2020. Between 2020 and 2022, he has worked as a postdoctoral research associate at the Department of Mechanical and Aerospace Engineering in Princeton University. His research interests lie at the intersection of control systems and machine learning with a focus on motion planning and agile control of aerial robots.

He has worked on data-driven discovery and control of dynamical systems using operator-theoretic methods and reservoir computers. His current research focuses on the structured learning of control systems from data with guaranteed performance and simultaneous learning and control of dynamical systems. He also works on model predictive control and motion planning for unmanned aerial vehicles.

Lucy Hodgins is a PhD student at the University of Southampton, researching control approaches for stroke rehabilitation using electrode arrays. She also creates and hosts the Coffee and Control podcast, which aims to highlight voices within the control community and inspire students to pursue a research career in control.

Rajul Kumar is a Presidential Scholar and PhD student at George Mason University, focusing on the intersection of non-linear control and human–robot interactions. He received his Bachelor of Technology in Electrical Engineering from Delhi Technological University (formerly Delhi College of Engineering) in 2021. His research aims to advance control methodologies for safer, more intuitive human–robot collaboration, and he has actively contributed to initiatives that broaden engagement and opportunities within the engineering community.

Felipe Arenas Uribe is a Ph.D. candidate in Aerospace Engineering at the University of Kentucky, where he conducts research within the Autonomy, Robotics and Controls Lab. He holds a B.Sc. in Mechanical Engineering with a minor in Robotics and Automation from Universidad de La Sabana in Colombia. His research specializes in optimization-based and provably safe control, with a focus on real-time algorithms for safety-critical systems and high-performance space vehicles. Beyond his research, Felipe is the founder and director of the International Graduate Pathway Program at the University of Kentucky, which facilitates research opportunities for international visiting scholars. 

Jimin Choi is a Ph.D. candidate in Aerospace Engineering at the University of Michigan. Her research focuses on autonomous systems, decision-making under uncertainty, and optimization for uncrewed aerial systems and future air mobility. She received his M.S. and B.S. from Korea Advanced Institute of Science and Technology (KAIST) and has published work on topics including air traffic decision-making, multi-agent coordination, and reinforcement learning.

Chi Zhang is a master’s student at Southern University of Science and Technology. He holds a B.Eng. degree in Automation and is currently pursuing an M.Sc. degree in Control Science and Engineering.

His current research focuses on multi-robot systems and target tracking under noisy measurements, employing an information-centric approach. 

In addition, driven by a long-standing interest in system autonomy and the generality of control scenarios, Chi is actively exploring the intersection of AI and formal methods. He aims to incorporate automated formal reasoning into control frameworks, thereby ensuring the provable reliability of generalized autonomous system control.

Luca Ballotta received the Master’s degree in automation engineering and the Ph.D. degree in information engineering from the University of Padova in 2019 and 2023, respectively. He is currently a Postdoctoral Researcher with the Delft Center for Systems and Control (DCSC), Delft University of Technology. In 2020 and 2022, he was Visiting Student at the Massachusetts Institute of Technology. He was the recipient of the Young Author Prize at the 2020 IFAC World Congress and was also the Finalist of the 2024 EECI Ph.D. Award. His research interests include networked control of multi-agent and multi-robot systems under resource constraints, resilient distributed control, safe control, and control under sparsity constraints.

Saeed Ahmed is an Assistant Professor of Systems and Control at the University of Groningen, where he is affiliated with the Engineering and Technology Institute Groningen and the Jan C. Willems Center for Systems and Control. Prior to joining this position, he held research positions at the University of Groningen, The Netherlands, the Technical University of Kaiserslautern (now RPTU), Germany, Bilkent University, Turkey, and CentraleSupélec, France. His research interests span various topics in systems and control engineering. From a theoretical point of view, he is interested in stability and control, online optimisation, observer design, nonlinear and hybrid (switched and impulsive) systems, networked systems, and time-delay systems. From an application point of view, he is interested in designing intelligent control algorithms for autonomous vehicles and district heating systems. He won several awards including the best presentation award in the Control, Robotics, Communications, Network category at the IEEE Graduate Research Conference 2018 held at Bilkent University, Turkey, and the Outstanding Reviewer Award by the European Journal of Control. He is an associate editor of Systems and Control Letters and IEEE CSS Technology Conference Editorial Board. He is a member of the IFAC Technical Committees on Non-linear Control Systems, Networked Systems, and Distributed Parameter Systems.

Wenbin Wan is an Assistant Professor in the Department of Mechanical Engineering at the University of New Mexico (UNM). He received his Ph.D. in mechanical engineering and M.S. in applied mathematics from the University of Illinois Urbana-Champaign (UIUC). He earned his B.S. in mechanical engineering from the University of Missouri–Columbia. He was appointed as a MechSE Teaching Fellow at UIUC and was named a CPS Rising Star by the University of Virginia. His research interests include control and optimization, machine learning, and cyber-physical systems (CPS) and their safety-critical applications. He is especially interested in enabling the safe operation of CPS under large uncertainties, such as CPS attacks, unforeseen environments, and faulty models, by integrating resilient estimation, machine learning, and robust adaptive control.

Tung Nguyen received a degree of engineering in automatic control from Hanoi University of Science and Technology, Vietnam, in 2018 and an M.Sc. degree in aerospace engineering from Sejong University, South Korea, in 2021. Currently, he is working toward a Ph.D. degree in automatic control with the Division of Systems and Control, Department of Information Technology, Uppsala University, Sweden. He was visiting scholars at the Kyushu University, Japan (2018), the University of Cyprus, Cyprus (2023), and the Lund University, Sweden (2024). His research interests include control theory, multi-agent systems, and cyber-physical security.

Baike She is a postdoctoral fellow in the School of Electrical and Computer Engineering at the Georgia Institute of Technology. He obtained his Ph.D. in Mechanical Engineering from the University of Iowa. His current research focuses on the modeling, analysis, and control of network dynamics.

Pio Ong received a B.S. in Aerospace Engineering from UCSD in 2012 and an M.S. in Astronautical Engineering from USC in 2013. While working at SpaceX, he developed a strong interest in control theory, which led him to pursue a Ph.D. in Engineering Sciences (Aerospace Engineering) at UCSD. Under the guidance of Prof. Jorge Cortés, he completed his Ph.D. in 2022. Currently, he is a postdoctoral researcher at Caltech, working with Prof. Aaron D. Ames. His research focuses on safety-critical control and event-triggered control for nonlinear and networked systems, with a particular interest in using control barrier functions (CBFs) to guarantee system safety in the presence of attacks or heavy resource constraints, with applications to autonomous and aerospace systems.

Runyu (Cathy) Zhang is a Ph.D. candidate (2019 - present) in the School of Engineering and Applied Sciences, Harvard University. During the summer of 2022, she served as a research intern at Salesforce Research, working on multi-agent reinforcement learning. Prior to pursuing her Ph.D., she earned a B.S. degree in mathematics from Peking University in 2019. Her research interests lie in online control methods, reinforcement learning, game theory and optimization, with particular focus on multi-agent systems. She was selected as the EECS rising star in 2024, and was a finalist of the Two Sigma Diversity PhD Fellowship in 2022.

Ahmet Kaan Aydin received a bachelor’s degree in mathematics from Yildiz Technical University (Turkiye) in 2020, and an M.Sc. degree in Mathematics from Western Kentucky University (USA) in 2022. Ahmet is currently pursuing a Ph.D. degree in Applied Mathematics at the University of Maryland, Baltimore County. His research interests include controllability, and model reductions of smart material systems and development of efficient solvers for stochastic Navier-Stokes equations.

Armin Lederer is an Assistant Professor in the Department of Electrical and Computer Engineering at the National University of Singapore (NUS). He was awarded a Presidential Young Professorship and is a Mercator Fellow of the DFG Project ALeSCo. Before joining NUS in 2025, he was a postdoctoral researcher at ETH Zurich working in  the Institute for Machine Learning and an associated researcher of the ETH AI Center. He obtained his PhD, Master’s, and Bachelor’s degree in Electrical and Computer Engineering at the Technical University of Munich, Germany, in 2023, 2018, and 2015, respectively. His research focuses on ensuring the safety of unknown systems through a combination of techniques from model-based control and supervised machine learning. His goal is the development of theoretically rigorous and computationally efficient methods that can be straightforwardly integrated into robotic systems.

Gabriel Santos Pereira is an undergraduate student of Control and Automation Engineering at the Federal University of Minas Gerais (UFMG), Brazil, where he is a member of the LOPAC-DEE research laboratory. He completed an academic exchange program at Polytech Angers, LARIS research laboratory in France, focusing on automated systems and computer engineering. His research focuses on the application of Tropical Algebra for modeling industrial processes and urban systems, such as traffic networks. Currently, he is an intern with the Operations Research team at Vallourec, working to integrate academia and industry for an optimized future. He also serves as a volunteer for the IEEE Student Branch at UFMG.

Riwa Karam is a Ph.D. candidate in the Electrical Engineering and Computer Science Department at the University of California, Irvine. She is a member of the Robot Ecology Lab and is advised by Professor Magnus Egerstedt and Professor Yanning Shen. She is currently in the third year of her doctoral program. Her research focuses on collaboration in heterogeneous multi-agent systems, with an emphasis on leveraging machine learning to enable scalable decision-making in complex multi-robot systems. She received her M.S. in Electrical and Computer Engineering from the University of California, Irvine in June 2025, and her B.S. in Computer Engineering from the University of Balamand, Al-Kurah in June 2023.

Giovanna Amorim is a Ph.D. candidate in Mechanical and Aerospace Engineering at Princeton University. She received her B.S. in Aerospace Engineering from the University of Maryland, College Park. Her research focuses on perceptual decision-making, nonlinear dynamics, and multi-agent systems, with applications in robotics and autonomous systems.

​Abhishek Barad is a researcher at the Indian Institute of Technology (IIT), Madras, completing an M.S. in Aerospace Engineering with a foundational background in Electrical Engineering. His expertise lies at the intersection of Optimal Control Theory, Guidance and Navigation, and Trajectory Generation.

​Abhishek’s primary research, focused on autonomous guidance and constrained optimal control, was recently presented at the IEEE 64th Conference on Decision and Control (CDC) 2025. Currently, he is pivoting his expertise toward Robotics, with a specific interest in addressing cutting-edge challenges in robot learning and perception. He is actively seeking a PhD position to apply his control-theoretic background to complex, hands-on robotics problems. 

Dr. Emily Pereira is an Assistant Professor in the Electrical and Computer Engineering Department at Texas Tech University. She earned her Ph.D. in Electrical and Computer Engineering from the University of Southern California, where she developed control algorithms for regulating large-scale dynamical networks. Dr. Pereira completed postdoctorate work at Johns Hopkins University, with a special focus on translating control systems principles to identify biomarkers for epilepsy. Dr. Pereira received the National Science Foundation Graduate Research Fellowship, National Defense Science and Engineering Graduate Research Fellowship, and Annenberg Fellowship. In 2023, she was named a rising star in Electrical Engineering and Computer Science. Recently, she was named Best Outstanding Faculty Mentor at Texas Tech University. 

Dr. Xiangyu Meng is currently an Associate Professor in the Division of Electrical and Computer Engineering at Louisiana State University (LSU), a position he has held since January 2026. He first joined LSU as an Assistant Professor in January 2019. He received his Ph.D. in Electrical and Computer Engineering from the University of Alberta, Canada, in 2014. He then worked as a Research Fellow at Nanyang Technological University, Singapore (2014–2016), followed by a Postdoctoral Associate position in the Division of Systems Engineering at Boston University (2017–2018). Dr. Meng's research interests include event-triggered control, multi-agent systems, and reinforcement learning with applications in autonomous vehicles and intelligent transportation systems.

Dyhia Bouhadjra is a researcher at the National Research Council of Italy (CNR), where she specializes in Moving Horizon Estimation (MHE) for dynamical systems. Her work focuses on optimization-based formulations and the development of computationally efficient algorithms designed for high-performance, real-time implementation.

She earned her Ph.D. in Control Engineering in December 2022 through a joint program (cotutelle) between the University of Lorraine (France) and the University of Genoa (Italy). Her doctoral research focused on observer design for nonlinear systems, with applications to biological plants, combining theoretical developments with application-oriented validation.

Following her Ph.D., she held temporary teaching and research positions (ATER — Attaché Temporaire d’Enseignement et de Recherche) in France, first at the Polytechnic School of the University of Orléans in 2023, and subsequently at the University of Lorraine within the “Centre de Recherche en Automatique de Nancy” in 2024.

Laura Lützow is a PhD student at the Cyber Physical Systems Group at the Technical University of Munich under the supervision of Prof. Dr.-Ing. Matthias Althoff. She holds a bachelor's degree in Mechatronics from the Technical University of Ilmenau (2020) and a master's degree in Robotics, Cognition, and Intelligence from the Technical University of Munich (2022). Laura completed her master's thesis on density-based motion planning at the Massachusetts Institute of Technology's Reliable Autonomous Systems Lab, under the supervision of Chuchu Fan. From January to July 2025, she was visiting the Stanford Intelligent Systems Laboratory under Mykel Kochenderfer. 

Laura's current research focuses on set-based system identification, uncertainty quantification, and conformance checking to improve the safety and reliability of autonomous systems and artificial intelligence.

G. Q. Bao Tran is a Postdoctoral Research Associate at the University of Illinois Urbana–Champaign, USA. In 2025, he was a Postdoctoral Research Associate at Seoul National University, South Korea, and a Visiting Scholar at Keio University, Japan. Bao received his Ph.D. in Mathematics and Automatic Control from Mines Paris, Université Paris Sciences et Lettres (PSL), France, in 2024. In 2023, he was a Visiting Scholar at the University of California Santa Cruz, USA. Bao obtained an Engineering degree in Automatic Control from Grenoble INP, Université Grenoble Alpes, France, in 2021, after completing his Bachelor’s studies in Mechatronics at HCMC University of Technology, Vietnam, in 2019. Throughout his career, he has also conducted research at GIPSA-Lab, France, and at the University of Tokyo, Japan.

Rahul Misra is currently a Post doctoral researcher at the Department of Electronic Systems, Aalborg University. He previously received his PhD from the same institute. His PhD thesis focused on Decentralized control of complex systems using game theory and reinforcement learning. His research lies at the intersection of probability theory, optimization, and control theory. Specific topics of his research include game theory, reinforcement learning,  constrained optimization, and nonlinear control. He has experience in designing control systems for various applications, including satellites, water networks, building HVAC, and robotics. He was previously employed at Bosch Group in India. His research has been recognized with the EliteForsk Rejsestipendier (Elite Research Travel Grant) in 2022 by the Ministry of Higher Education and Science, Denmark.

Erfaun Noorani is a Technical Staff at MIT Lincoln Laboratory. His research focuses on developing robust-resilient-adaptive reinforcement learning and data-driven control systems that are generic, provide performance guarantees, and can generalize-reason-improve in complex and unknown task environments. Before joining the Laboratory, he was a Postdoctoral Associate within the Institute for Systems Research (ISR) at the University of Maryland, College Park, where he received his Ph.D. and M.S. as a Clark Doctoral Fellow with the Department of Electrical and Computer Engineering. His doctoral work, under the supervision of John Baras, focused on robust and risk-sensitive reinforcement learning. Erfaun obtained a B.Sc. degree in Electrical Engineering from Drexel University, Philadelphia, Pennsylvania.