Nirupam Roy is an Assistant Professor at the Department of Computer Science, University of Maryland, College Park, and Director of the iCoSMoS research lab. His work bridges wireless networking, mobile computing, and acoustic sensing with applications in IoT, localization, healthcare, security, and wearables. Research Focus: Wireless Networking & Mobile Sensing Awards: Best paper award, MobiSys 2022 Best demo award, MobiSys 2021 CSL Ph.D. Thesis Award, UIUC 2019 Students: Nakul Garg, Yang Bai, Irtaza Shahid, Harshvardhan Takawale, Aritrik Ghosh, Ayushi Mishra, Sumbul Zehra, Justin Goodman Grants: NSF CAREER award (2023), Meta Research Award (2023)
Kevin M. Lynch is a Professor of Mechanical Engineering at Northwestern University's McCormick School of Engineering, where he also serves as Director of the Center for Robotics and Biosystems. His research spans multiple domains of robotics, with particular expertise in dynamics, motion planning, and feedback control of mechanical systems. Dr. Lynch received his Ph.D. in Robotics from Carnegie Mellon University in 1996, with a thesis on "Nonprehensile Robotic Manipulation: Controllability and Planning" under advisor Prof. Matthew T. Mason. He earned his B.S.E. with honors in Electrical Engineering from Princeton University in 1989. His research interests focus on robotics, particularly dynamics, motion planning, and feedback control of mechanical systems. He investigates mechanics, planning, and control of robotic manipulation (juggling, throwing, pushing, rolling, vibration, etc.) and locomotion. His work also explores self-organizing systems, particularly decentralized control of mobile sensor networks and swarm robotics, underactuated dynamic systems, and physical human-robot interaction with industrial applications. Recent research has expanded into bio-inspired active electrosense, underwater robotics, control and optimization for robot swarms, swarm shape control, and functional electric stimulation. Dr. Lynch's recent publications demonstrate a strong trend toward rehabilitation robotics and human-robot interaction, particularly in lower-limb exoskeletons for gait training and rehabilitation. His work bridges fundamental robotics research with practical applications in healthcare, showing increasing integration of swarm robotics principles with human-centered design. The publications also reveal continued strong contributions to fundamental robotics theory, particularly in swarm formation control and manipulation dynamics. George Saridis Leadership Award in Robotics and Automation (2022) Harashima Award for Innovative Technologies (2017) IEEE Fellow (2010) Charles Deering McCormick Professor of Teaching Excellence (2007-10) Society of Automotive Engineers Ralph R. Teetor Educational Award (2007) Early Career Award in Robotics and Automation (2001) McCormick School of Engineering and Applied Science Teacher Of The Year Award (1998-1999) NSF Career Award (1998) As Director of the Center for Robotics and Biosystems, Dr. Lynch oversees significant research grants and initiatives in robotics. He has made substantial contributions to robotics education through his "Modern Robotics" book and associated Coursera specialization, which has reached thousands of students worldwide. His professional service includes serving as Editor-in-Chief of IEEE Transactions on Robotics, where he oversaw a 90% increase in submissions during his tenure. Dr. Lynch leads research groups focusing on swarm robotics and rehabilitation robotics, with particular emphasis on the Center for Robotics and Biosystems at Northwestern University. His teams integrate expertise from mechanical engineering, electrical engineering, computer science, and rehabilitation medicine to develop innovative robotic systems for both industrial applications and healthcare solutions.
Dr. Joey Paquet is a Tenured Associate Professor and Department Chair in the Department of Computer Science and Software Engineering at Concordia University in Montreal, Canada. He holds a PhD and specializes in research areas including Design and Implementation of Programming Languages, Context-Driven Computing, and Demand-Driven Computing. His work focuses on advancing programming paradigms and their applications in cybersecurity, distributed systems, and autonomic computing. Dr. Paquet is actively involved in thesis supervision across Computer Science and Software Engineering programs at both master's and doctoral levels. Research interests are centered around programming language design, particularly in demand-driven and context-aware systems. His contributions include frameworks like GIPSY and OpenISS, enabling scalable data processing and forensic computing. Recent work explores autonomic intent-driven networking, real-time gesture recognition, and IoT forensics. These efforts highlight his expertise in both theoretical constructs and practical implementations. His advising role supports students in MCompSc, MASc, and PhD programs. While specific grants are not detailed, his projects often involve interdisciplinary collaboration. Dr. Paquet is affiliated with platforms like LinkedIn and ResearchGate, reflecting an active academic presence. Key technical contributions include pioneering work on forensic computing backends, intent expression languages, and multimodal interaction systems. His research addresses challenges in cybersecurity, distributed systems, and service composition, with a focus on resilience and scalability.
Baris Fidan is a Professor in Mechanical & Mechatronics Engineering at the University of Waterloo, with cross appointments in System Design Engineering and Electrical & Computer Engineering. He is a senior member of IEEE and AIAA. His research focuses on cooperative/adaptive control, autonomous systems, multi-agent networks, and vehicular control applications. He leads the Cooperative & Adaptive Mechatronic Systems (CAMS) Lab, which develops control strategies for autonomous vehicles, robotic systems, and intelligent transportation. Education: PhD in Electrical Engineering, University of Southern California (2003) Masters in Electrical & Electronic Engineering, Bilkent University (1998) Bachelor's in Electrical & Electronic Engineering & Mathematics, Middle East Technical University (1996) Research Interests: His work spans adaptive control theory, sensor networks, multi-agent coordination, autonomous vehicle networks, and biomedical systems control. He emphasizes practical applications in intelligent transportation, robotic navigation, and distributed system optimization. Grants & Projects: He has led major grants including NSERC Discovery Programs on cooperative mechatronic systems and 3D autonomous vehicle coordination. Industrial projects include autonomous driving strategies, vehicle control optimization, and high-precision gear manufacturing technologies. Labs/Teams: Directs the CAMS Lab, which collaborates on projects involving distributed motion planning, sensor localization, and autonomous vehicle networks. Current projects address challenges in urban autonomous driving, cooperative robotic systems, and resilient sensor networks.
Kostas Bekris is a Professor in the Department of Computer Science at Rutgers University, specializing in Robotics and Artificial Intelligence. His research focuses on motion planning, autonomous manipulation, and robot control, with notable contributions to tensegrity robotics, perception-driven systems, and large-scale package handling. He leads a team conducting groundbreaking work in robotics, supported by grants from NSF, NASA, and industry collaborators like ExxonMobil. His group emphasizes interdisciplinary approaches, combining machine learning, topological methods, and differentiable physics modeling to advance robot capabilities in complex environments. Education details are not explicitly stated in the provided texts, but his academic career has included significant mentorship of PhD students and postdoctoral researchers. Key projects involve vision-driven manipulation pipelines, obstacle detection systems (PROBE), and resilient robot designs inspired by biological structures. He has been recognized for his work through prestigious awards including the NASA Early Career Grant and multiple NSF grants, as well as team achievements in robotics competitions like the Amazon Picking Challenge. Research interests span robotics subfields such as: Autonomous manipulation in cluttered environments Learning-based control for dynamic systems Topological data analysis for motion reasoning Tensegrity and soft robotics architectures Sim-to-real transfer in robotic tasks His team's work has produced open-source software tools and datasets, advancing benchmarks in manipulation and perception. Recent articles emphasize scalable solutions for industrial automation and robust navigation strategies in unstructured settings. Scientific achievements include: Development of PROBE for proprioceptive obstacle detection Advances in differentiable physics engines for tensegrity systems NSF-funded projects on robotic rearrangement and modular morphologies Advising contributions span over a decade, with current advisees focusing on topics like non-prehensile manipulation and large-scale storage optimization. Collaborations with industry (e.g., ExxonMobil) and academic partners (Yale University) reflect his commitment to applied robotics research. Labs and teams under his leadership include the Rutgers CS Robotics Group, contributing to projects like the ARIAC challenge platform and packing/industrial automation systems. Future work targets improved robot resilience in disaster scenarios and enhanced human-robot collaboration paradigms.
Dr. Mathieu Joerger is an Associate Professor in the Aerospace & Ocean Engineering Department at Virginia Tech, leading the Assured Vehicle Autonomy (AVA) Lab. He holds a Ph.D. (2009), M.S. (2002), and Diplôme d’Ingénieur (2002) from Illinois Institute of Technology and INSA Strasbourg. His research focuses on navigation safety, multi-constellation GNSS, and autonomous system integrity. He serves as Technical Editor for IEEE Transactions on Aerospace and Electronic Systems and co-leads the CARNATIONS initiative for resilient PNT systems. Notable awards include the ION Early Achievement Award (2015) and Bradford W. Parkinson Award (2009). Research interests include GNSS augmentation, LiDAR/IMU integration, and safety quantification for autonomous vehicles. His lab collaborates with industry/government on projects like CAAMS and develops methods to detect GNSS interference using UAS. Key publications address integrity monitoring in SLAM, particle filtering, and Kalman filter applications. Education: Ph.D. Mechanical & Aerospace Engineering, Illinois Tech (2009); M.S. Mechanical Engineering, Illinois Tech (2002); Diplôme d’Ingénieur, INSA Strasbourg (2002). Awards: ION Early Achievement Award, Outstanding NAVIGATION Reviewer, Bradford W. Parkinson Award. Professional Roles: Senior Editor for IEEE Transactions, ARAIM Standards Contributor, CARNATIONS Co-Director. Advises multiple PhD/Master’s students and oversees lab activities involving 20+ researchers. Projects include R-PNT systems, UAS-based RFI localization, and automotive GNSS safety. Active in international conferences like ION GNSS+ and AIAA forums.
Maria Apostolaki is an Assistant Professor of Electrical and Computer Engineering at Princeton University. Her research focuses on designing secure, reliable, and high-performance networked systems, integrating expertise in networking, security, blockchain, and machine learning. She holds a Ph.D. from ETH Zurich (2021) and an M.Eng. from the National Technical University of Athens (2015). Education: Ph.D., ETH Zurich 2021 | M.Eng., NTUA 2015 Her work investigates challenges in network security, distributed systems, and adversarial resilience. Notable contributions include SABRE (protecting Bitcoin from routing attacks) and TANGO (collaborative route control). She has advised multiple graduate students in computer science and engineering. Key honors include the NSF CAREER Award and the IRTF/IETF Applied Networking Research Prize (2018). Her lab explores cutting-edge topics like contextual robustness in ML-driven network functions and formal methods for secure systems. Advising: 6 advisees in COS/ECE domains Grants: NSF CAREER Award, innovation grants for AI/robotics Her TANGO framework enables secure cross-domain routing, while recent work addresses vulnerabilities in Ethereum PoS and BGP routing protocols.
Margarita Boenig-Liptsin is a tenure-track Assistant Professor of Ethics, Technology and Society at ETH Zurich's Department of Humanities, Social and Political Sciences, a position she has held since September 2022. Trained in Science, Technology and Society with dual PhDs from Harvard University (History of Science) and Université Paris-Sorbonne (Philosophy), she brings interdisciplinary expertise to examining the relationship between technology, power, democracy, and ethics. Her research spans several interconnected areas focusing on transformations to human identity and citizenship in relation to information technologies across time and cultures. She investigates the social and political aspects of digital technologies, identity and selfhood in technological societies, ethics of technology, and comparative cultures of innovation. Her work uniquely bridges historical analysis with contemporary ethical concerns, examining how concepts like human dignity evolve alongside technological developments from punch cards to AI governance frameworks. Her recent publications (2023-2025) reveal a strong focus on AI ethics, data justice, and the philosophical implications of algorithmic systems. These works demonstrate her consistent interest in how technology shapes democratic processes, citizenship, and ethical frameworks. Her research shows progression from historical studies of computer literacy programs to contemporary analyses of generative AI's impact on knowledge production and everyday ethics. Her scientific recognition includes: NSF funding for her collaborative project on Silicon Valley's innovation imaginary Mozilla Foundation Responsible Computer Science Challenge grant (2018-2021) Academic Data Science Alliance support (2020-2022) Sorbonne Université's Paris IAS Chair on 'Major Changes' (2021-2022) At ETH Zurich, she leads research and teaching initiatives that build connections between engineering and social sciences. Previously at UC Berkeley, she directed the Human Contexts and Ethics Program, developing the Human Contexts and Ethics component for data science education. Her work consistently emphasizes translating social science theory for diverse audiences and connecting scholarly work to community needs in Zurich, Switzerland, and Europe. She teaches courses including 'Artificial Intelligence and Human Values' and 'Research in Ethics, Technology and Society' for the Fall 2025 semester.
Michael Bartlett is an Associate Professor in the Department of Mechanical Engineering at Virginia Tech , leading the Soft Materials and Structures Lab within the College of Engineering. His research focuses on bio-inspired materials , soft robotics , and multifunctional composites with applications in adaptive adhesives , stretchable electronics , and self-healing systems . Education: Ph.D., Polymer Science & Engineering, University of Massachusetts Amherst (2013) B.S.E., Materials Science & Engineering, University of Michigan (2008) His work explores the intersection of soft materials , morphing structures , and functional composites , leveraging techniques like kirigami and liquid metal integration to create innovations such as octopus-inspired underwater gloves and shape-shifting drones . His recent articles highlight advancements in programmable adhesion , liquid metal conductors , and multiscale material design . Scientific Awards: National Academy of Inventors Senior Member (2024) NSF CAREER Award (2023) Office of Naval Research Young Investigator Award (2021) Soft Matter Emerging Investigator (2021) DARPA Director’s Fellowship (2020) Adhesion Society Early Career Scientist (2020) DARPA Young Faculty Award (2018) 3M Non-Tenured Faculty Award (2017) Bartlett has mentored over 40 undergraduate students and numerous graduate researchers, resulting in 12 peer-reviewed articles with student co-authors. His lab receives funding from federal agencies like NSF , ONR , and DARPA , as well as industry partnerships. The group also engages in K-12 outreach programs and collaborates with institutions such as University of Nebraska-Lincoln and Iowa State University .
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.
Cong Shi, also known as Alex Shi, is a Professor of Management at the Miami Herbert Business School, University of Miami, since 2025. Previously, he served as Associate Professor at the University of Michigan (2019-2023) and Assistant Professor there (2012-2019). His academic journey began with a B.Sc. in Mathematics (First Class Honors) from the National University of Singapore (2007) and a Ph.D. in Operations Research from MIT (2012) under Professor Retsef Levi. Education : MIT (Ph.D.), NUS (B.Sc.) Current Role : Professor, Management, Miami Herbert Business School Prior Roles : Associate Professor (Tenured), University of Michigan; Assistant Professor, University of Michigan His research spans Revenue Management, Supply Chain Management, Healthcare Operations, Human-Robot Interaction, and Data-Driven Optimization. Recent publications focus on fairness-constrained inventory, sequential pricing, and trust-aware robotics. He has received prestigious awards including the Senior Research Award (2025) and Amazon Research Award (2021), alongside multiple INFORMS recognitions. The 15 most recent articles highlight advancements in inventory control with fairness constraints, sequential pricing algorithms, and trust propagation models in robotics. His work bridges theoretical rigor with practical applications in supply chains and human-robot collaboration. Scientific Awards : Senior Research Award, Miami Herbert Business School, 2025 Amazon Research Award, 2021 INFORMS Meritorious Service Awards (2018, 2019, 2021, 2023) IOE Graduate Course Professor of the Year, University of Michigan, 2019 He has advised 10 PhD students, many now in academia (e.g., UC Berkeley, Penn State) or tech roles (Meta, Amazon). Grants include NSF funding as PI and Co-PI.
Dr. Lilong Chai serves as an Associate Professor & Engineering Specialist in the Department of Poultry Science at the University of Georgia's College of Agricultural and Environmental Sciences, with affiliate status at the UGA Institute of Integrative Precision Agriculture. His work integrates engineering principles with animal science to advance sustainable poultry production systems through climate-resilient practices and precision farming technologies. His academic foundation includes a Ph.D. in Agricultural and Bio-environmental Engineering from China Agricultural University (2005-2011), B.S. from Anhui Agricultural University (2001-2005), joint Ph.D. studies at Purdue University (2008-2010), and postdoctoral research at Iowa State University (2015-2018) and Agriculture and Agri-Food Canada (2012-2015). Dr. Chai's research program centers on precision poultry farming, climate-smart animal production, and animal welfare enhancement. He pioneers applications of deep learning, computer vision, and environmental engineering to develop real-time monitoring systems for poultry behavior, health indicators, and housing conditions. His work addresses critical industry challenges including floor egg management, footpad dermatitis detection, air quality control, and disease prevention in cage-free systems, emphasizing practical solutions that balance productivity with ethical animal husbandry. Analysis of his 2023-2025 publications reveals dominant themes in AI-driven behavioral monitoring (dustbathing, perching, foraging), thermal imaging for welfare assessment, and sustainable waste management. These studies consistently bridge agricultural engineering, veterinary science, and data analytics to create scalable precision farming tools applicable across commercial poultry operations. His scientific recognition includes 20 major awards such as: Educational Aids Blue Ribbon Award from ASABE (2024) NACAA Communications Award for Precision Poultry Farming Education (2023) Georgia Research Alliance's Georgia Greater Yield selection (2023) ASABE Outstanding Associate Editor Award (2022) Dr. Chai has secured $5 million through 40 competitive grants from USDA-NIFA, NSF, and international agencies as PI/Co-PI. He actively translates research into practice through leadership roles including Coordinator of the Georgia Precision Poultry Farming Conference, Chair of ASABE's Environmental Air Quality Committee, and reviewer for major research foundations. His extension work directly impacts industry stakeholders through annual training programs serving Georgia's poultry sector. His research infrastructure operates within UGA's Poultry Science Department and the Institute of Integrative Precision Agriculture, where he collaborates with interdisciplinary teams to develop next-generation monitoring systems integrating robotics, thermal imaging, and foundation models for real-world poultry applications.
Geert Deconinck is a full professor at KU Leuven , leading the Electrical Energy Systems and Applications (ELECTA) research group within the Department of Electrical Engineering (ESAT). He also serves as scientific leader of the EnergyVille research center's algorithms domain, focusing on smart electrical networks and thermal systems. M.Sc. and Ph.D. from KU Leuven Head of ELECTA since 2012 (10 professors, 8 postdocs, 70+ PhDs) Over 8 million EUR research budget in last 5 years 44 completed PhDs and 10 current advisees IEEE Transactions editorial board member His research spans smart grid architectures , distributed control , and cyber-physical security , with recent focus on EV-grid integration , renewable energy democratization , and multi-carrier energy systems . Current projects include: Smart Charging - E-Mobility meets Renewable Energy Early Detection and Defense Systems for Smart Grids Open-source P2P energy sharing platforms Microgrid control strategies for PV-battery systems Awarded IET Fellow and IEEE Senior Member status, his work combines machine learning with power systems engineering through both theoretical modeling and experimental validation . He has contributed over 575 publications with 9800+ Google Scholar citations.
Dr. Bin Tang is a Professor in the Department of Computer Science at California State University, Dominguez Hills. He holds a Ph.D. in Computer Science from Stony Brook University (2007) and dual M.S. degrees in Computer Science and Materials Science from the same institution. His research focuses on algorithmic solutions for data placement in networks, with applications in robotic sensor systems and cloud data centers. He has led multiple NSF-funded projects including 'Edge-Based Approach to Robust Multi-Robot Systems' and 'Optimal Resource Allocation in Policy-Driven Data Centers'. Dr. Tang mentors students in research competitions and has supervised numerous graduate theses. He teaches courses in operating systems, algorithms, computer networks, and cloud computing.
Professor Petri Kuosmanen is affiliated with Aalto University as a faculty member of the School of Engineering and holds a position in the Department of Energy and Mechanical Engineering and the Mechatronics unit. Doctoral Degree in Engineering and Technology, Helsinki University of Technology (2004) Licentiate Degree in Engineering and Technology, Helsinki University of Technology (1992) Master's Degree in Engineering and Technology, Helsinki University of Technology (1988) His research focuses on Industrial Internet and Rotor Dynamics , with significant contributions to elevator systems , hydraulics , and wastewater treatment plant design . Recent work includes optimizing natural frequencies in rotor systems and developing digital twins for engineering education . Key trends in his 2024 publications include: Rotor dynamics and vibration analysis Smart data validation in industrial IoT networks Cold-climate adaptations for wastewater treatment Automated fiber optics coating mechanisms Energy efficiency in aeration systems As Principal Investigator, he leads projects like DRIVE FORWARD (2024–2027) and GOOD (2021–2024), focusing on electrified mobile machinery. He actively collaborates with networks such as DAAAM International (Chair) and European CLUSTER-university network (Member).
