Wenchao Li is an Assistant Professor in the Department of Electrical and Computer Engineering at Boston University, directing the Dependable Computing Laboratory. He holds a B.S., M.S., and Ph.D. in Electrical Engineering and Computer Sciences, along with a B.A. in Economics from UC Berkeley. His research focuses on dependable computing, applying formal verification, machine learning, and control theory to cyber-physical systems, electronic design automation, and AI safety. Key research interests include neural network verification, safe reinforcement learning, autonomous systems security, and resilient control strategies for connected vehicles. His work emphasizes provable safety guarantees and defense against adversarial attacks in critical infrastructure systems. Notable awards include the ACM Outstanding Ph.D. Dissertation Award and the Leon O. Chua Award. His lab investigates topics such as neural network repair, secure multi-robot coordination, and formal methods for autonomous systems. He advises students like Jiameng Fan and collaborates on projects funded by grants in AI safety and cyber-physical systems. Labs/Teams: Dependable Computing Laboratory Grants: Focus on formal verification, AI safety, and autonomous systems resilience
Angelica Lim is an Assistant Professor of Professional Practice and Rajan Family Scholar in the School of Computing Science at Simon Fraser University. Her research focuses on Human Robot Interaction, Affective Computing, and Multimodal Perception with applications in healthcare and developmental robotics. She holds a PhD in Informatics from Kyoto University (2014), an M.Sc. from Kyoto University (2012), and a B.Sc. in Computing Science from SFU (2008). Her work bridges robotics and human-centered AI through projects like the ROSIE Lab, exploring emotion-aware systems, socially assistive robots, and VR programs for aging populations. Key contributions include benchmarking emotional speech recognition (BERSting), developing embodied emotion models for robots, and co-designing healthcare technologies with patient partners. Recent publications emphasize ethical AI, multimodal perception systems, and human-robot collaboration in dynamic environments. Teaching includes courses on software engineering, artificial intelligence, and introductory computer science. Her research has been applied in dementia care through VR programs, robotic companionship for older adults, and emotion-aware human-robot communication systems. Current initiatives focus on inclusive HRI design and sim2real methodologies for underrepresented data in affective computing.
Geoff Hollinger is a Professor in the Department of Mechanical, Industrial, and Manufacturing Engineering at Oregon State University, and a Ron and Judy Adams Faculty Scholar. His research focuses on robotic decision-making, planning, and coordination for autonomous systems, particularly in underwater and multi-robot environments. He leads the Robotic Decision-Making Laboratory and has expertise in mission planning, control systems, and marine robotics. Dr. Hollinger holds a PhD in Robotics from Carnegie Mellon University (2010), an MS in Robotics (2007), and a BS in General Engineering and BA in Philosophy from Swarthmore College (2005). His work spans theoretical advancements and practical applications, including underwater docking systems, autonomous exploration, and soft robotics for hazardous environments. Research Interests: Autonomous underwater vehicle (AUV) systems and docking Multi-robot coordination and task assignment Probabilistic planning and decision-making Behavior trees and formal grammars for task planning Underwater manipulation and grasping Energy-efficient trajectory planning Key Achievements: Recipient of the 2017 ONR Young Investigator Award 2017 Celebrate Excellence Awards and Engelbrecht Young Faculty Award Developed frameworks like Angler for intervention tasks and Wave for underwater emulation Labs/Teams: Robotic Decision-Making Laboratory, Collaborative Robotics and Intelligent Systems Institute (CRIS).
Dr. Tim Oates is a Professor in the Department of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County . His research spans machine learning, artificial intelligence, and brain-machine interfaces, with a focus on weakly supervised methods, human-in-the-loop reinforcement learning, and grounded policy development for robotics. Ph.D., Computer Science, University of Massachusetts, Amherst, 2000 M.S., Computer Science, University of Massachusetts, Amherst, 1997 B.S., Computer Science and Electrical Engineering, 1989 Current research threads include: Developing non-invasive brain injury severity assessment via medical time series Modeling human brain development through computational frameworks Designing algorithms for autonomous robotic learning Recent publications highlight AI security mechanisms (backdoor detection via tensor decomposition, matrix factorization) Medical applications (3D artery reconstruction, skin lesion diagnosis, EEG denoising) Neuro-symbolic integration (holographic representations, language-guided reinforcement learning) Mathematical reasoning (schema-based problem solving, subitizing algorithms) Contact: oates@cs.umbc.edu | Office: 336 Information Technology and Engineering (ITE) Building
Lyndia Wu is an Assistant Professor in the Department of Mechanical Engineering at the University of British Columbia's Faculty of Applied Science, where she holds the prestigious Canada Research Chair in Wearable Brain Injury Sensing. She leads the SimPL (Sensing in Biomechanical Processes Lab) and maintains an active research program focused on biomechanics and medical device development. Her educational background includes: B.A.Sc. from the University of Toronto M.S. from Stanford University Ph.D. from Stanford University Postdoctoral Fellowship from Stanford University Dr. Wu's research program centers on developing novel sensing and data analytics technologies to study human biomechanics in health and disease states. Her primary research areas encompass brain injury or concussion biomechanics using advanced sensing, modeling, and machine learning approaches, as well as the development of innovative sensors and algorithms for studying sleep disorders like obstructive sleep apnea. She specializes in wearable sensors for brain health monitoring, traumatic brain injury mechanisms, and AI applications in healthcare settings. Analysis of her recent publications reveals a strong focus on sports-related head impacts (particularly in soccer), EEG monitoring following impacts, and sleep monitoring after concussions. Her work demonstrates interdisciplinary collaboration across biomechanical engineering, neuroscience, and clinical medicine, with publications spanning biomechanics, neurotrauma, biomedical instrumentation, and signal processing domains. Dr. Wu has received significant recognition for her work, including: Scholar Award from the Michael Smith Foundation for Health Research (2019) Junior Faculty Teaching Award from UBC Mechanical Engineering (2022) She actively supervises graduate students in Mechanical Engineering programs (MASc and PhD) and collaborates extensively across disciplines. Dr. Wu is affiliated with multiple research centers including the Institute for Computing, Information and Cognitive Systems (ICICS), Origins of Balance Deficits and Falls, and SmarT Innovations for Technology Connected Health (STITCH), reflecting her interdisciplinary approach to solving complex biomedical challenges. As director of the SimPL lab, she leads a research team developing cutting-edge sensing solutions for biomechanical processes with particular emphasis on brain injury prevention, monitoring, and recovery assessment through innovative engineering approaches.
Benoit Rosa is currently a CNRS Researcher within the Robotics, Data science, and Healthcare technologies Team at the ICube Laboratory, University of Strasbourg. Previously, he was a Research Fellow at the Pediatric Cardiac Bioengineering Lab, Boston Children's Hospital, Harvard Medical School (2015-2016), and a postdoctoral fellow in the Robot Assisted Surgery group at the Mechanical Engineering department of KU Leuven, Belgium (2013-2015). He received his Ph.D. in 2013 from Pierre & Marie Curie University (now Sorbonne University) under the supervision of Pr. Guillaume Morel and Pr. Jerome Szewczyk. His PhD was awarded the best PhD thesis award by the CNRS research group on robotics for 2013. Prior to his PhD, he obtained an Engineering Degree (equivalent to a Master's) from Ecole Centrale Paris. Rosa's research focuses on surgical robotics and image-guided control, with particular expertise in the design and control of miniature, distally-actuated and flexible systems for minimally invasive surgery. His work spans from mechatronic design of minimally invasive surgical devices to advanced control algorithms for surgical robots. Key areas include continuum robotics, visual servo control, surgical tool segmentation, and OCT-guided interventions. His research has significant applications in cardiac surgery, endomicroscopy, and various minimally invasive procedures, with a strong emphasis on translating theoretical robotics into practical clinical solutions. His recent publications demonstrate a growing trend toward applying deep learning techniques to enhance surgical robotics, with focus on autonomous systems that improve precision and reduce surgeon cognitive load while addressing challenges in medical imaging and surgical navigation. Scientific Awards: Best PhD thesis award by the CNRS research group on robotics (2013) Rosa has led multiple significant research projects including Image-based tracking of continuum robots (ongoing), Robot-assisted endomicroscopy (2010-2013), Beating heart intracardiac cardioscopy-guided interventions (2015-2019), and Intuitive control of active catheters (2014-2015). His work has resulted in numerous patents and collaborations with leading medical institutions worldwide, securing research funding for advancing surgical robotics technology. He actively participates in the academic community through invited talks and workshops, and maintains strong collaborations with institutions including Harvard Medical School, KU Leuven, and various French research entities, bridging theoretical robotics with practical clinical applications across multiple medical specialties.
Ozgur S. Oguz is an Assistant Professor at Bilkent University , Faculty of Computer Engineering, and the lead of the Learning for Intelligent Robotic Agents (LiRA) Lab . His research focuses on enhancing autonomous agents' capabilities in learning, reasoning, and planning, particularly for robotics applications. Education : PhD in Computer Science from TU Munich , studies at University of British Columbia (UBC) and Koç University , postdoctoral work at University of Stuttgart and Max Planck Institute for Intelligent Systems . His research explores algorithms for autonomous decision-making, with emphasis on deep learning , reinforcement learning , and robotics . Recent work includes diffusion-based reinforcement learning , hindsight experience prioritization , and hybrid manipulation planning , often addressing challenges in sequential task execution and tactile-based control. Key trends in his publications revolve around robotic manipulation , motion planning , and human-robot interaction . He has contributed to conferences like NeurIPS , ICRA , IROS , and journals such as IEEE TRO and Scientific Reports .
Trenton R. Foster, M.D., is an Associate Professor of Surgery at Mayo Clinic College of Medicine, serving as a Consultant in the Division of Endocrine Surgery within the Department of Surgery. He holds multiple leadership positions including Associate Program Director for the General Surgery Residency Program and Associate Director of Student Clerkships Programs. Dr. Foster is also the Physician Lead for the Collaborative Endocrine Surgery Quality Improvement Program (CESQIP) and serves on several important committees including the Clinical Competency Committee and the Department of Surgery Equity, Inclusion, and Diversity Committee. Dr. Foster's research focuses on optimizing surgical management of endocrine disorders, with particular emphasis on determining appropriate surgical extent for thyroid cancer, improving preoperative localization for parathyroid disease, and refining diagnostic approaches for adrenal tumors. His work utilizes national and institutional databases to understand disease behavior and improve patient outcomes through evidence-based practice. Analysis of Dr. Foster's recent publications (2023-2025) reveals a strong focus on clinical outcomes research across the spectrum of endocrine surgery. His work addresses critical questions regarding optimal surgical approaches for thyroid, parathyroid, and adrenal conditions, with particular attention to minimally invasive techniques, long-term outcomes, and quality improvement initiatives. The research demonstrates expertise in analyzing complex surgical datasets to derive practical clinical insights that directly impact patient care. His scientific achievements include: 2025 Focused Practice Designation in Adult Complex Thyroid and Parathyroid Surgery from the American Board of Surgery 2019 Dennis Wasson, M.D. Award for Outstanding Graduating Chief Resident from Yale University Multiple research awards from 2015-2016 including the SVS Foundation Resident Research Prize and Department of Surgery Best Basic Science Research Award at Yale Golden Key National Honor Society membership during undergraduate studies Dr. Foster actively mentors residents and medical students through his roles in the General Surgery Residency Program and student clerkships. He collaborates extensively with colleagues in endocrinology, radiology, and pathology to provide comprehensive, multidisciplinary care for patients with endocrine disorders. His research directly informs clinical practice, leading to improved preoperative evaluation, optimized surgical approaches, and enhanced postoperative care protocols while maintaining safety and effectiveness.
John Valasek is a Professor in the Department of Aerospace Engineering at Texas A&M University, holding the Drs. L. Diane '88 and John E. Hurtado '91 Professorship. He directs the Vehicle Systems & Control Laboratory (VSCL) and serves as Site Director for the NSF Center for Autonomous Air Mobility and Sensing (CAAMS) and the FAA Center for General Aviation Research (PEGASAS). His research focuses on autonomous control systems, UAV navigation, and cybersecurity for aerospace vehicles. Valasek earned his Ph.D., M.S., and B.S. in Aerospace Engineering from the University of Kansas (1995) and California State Polytechnic University (1986). Education: Ph.D., Aerospace Engineering, University of Kansas - 1995 M.S., Aerospace Engineering, University of Kansas - 1990 B.S., Aerospace Engineering, California State Polytechnic University - 1986 Research Interests: Autonomous systems, nonlinear control, vision-based navigation, UAV control, bio-nano materials control, and aerospace systems engineering. Key Contributions: Over 100 invited lectures/seminars, leadership in NSF-funded research centers, and development of advanced control algorithms for aerospace systems. Notable publications include work on reinforcement learning for autonomous systems and real-time system identification for UAS. Awards: John Leland Atwood Award (2015) McElmurry Outstanding Teaching Award (2001, 2004, 2014) Engineering Hall of Fame inductee (2019) Advising & Grants: Advised over 60 graduate students, including recent NSF GRFP winner Evelyn Madewell. PI on multi-million-dollar grants, including the NSF CAAMS project and Air Force-funded research on autonomous systems. Labs & Teams: Directs the Vehicle Systems & Control Laboratory (VSCL), focusing on low-cost attritable aircraft technology and autonomy. Collaborates with industry partners like Stratolaunch and VectorNav through CAAMS initiatives.
Imraan Faruque is an Associate Professor in the Department of Mechanical and Aerospace Engineering at Oklahoma State University (OSU), part of the College of Engineering, Architecture and Technology (CEAT). His research focuses on biologically-inspired flight control systems, engineered autonomy for unmanned aerial vehicles (UAVs), and the integration of sensory feedback mechanisms in autonomous systems. Education: Faruque holds a Ph.D. and M.S. in Aerospace Engineering from the University of Maryland (2011 and 2010) and a B.S. in Aerospace Engineering from Virginia Tech (2006). Research Interests: His work emphasizes bio-inspired solutions for aerial autonomy, including swarm coordination, gust-aware flight control, and human-autonomy interaction. Key areas include unmanned systems design, visual feedback algorithms, and adaptive control strategies derived from insect flight dynamics. Awards: He has received notable accolades such as the ONR Young Investigator Award (2019), AIAA Hal Andrews Young Engineer/Scientist Award (2017), and multiple 'Best in Session' recognitions at major conferences. His team also secured 1st Place in the International Aerial Robotics Championship (2005). Publications: Faruque’s research spans topics like orbital debris management, swarm intelligence, and tornado sensing with UAVs. His work bridges biological principles and engineering, with applications in aerospace, robotics, and environmental monitoring.
Gijs Krijnen serves as a Professor at the University of Twente within the Faculty of Electrical Engineering, Mathematics and Computer Science, based in Room Carré 3435 with contact email gijs.krijnen@utwente.nl. His research spans advanced engineering domains including: Additive manufacturing 3D printed sensors & actuators Embedded sensing systems Parametric & nonlinear transduction mechanisms Bio-inspired control algorithms Wearable & soft robotics platforms Current initiatives involve Mission I.A.M., Wearable Robotics, IRE, and the RaM laboratory, driving innovation in robotic sensing and actuation. No scientific awards were documented in the source material. Advising activities and research funding details remain unspecified in the provided information. The RaM laboratory constitutes his primary research environment for developing integrated robotics and mechatronics solutions.
Lee M. Miller is a Professor and Vice Chair of Academic Affairs in the Department of Neurobiology, Physiology and Behavior at the University of California, Davis, affiliated with the Center for Mind and Brain. His research focuses on neuroengineering, computational neuroscience, and neural mechanisms underlying attention, speech processing, and multisensory integration. Research interests include the development of neural prosthetics, decoding of neuromuscular signals for prosthetic control, and understanding how auditory and visual systems interact during speech perception and attentional processes. His work bridges clinical applications (e.g., cochlear implants) with fundamental neuroscience, leveraging tools like electrophysiological recordings, EEG/MEG, and advanced signal processing techniques. Recent publications highlight innovations in electromyographic speech neuroprosthetics, the topology of neuromuscular signals, and the neural basis of speech-in-noise processing. Miller’s studies emphasize translational potential, such as improving speech synthesis from brain signals and designing haptic feedback systems for motor coordination. His contributions have advanced understanding of neural mechanisms in sensory integration, auditory attention, and the impact of cognitive factors on perception. Miller maintains a lab dedicated to these interdisciplinary efforts, with a focus on both basic science and clinical applications.
Arri Priimägi is a Professor at Tampere University's Faculty of Engineering and Natural Sciences, leading the Smart Photonic Materials research group. He focuses on functional soft materials, particularly light-activated systems for applications in soft robotics, photonics, and biomaterials science. His interdisciplinary work bridges physics, chemistry, and engineering, emphasizing collaboration to advance materials for future technologies. Education: PhD in Applied Physics from Helsinki University of Technology (2009), MSc in Physics from Tampere University of Technology (2004). His career includes postdoctoral research in Japan (Tokyo Institute of Technology) and Italy (Politecnico di Milano). Research Interests: Design of stimuli-responsive materials, light-driven actuators, and bioinspired systems. Key projects include ERC Starting Grant-funded work on tunable photonic structures and an ERC Proof-of-Concept Grant for optical humidity sensing. He leads the Chemistry & Advanced Materials research cluster and contributes to the PREIN Flagship in photonics. Awards : Academy of Finland Award for Scientific Courage (2018) ERC Starting Grant (2016) Outstanding Doctoral Dissertation Award (2009) Grants & Projects : ERC Proof of Concept: Optical Sensing of Humidity (2018–2020) ERC Starting Grant: Tunable Photonic Structures (2016–2021) Academy of Finland Fellowship: Halogen-Bonded Materials (2014–2019) Labs/Teams: Active in the Smart Photonic Materials group and collaborates internationally on soft robotics and photonic materials.
Brenna D. Argall is an Associate Professor of Computer Science, Mechanical Engineering, and Physical Medicine & Rehabilitation at Northwestern University, and a Faculty Research Scientist at the Shirley Ryan AbilityLab. Her research focuses on assistive and rehabilitation robotics, with an emphasis on human-robot interaction, shared autonomy, and intelligent control systems. She holds a PhD in Robotics from Carnegie Mellon University and has held postdoctoral fellowships at EPFL (Switzerland) and the NIH. Education: PhD in Robotics, Carnegie Mellon University (2009) Postdoctoral Fellow, EPFL (2009–2011) B.S. in Mathematics, Carnegie Mellon University (2002) Affiliations: Director, Argallab (Assistive & Rehabilitation Robotics Laboratory) Member, Northwestern Center for Robotics and Biosystems Advisor, Northwestern MS in Robotics Program Her research explores dynamic autonomy allocation , shared control systems , and interface-aware robotics , with applications in rehabilitation and assistive devices. Key projects include wheelchair automation, robotic arm control, and body-machine interfaces for users with motor impairments. Research Highlights: NSF CAREER Award (2016) AIMBE Fellow (2020) "40 under 40" Innovator (Crain’s Chicago Business) Publications emphasize human-centered robotics, including over 50 peer-reviewed articles on topics like intent inference, assistive autonomy, and teleoperation assistance. Current lab efforts prioritize interface-aware systems and customizable shared control to enhance accessibility for users with disabilities.
Philippe Souères is a Researcher at LAAS-CNRS (Laboratory for Analysis and Architecture of Systems) within the University of Toulouse. He leads the Gepetto team, focusing on advanced robotics, humanoid motion generation, and the integration of human biomechanics into robotic systems. His work bridges robotics, neuroscience, and biomechanics, emphasizing optimal control, sensor-based systems, and human-robot interaction. Research interests include robot control (optimal control, nonlinear systems), neurosciences (human motor control, sensorimotor integration), and biomechanics (organization of human movement). Notable contributions include models for humanoid locomotion, human-like motion generation using inverse dynamics, and studies on task-dependent balance in humans and robots. Souères has authored/co-authored over 50 publications, including award-winning work on human movement modeling for robotics. He has supervised numerous PhD students and contributed to projects like the EAR initiative (Robot Audition) and the development of the Pyrène humanoid robot. His research also extends to aerial robotics, ducted fan vehicles, and interdisciplinary collaborations with neuroscientists and biomechanics experts. Awards include the Best Conference Paper Award (2010) for integrating human movement invariants into humanoid robotics. Souères is actively involved in academic outreach, appearing in media discussions on robotics ethics and technological innovation.
