Find Academic Supervisors

Kostas BekrisView profile

Professor

• Robotics
• Artificial Intelligence
• Computer Vision
• +7 more

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.

Fumiya IidaView profile

Researcher

• bio-inspired robotics
• evolutionary robotics
• soft robotics
• +3 more

Dr. Fumiya Iida is a researcher affiliated with the University of Cambridge , contributing to interdisciplinary research through Cambridge Reproduction and the Department of Engineering . His work spans bio-inspired robotics , soft robotics , and embodied intelligence , with a focus on biomechanics and human-robot interaction. His research integrates evolutionary robotics , reservoir computing , and tactile sensing , aiming to bridge engineering, physiology, and synthetic biology. Recent publications highlight innovations in Soft robotic actuation Robust control systems Multimodal sensor integration Human-robot collaborative tasks Dr. Iida's 15 most recent 2025 articles emphasize reservoir computing , soft sensor design , and adaptive motor coordination , reflecting his commitment to advancing embodied intelligence in robotics. No formal awards or student advisement details were found in the provided texts.

John BaillieulView profile

Professor

• Robotics
• Nonlinear control theory
• Mechanical systems control
• +6 more

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.

Noah J. CowanView profile

Professor

• Neuromechanics
• Robotics
• Neuroscience
• +5 more

Noah J. Cowan is a Professor of Mechanical Engineering at Johns Hopkins University's Whiting School of Engineering, with secondary appointments in Computer Science, Electrical & Computer Engineering, and Neuroscience. He is the founder and director of the Locomotion in Mechanical and Biological Systems (LIMBS) Laboratory, part of the Laboratory for Computational Sensing and Robotics. His research focuses on neuromechanics, robotics, and control theory, bridging neuroscience, biomechanics, and engineering. Cowan's work investigates how organisms achieve precise locomotion and applies these insights to advance robotics, neuroprosthetics, and rehabilitation technologies. Education: B.S. Electrical Engineering (Ohio State, 1995), M.S. and Ph.D. Electrical Engineering & Computer Science (University of Michigan, 1997/2001). Postdoctoral fellowship at UC Berkeley (2001–2003) before joining Johns Hopkins. Research Interests: Neuromechanics of motion, bio-inspired robotics, multisensory integration in animals (e.g., electric fish, Drosophila), and sensorimotor control in clinical contexts like cerebellar ataxia. His lab studies how neural circuits interact with biomechanics to produce movement, with applications to robotic design and neurological disorder treatments. Awards & Recognition: Presidential Early Career Award for Scientists and Engineers (2010), IEEE Fellow, NSF CAREER Award (2009), and multiple teaching and research excellence awards at Johns Hopkins. His work has been published in top journals like Nature , Proceedings of the National Academy of Sciences , and IEEE Transactions on Robotics . Outreach & Mentorship: Longtime mentor for high school and undergraduate students in STEM, leading programs like the Baltimore Ingenuity Project and WISE. Served as team leader for the STEM Achievement in Baltimore Elementary Schools (SABES) initiative. Key Projects: Development of the LIMBS Lab’s VR systems for animal studies, bioelectric navigation technologies for medical devices, and collaborations with clinicians on upper limb movement disorders. His team’s research on electric fish and fruit flies has revealed principles of adaptive control applicable to robotics and AI.

• Robotics
• Micro/Nanorobotics
• Physical Intelligence
• +3 more

Metin Sitti is a Professor and currently serves as a part-time adjunct professor at Koç University's Faculty of Medicine and Engineering. He is also the President of Koç University and Director of the Max Planck Institute for Intelligent Systems since 2014. His research spans robotics , micro/nanorobotics , physical intelligence , bio-inspired robotics , and materials science . Undergraduate: Boğaziçi University (Electrical and Electronics Engineering, 1992) Master's: Boğaziçi University (1994) PhD: University of Tokyo (Electrical Engineering, 1999) His research focuses on small-scale robotics for biomedical applications, including magnetic microrobot swarms , biohybrid systems , and functional materials . Recent publications emphasize 3D control , wireless actuation , and clinical translation of robotic systems. Scientific Awards : 2020 Scientific Breakthrough of the Year 2018 Koç University Rahmi M. Koç Science Medal 2014 IEEE/ASME Best Mechatronics Paper Award 2013/2012 World RoboCup Micro-Robotics First Prize He has advised numerous students and collaborates with institutions like Carnegie Mellon University and University of Stuttgart. His work integrates physical intelligence into miniature robots for medical imaging , drug delivery , and autonomous systems .

Tobi DelbruckView profile

Professor

• Neuromorphic Engineering
• Event-Based Vision Systems
• Silicon Retinas
• +6 more

Tobi Delbruck is a titular professor of physics and electrical engineering at ETH Zurich, where he leads the Sensors Group at the Institute for Neuroinformatics (INI) in Zurich, Switzerland. He collaborates closely with Shih-Chii Liu and Giacomo Indiveri as part of the 'hardware groups' at INI. Delbruck has also served as visiting faculty at Caltech and is a Fellow of the IEEE. His work focuses on bio-inspired and neuromorphic event-based sensory processing systems. Professor Delbruck's research spans multiple areas of neuromorphic engineering, with particular emphasis on event-based vision systems and low-power analog VLSI circuits. His work has significantly advanced the field of Dynamic Vision Sensors (DVS), which mimic the human retina's response to changes in brightness rather than capturing full frames. This approach enables extremely low-latency vision processing with minimal power consumption, making it ideal for high-speed applications and robotics. His research has applications in robotics, autonomous systems, and low-power embedded vision. Delbruck is an active contributor to the neuromorphic engineering community, co-organizing the annual Telluride Workshop on Neuromorphic Engineering and serving in leadership roles with IEEE. He has authored numerous influential publications and co-authored books including "Event-Based Neuromorphic Systems" and "Analog VLSI: Circuits and Principles." His jAER (Java Address-Event Representation) project provides open-source tools for real-time event-based sensory processing. Analysis of his recent publications shows a clear trend toward integrating event-based vision with deep learning techniques and applying these systems to practical robotics problems. His scientific achievements have been recognized with multiple awards including: IEEE Fellow Winner of Best Live Demonstration award at ISCAS 2012 Honorable Mention Award from Sensory Systems Technical Committee at ISCAS 2012 Overall Best Student Paper Award and Best Paper Award from Sensory Systems Technical Committee at ISCAS 2010 Winner of the 2006 ISSCC Jan Van Vessem Outstanding European Paper Award Professor Delbruck actively mentors students and has supervised numerous PhD and Master's theses in the areas of neuromorphic engineering and event-based vision systems. His group has secured significant research funding from various sources to support their innovative work in bio-inspired sensory processing. He teaches courses on "Electronics for Physicists II (Digital)" and "Neuromorphic Engineering," helping to train the next generation of researchers in this field. The Sensors Group at INI, which Delbruck leads, operates state-of-the-art facilities for designing and testing neuromorphic vision systems. The group maintains close collaborations with researchers worldwide and has developed several important open-source resources including the jAER project and bias generator design kits. Their work continues to push the boundaries of what's possible with event-based sensory processing, with applications ranging from high-speed robotics to low-power embedded vision systems.

Kevin KochersbergerView profile

Associate Professor

• Dynamics and control
• Autonomous aerial systems
• Applied aerodynamics
• +7 more

Dr. Kevin Kochersberger is an Associate Professor in the Department of Mechanical Engineering at Virginia Tech , with a career spanning academic research, technical innovation, and educational leadership. His work focuses on autonomous aerial systems , robotic control , and applied aerodynamics , particularly through the Uncrewed Systems Laboratory . Kochersberger's research has pioneered UAV-based radiation detection , 3D terrain mapping , and low-resource drone applications , including establishing the African Drone and Data Academy in Malawi . Education: Ph.D., Mechanical Engineering, Virginia Tech (1994) M.S., Mechanical Engineering, Virginia Tech (1984) B.S., Mechanical Engineering, Virginia Tech (1983) A.S., Engineering Science, Jamestown Community College (1981) Kochersberger's publications demonstrate expertise in UAV path planning , smart material actuation , and radiation source localization , with over $9M in research funding. His scientific awards include AIAA Associate Fellow (2009) and Aviation Week Aerospace Laureate (2003). Notable projects involve helicopter-deployable robotic systems and urban canyon navigation without GPS. Recent articles highlight BVLOS drone simulators , 2.5D terrain mapping , and autonomous negative obstacle traversal , reflecting his focus on real-time adaptive control and heterogeneous robotic systems . He teaches Drone Technology and Flight Operations and Advanced Design Projects , emphasizing student-driven innovation and industry collaboration .

• Adaptive structures
• Mechanical metamaterials
• Robotic materials
• +6 more

Andres F. Arrieta is an Associate Professor of Mechanical Engineering at Purdue University's School of Mechanical Engineering in West Lafayette, Indiana. He leads the Programmable Structures Lab and holds affiliations with multiple research areas including dynamics, advanced materials, and robotics. His research focuses on adaptive structures, mechanical metamaterials, and programmable systems. Education: Mechanical Engineer, Universidad de los Andes, Bogotá, 2006 Ph.D., University of Bristol, United Kingdom, 2010 Postdoctoral Research Fellow, ETH Zurich, 2012 Research Interests: His work emphasizes multistable structures, structural nonlinearity, and elastic instabilities. He explores applications in energy harvesting, morphing wings, and mechanical metamaterials. Recent trends include bio-inspired designs and smart materials for adaptive systems. Awards: 2019 ASME Best Paper Award (Bioinspired Materials) 2018 Gary Anderson Early Achievement Award 2017 Journal Cover Feature (Chiral Metastructure) 2012 ETH Postdoctoral Fellowship Labs/Teams: Leads the Programmable Structures Lab, focusing on innovative metastructures and adaptive robotics systems.

Tosiron AdegbijaView profile

Associate Professor

• Computer Architecture
• Embedded Systems Design
• Low-Power Embedded Systems
• +14 more

Tosiron Adegbija is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Arizona, where he serves as Director of Graduate Studies and Thomas R. Brown Endowed Fellow. He is a member of the Graduate Faculty and actively contributes to research and teaching in computer architecture and embedded systems. Education: PhD in Electrical and Computer Engineering, University of Florida, 2015 MS in Electrical and Computer Engineering, University of Florida, 2011 BS in Electrical Engineering, University of Ilorin, Nigeria, 2005 His research centers on energy-efficient computing with a focus on bio-inspired computer architecture , including spiking neural network (SNN) accelerators and in-memory computing. He also explores domain-specific architectures , adaptable memory systems , and microprocessor optimizations for IoT . His work leverages novel memory technologies like STT-RAM to enhance performance and reduce energy consumption in embedded and resource-constrained systems. Recent publications highlight trends in hybrid SNN acceleration, domain-specific accelerator generation, and system-level design space exploration. His research is increasingly focused on neuromorphic computing, automated hardware design, and ultra-efficient architectures using emerging materials like antiferromagnetic tunnel junctions. Scientific Awards: National Science Foundation (NSF) CAREER Award (2019) Elected IEEE Senior Member (2020) Best Paper Award at IEEE ISVLSI (2014) Teaching Award, University of Arizona (2018) ACM GLSVLSI Travel Award (2015) He advises numerous graduate and undergraduate students, many of whom have pursued careers at institutions like Pacific Northwest National Labs, Micron Technology, and Amazon. He has secured significant funding, including a $1.9M NSF FuSE2 grant for energy-efficient computing. His lab collaborates with UA Physics, CMU, and UNL. He has also developed educational tools for Chipyard and RISC-V, supporting hands-on learning in computer architecture. Labs and Research Teams: Leads a research group focused on bio-inspired and domain-specific computing, fostering innovation in energy-efficient hardware. The lab emphasizes hardware/software co-design, neuromorphic engineering, and real-world deployment in IoT and biomedical applications.

Rogério de LemosView profile

Senior Lecturer

• Resilient AI
• Self-adaptive software systems
• Authorisation infrastructures
• +7 more

Rogério de Lemos is a Senior Lecturer in Computing Science and Director of Postgraduate Research (PGR) at the School of Computing, University of Kent. He previously served as an invited assistant professor at the University of Coimbra, Portugal, and as a Senior Research Associate at the Centre for Software Reliability (CSR) at the University of Newcastle upon Tyne, UK. Dr. de Lemos' research focuses on architecting resilient systems, particularly in resilient AI, self-adaptive software systems, and authorization infrastructures. He belongs to both the Programming Languages and Systems Group and the Cyber Security Group at the University of Kent. His specific research interests include: Software engineering for self-adaptive systems assurances and resilience evaluation Dynamic generation of processes Handling insider threats using self-adaptive authorization Architectural abstractions for fault tolerance Verification and validation of dependable software architectures Software development for safety-critical systems Dependability and bioinspired computing His publication trends show increasing emphasis on practical applications of self-adaptive systems in cyber security contexts, with recent work spanning network traffic analysis, cryptographic function detection, and cloud-edge security architectures. His research bridges theoretical foundations with practical implementations, particularly in cyber security and resilient systems architecture. Dr. de Lemos currently leads the "Collaborative and Confidential Information Sharing and Analysis for Cyber Protection" project funded by the European Union's Horizon 2020 Programme. His past projects include "ADAAS: Assuring Dependability in Architecture-based Adaptive Systems" and multiple collaborations with NCR on sensor fusion and fault tolerance. As Director of Postgraduate Research, he oversees the School of Computing's research degree programs and likely supervises PhD students in resilient systems and cyber security, though specific student names are not listed in the available information.

Joseph A. CampbellView profile

Assistant Professor

• Explainable AI
• Robotics
• Machine Learning
• +3 more

Joseph A. Campbell is an Assistant Professor in the Department of Computer Science at Purdue University, leading the Collaborative AI for Machines and People (CAMP) Lab. He holds a Ph.D., M.S., and B.S. in Computer Science and Computer Engineering from Arizona State University. Before academia, he worked as a software engineer for five years. Prior to Purdue, he was a Postdoctoral Fellow at Carnegie Mellon University's Robotics Institute. His research focuses on explainable machine learning and robotics, particularly how agents use explanations for self-improvement and decision-making. Key areas include theory of mind in multi-agent systems, lifelong learning, and interpretable transfer learning. His work bridges robotics and AI, with applications in human-robot interaction and prosthetic control. Notable publications include advancements in reinforcement learning with language models, multi-agent collaboration frameworks, and methods for enhancing state estimation in robots. His research has been presented at top conferences like NeurIPS, EMNLP, and CoRL. Dr. Campbell maintains an active GitHub profile (joe-campbell) with repositories such as Interaction Primitives for robotics applications. His lab, CAMP, explores AI systems that collaborate effectively with humans and other machines.

Michael MilfordView profile

Professor

• Robotics
• Neuroscience
• Computer Vision
• +3 more

Professor Michael Milford is a robotics and computer vision expert at Queensland University of Technology (QUT), serving as Joint Director of QUT's Centre for Robotics. His research bridges robotics, neuroscience, and computer vision, focusing on biologically inspired navigation systems for autonomous vehicles and drones. He has pioneered projects like SeqSLAM and RatSLAM, emphasizing the synergy between biological intelligence and robotic systems. Research Interests: Milford explores navigation algorithms inspired by animal behavior, energy-efficient neural networks, and autonomous systems. His work aims to create robots capable of operating in dynamic environments through interdisciplinary collaboration with institutions like MIT, Harvard, and NASA's Jet Propulsion Laboratory. Awards & Recognition: Awarded the 2019 Batterham Medal and a $2.7M Australian Laureate Fellowship for his project on GPS-independent positioning systems. His work has produced highly cited papers in robotics and computer vision, including breakthroughs in visual SLAM and place recognition under varying conditions. Teaching & Collaboration: Milford mentors students in robotics and AI, launching initiatives like the STEM Storybook to inspire youth. He collaborates globally, emphasizing cross-disciplinary research to bridge gaps between fundamental and applied sciences. Labs & Projects: Leads QUT's Centre for Robotics, advancing technologies for autonomous systems. His projects explore neuromorphic computing, SLAM systems, and bio-inspired navigation, with applications in defense, transport, and environmental monitoring.

James Herbert-ReadView profile

Associate Professor

• Behavioural Ecology
• Marine Biology
• Collective Animal Behaviour
• +4 more

Dr James Herbert-Read is an Associate Professor and Whitten Lecturer in Marine Biology at the Department of Zoology, University of Cambridge. He serves as Deputy Head of Department (Postgraduate Education) and leads the Marine Behavioural Ecology Group. His research focuses on understanding how animals, particularly marine organisms, collect and process information from their environments to make behavioral decisions, with emphasis on social interactions, adaptation mechanisms, and ecological constraints. His group employs theoretical frameworks, controlled experiments, and quantitative field studies to investigate behavioral diversity in marine species. Key themes include collective behavior, predator-prey dynamics, camouflage strategies, and the impacts of environmental stressors on animal decision-making. Recent publications highlight work on lionfish vocalization mechanisms, cuttlefish camouflage, citizen science applications in marine research, and behavioral responses to visual and acoustic noise. Scientific awards and affiliations include: Whitten Lecturer in Marine Biology Associate Professor, University of Cambridge He has supervised research projects on topics such as: Social attraction in invasive fish species Evolution of coordinated movement Neurophysiological basis for leadership in shoals Maternal effects on offspring exploration

Zeynep TemelView profile

Assistant Professor

• Bio-Inspired Robotics
• Compliant Mechanisms
• Robotic Manipulation
• +3 more

Zeynep Temel is an Assistant Professor at Carnegie Mellon University's College of Engineering, jointly appointed in the Biomedical Engineering and Robotics Institute. She leads the Zoom Lab, focusing on bio-inspired compliant mechanisms for robotic systems. Current research emphasizes adaptable robots for complex environments through mechanical intelligence and embedded control . Key application areas include surgical robotics , search-and-rescue , and micromanipulation . Her work spans bio-inspired design, compliant robotics, and human-centered applications. Recent publications highlight advancements in: Swarm robotics for collaborative exploration Soft actuators using bioplastics and gelatin Dexterous manipulation via delta robot frameworks The Zoom Lab trains students in robotic fabrication and biological modeling, with members transitioning to roles in academia and industry.

• Computer Science
• Artificial Intelligence
• Machine Learning
• +9 more

Jim Torresen is a Professor at the Norwegian University of Science and Technology (NTNU), specializing in Computer Science, Artificial Intelligence, and Robotics. He earned his M.Sc. and Dr.ing. (Ph.D.) in computer architecture and design from NTNU in 1991 and 1996 respectively, followed by industry experience in hardware design before transitioning to academia in 1999. Research Interests: His work spans Machine Learning, Evolvable Hardware, and Ethical AI, with notable contributions to music technology, facial expression recognition, and healthcare monitoring systems. He actively explores interdisciplinary applications of AI in creative domains and clinical environments. Publications & Editorial Roles: Torresen has published extensively in journals like Frontiers in Artificial Intelligence and Genetic Programming and Evolvable Machines . He serves as a Topic Editor for Frontiers in Explainable AI and has editorial roles in robotics and biomedical AI domains.