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Dmitry BerensonView profile

Associate Professor

• Robotics
• Motion Planning
• Machine Learning
• +3 more

Dmitry Berenson is an Associate Professor in the Robotics Department and Electrical Engineering and Computer Science Department at the University of Michigan. He holds a B.S. from Cornell University (2005) and a Ph.D. from Carnegie Mellon University (2011). His research focuses on algorithms for robotic manipulation, motion planning, and control, emphasizing integration with real-world systems and open-source distribution. He has received the IEEE RAS Early Career Award and NSF CAREER Award. His academic journey includes postdoctoral work at UC Berkeley (2012) and faculty positions at Worcester Polytechnic Institute (2012-2016). He leads the ARM Lab, exploring topics such as deformable object manipulation, tactile control, and learning-based planning. Teaching responsibilities include courses like ROB 502 (Programming for Robotics), EECS 465 (Algorithmic Robotics), and ROB 520 (Motion Planning). Education: B.S., Electrical and Computer Engineering, Cornell University (2005) Ph.D., Robotics Institute, Carnegie Mellon University (2011) Postdoctoral Research, UC Berkeley (2012) Research Interests: Learning and motion planning for manipulation Control theory and optimization Deformable object interaction Robot perception and tactile systems Key Contributions: Development of algorithms for manipulation under uncertainty Advances in motion planning with contact feedback Integration of learning with classical robotics methods Recent publications emphasize probabilistic modeling, tactile-driven control, and generalization in learned dynamics. His work addresses challenges in cluttered environments, deformable objects, and safe human-robot collaboration.

Juan Andrade CettoView profile

Researcher

• Mobile Robotics
• Computer Vision
• Neuromorphic Systems
• +3 more

Juan Andrade Cetto is a Researcher at the Institute of Robotics and Industrial Informatics (IRI), part of the Spanish National Research Council (CSIC). He previously served as Director of IRI from 2014 to 2020. His expertise spans mobile robotics, computer vision, and neuromorphic systems. He holds a BSEE from CETYS University (1993), an MSEE from Purdue University (1995), and a PhD in Robotics from the Universitat Politècnica de Catalunya (UPC, 2003), recognized with the EURON Georges Giralt Best PhD Award in 2005. Research Interests: - Mobile Robotics and Autonomous Systems - Event-based Vision and Neuromorphic Sensors - Real-time Sensor Fusion and SLAM - Control Systems for Energy Conversion (e.g., PEM Fuel Cells) - Probabilistic Methods for Robotics and Computer Vision Recent Research Trends: His work emphasizes neuromorphic computing and event-based systems for robotics applications, including optical flow estimation, ego-motion tracking, and real-time SLAM. Collaborations include EU projects like ALLIES (AI for Sustainable Development Goals) and RAMON LLULL (AIRA Postdoctoral Programme). He leads the BOMBUS project (Perception and Navigation for Agile Robotics, 2024–present). Scientific Awards: EURON Georges Giralt Best PhD Award 2005 Grants & Leadership: Principal Investigator in multiple national/EU projects including BOMBUS (CSIC) and ALLIES (European). Advising: - Current Students: José Agustín Aguilar Plazaola (Fuel Cell Control), Raquel De Frutos Arranz (Event Camera-based Collision Avoidance) - Past Students: Not explicitly listed in provided text. Labs & Teams: Active in IRI’s Robotics and Industrial Informatics research groups, focusing on applied robotics and sensor systems.

• Robotics
• Control Systems
• Medical Engineering
• +3 more

Liangjing Yang is an Adjunct Associate Professor at the University of Illinois at Urbana-Champaign and an Assistant Professor at Zhejiang University. He holds a Doctor of Engineering from the University of Tokyo (2014), a Master of Engineering from the National University of Singapore (2011), and a Bachelor of Engineering from the same institution (2008). His academic positions include research fellowships at MIT, SUTD, and the University of Tokyo, alongside his current faculty roles. His research focuses on robotics, control systems, and medical engineering , with applications in image-guided surgery, human-robot interaction, and precision engineering. Key areas include robotic micromanipulation, adaptive control strategies, and vision-based tracking systems for surgical navigation. Yang's teaching contributions include courses such as Resident Instruction Dynamics of Mechanical Systems , Signal Processing , and Control Systems at ZJUI (Zhejiang University-UIUC Institute). He has received accolades like the First Prize in ZJU-UIUC Junior Faculty Course Design Competition (2022) and the SUTD-MIT Postdoctoral Fellowship (2016) . His research articles span topics like robotic solutions for 3D printing, medical imaging integration, and collaborative human-robot systems. Notable work includes Detect-Remove-Replace: A Robotic Solution That Enables Unmanned Continuous 3D Printing (2022) and Review on Vision-Based Tracking in Surgical Navigation (2020).

Marcus HolzingerView profile

Professor

• Space Policy
• Space Situational Awareness
• Information Theory
• +4 more

Dr. Marcus Holzinger is the Joseph T. Negler Professor and Hatfield Endowed Professor in Space Policy & Law at the University of Colorado Boulder's Department of Aerospace Engineering Sciences. He leads the Colorado Center for Astrodynamics Research (CCAR) and the VADeR Laboratory, focusing on advancing space exploration through interdisciplinary research in space policy, autonomy, and space situational awareness. His work emphasizes collaboration and sustainable practices in space. Education: PhD in Aerospace Engineering Sciences, University of Colorado Boulder (2011) MS in Aeronautics & Astronautics Engineering, University of Washington (2005) BS in Aeronautics & Astronautics Engineering, University of Washington (2003) Research Interests: Space Policy & Law Space Domain Awareness Autonomy & Decision Support Systems Cislunar Space Dynamics Information Theory & Estimation Space Traffic Management Recent Research Trends: Holzinger’s work prioritizes cislunar space exploration and decentralized decision-making for space systems, with applications in orbital debris mitigation, sensor tasking, and spacecraft autonomy. His publications frequently address challenges in initial orbit determination and spacecraft maneuver detection . Awards: American Astronautical Society Fellow (2022) AIAA Associate Fellow (2018) AFOSR Young Investigator Award (2017) Advising & Labs: Holzinger mentors students in the STARLIT and VADeR Observatories. Notable advisees include Sam Fedeler (2023 PhD) and Katie Melbourne (PhD student). His labs develop technologies like astrographic mapping and sensor networks for space surveillance. Labs/Teams: CCAR and the VADeR Lab collaborate on projects funded by NASA, AFRL, and industry partners, emphasizing hardware-in-the-loop testing and space policy frameworks.

Christian VogtView profile

Lecturer

• IoT and Embedded Systems
• Wireless Sensor Networks
• Medical Electronics
• +3 more

Dr. Christian Vogt Dr. Christian Vogt is a Lecturer at the Department of Information Technology and Electrical Engineering within the Center for Project-Based Learning at ETH Zürich. His research focuses on IoT systems, embedded electronics, and wearable technology with applications in agriculture, healthcare, and urban computing. He specializes in energy-efficient sensor networks, flexible electronics, and real-time data transmission systems. Research Interests Vogt's work bridges hardware innovation and software optimization, emphasizing practical implementations through project-based learning. Key areas include: IoT and Wireless Sensor Networks Low-power embedded machine learning Wearable biomedical devices Flexible/stretchable electronics Ultra-wideband and radar-based sensing Publications Recent work highlights energy-efficient livestock monitoring systems using LoRa, battery-free sensor nodes powered by human body energy, and real-time gesture recognition with novel sensors. His research often involves interdisciplinary collaborations between computer science, electrical engineering, and biomedical applications. Affiliations ETH Zürich - Center for Project-Based Learning Department of Information Technology and Electrical Engineering Contact: christian.vogt@pbl.ee.ethz.ch

Felipe MartinsView profile

Senior Lecturer

• Mobile Robot Control
• Educational Robotics
• Robotics Competitions
• +6 more

Felipe Martins is a Senior Lecturer-Researcher at Hanze University of Applied Sciences, active in both teaching and the Sensors and Smart Systems research group. He holds a PhD in Electrical and Electronic Engineering (2009) and has a background in industrial automation engineering (1999-2003). His work contributes to UN Sustainable Development Goals through educational robotics and automation. PhD: Modeling and Dynamic Compensation of Mobile Robots (Federal University of Espirito Santo) MSc: Control of Induction Generators via Fuzzy Logic BSc: Microcontroller-based Motor Control Research spans mobile robot control , educational robotics , autonomous navigation , and sensor networks . Recent publications focus on LiDAR data processing (2024), reinforcement learning for robotic applications (2022), and machine learning-driven localization (2023). He received Best Paper Awards at OL2A 2023 and WRE 2018. As a part-time teacher at University of Groningen (since 2022) and visiting researcher at CeDRI (2023), he bridges academia and industry. His editorial roles include guest editorships at Automation (MDPI) and Sensors journals. He co-organized RoboCup Junior events (2013-2021) and developed open-source robotics education tools like RoSoS A free simulator (2016).

Gustavo B. H. de AzevedoView profile

Academic

• Weather-sensing UAS (WxUAS)
• Autonomous and Control Systems
• Sensors and Transducers
• +5 more

Gustavo B. H. de Azevedo is a Research Assistant Professor in the Department of Mechanical and Aerospace Engineering at Oklahoma State University (OSU), affiliated with the College of Engineering, Architecture, and Technology (CEAT). His expertise spans weather-sensing UAS systems, autonomous control systems, and cross-disciplinary education. Education: PhD in Electrical and Computer Engineering, University of Oklahoma (2024) MSc in Electrical and Computer Engineering, University of Oklahoma (2020) BSc in Computer Engineering, Pontifícia Universidade Católica do Rio de Janeiro, Brazil (2017) Research Interests: Development of weather-sensing unmanned aerial systems (WxUAS) for atmospheric monitoring Optimization of autonomous control systems in harsh weather conditions Integration of low-cost sensors for environmental data collection Education innovations in engineering and cross-disciplinary STEM fields Awards: American Meteorological Society Award for contributions to ASTM standards on weather information for NextGen aircraft integration Advising & Grants: Active contributor to field campaigns such as LAPSE-RATE and the 3D Mesonet concept Collaborates with organizations like ASTM International and the American Institute of Aeronautics and Astronautics Labs/Teams: Involved in OSU's weather-sensing UAS development teams and the 3D Mesonet initiative, focusing on autonomous atmospheric profiling networks.

Daniel GöhringView profile

Professor

• Autonomous Vehicles
• Mobile Robotics
• Computer Vision
• +6 more

Prof. Daniel Göhring is a professor in the Department of Computer Science at the Free University of Berlin, leading the Autonomous Cars Lab and part of the Dahlem Center for Machine Learning and Robotics. His research emphasizes robotic perception, object tracking, and real-time planning under computational constraints, with a focus on autonomous vehicles and cooperative systems. Education: Bachelor's/Master's in Robotics (exact program unspecified) PhD in Computer Science at Humboldt University Berlin Postdoctoral Research at International Computer Science Institute (ICSI), Berkeley, CA Research Interests: Daniel's work integrates machine learning and sensor technologies like LiDAR and cameras to address challenges in autonomous driving. Key areas include SLAM algorithms, trajectory prediction, cooperative perception, and real-time systems. He explores how limited sensor data and computational resources can be optimized for dynamic traffic environments. Grants and Projects: Leader of the Autonomous Cars Lab Involved in EU-funded projects such as H2020 HIVEOPOLIS and KIS-M (AI-based mobility systems) Past projects include CRTX (recycling optimization), Open.Make (open hardware), RoboFish (biological swarm analysis), and SAFARI Awards: Best Poster Award at IAAS Workshop 2024 Best Paper Award at ICAIR-CACRE 2019 Teaching: He has taught courses such as Image Processing, Robotics, and Advanced Robotics. Recent semesters include modules on self-supervised learning, autonomous vehicle research, and continuous learning software projects. Labs and Teams: Daniel heads the Autonomous Cars Lab and collaborates with the BioRobotics Lab, focusing on interdisciplinary projects like 'Robots Communicating with Fish' and 'Open Hardware for FAIR Robotics.'

Gaurav SukhatmeView profile

Professor

• Robotics
• Artificial Intelligence
• Computer Science
• +6 more

Gaurav Sukhatme is a Professor of Computer Science and Electrical and Computer Engineering at the University of Southern California (USC), serving as Executive Vice Dean of the USC Viterbi School of Engineering and inaugural Director of the USC School of Advanced Computing. He holds the Donald M. Aldstadt Chair in Advanced Computing. His academic roles include former Chair of the USC Computer Science Department (2012–2017) and co-director of the USC Robotics Research and Robotic Embedded Systems Laboratories. **Education:** Bachelor's in Computer Science and Engineering, Indian Institute of Technology Bombay M.S. and Ph.D. in Computer Science, University of Southern California **Research Interests:** His work focuses on networked robots, learning-based robotics, field robotics, and AI-driven systems. Key areas include multi-robot coordination, autonomous systems, and resilient control strategies for heterogeneous teams. He emphasizes human-centered computing and ethical implications of AI. **Article Trends:** Recent publications highlight advancements in zero-shot visual generalization, multi-robot navigation, reinforcement learning for manipulation, and decentralized trajectory planning. Themes include resilience in multi-robot systems, policy optimization, and leveraging large language models for robotics tasks. **Awards:** AAAS Fellow (2024) NSF CAREER Award (2002) IEEE Fellow (2010) Okawa Foundation Research Grant (2006) **Advising & Grants:** He has served as PI/co-PI on NSF, DARPA, and NASA grants, including leadership in the NSF-funded Center for Embedded Networked Sensing (CENS). His work bridges theoretical and applied robotics, emphasizing cross-disciplinary collaboration. **Labs & Teams:** Directs the USC Robotics Research Laboratory and collaborates widely with institutions like JPL. His team focuses on real-world applications in autonomous systems, environmental monitoring, and human-robot interaction.

• Wearable Robotics
• Exoskeleton Control Systems
• Biomechanics
• +4 more

Aaron J. Young is an Adjunct Associate Professor in the School of Electrical and Computer Engineering at Georgia Institute of Technology. His research focuses on wearable robotics, exoskeleton control systems, and biomechanical analysis. He specializes in integrating machine learning and AI to enhance mobility assistance technologies for individuals with physical impairments. Young's work emphasizes real-time systems, including gait estimation, intent recognition, and adaptive assistance strategies for prosthetics and exoskeletons. His projects address challenges in slope navigation, stair climbing, and energy-efficient movement, often collaborating with clinical and engineering teams to translate innovations into practical applications. Key areas of exploration include exosuit design for hazardous environments (e.g., DOE-EM operations), biomechanical evaluation of manual lifting tasks, and improving post-stroke gait rehabilitation. His research also tackles commercialization barriers for wearable robotics, emphasizing sensor limitations and user-independent control systems. Recent publications highlight advancements in deep learning for slip detection, data-driven gait phase estimation, and task-agnostic exoskeleton control. His contributions aim to reduce metabolic costs, enhance user safety, and bridge the gap between robotics and clinical needs.

Ignacio CarluchoView profile

Assistant Professor

• Robotics
• Autonomous Systems
• Reinforcement Learning
• +3 more

Ignacio Carlucho is an Assistant Professor at Heriot-Watt University's School of Engineering & Physical Sciences, affiliated with the Institute of Sensors, Signals & Systems. He holds a PhD from the National University of Central Buenos Aires (2019) and completed postdoctoral research at Louisiana State University (2020–2021) and the University of Edinburgh (2021–2023). His research focuses on intelligent robots, particularly in underwater robotics, reinforcement learning, multi-agent systems, and cooperative autonomy. **Education:** PhD in Robotics, National University of Central Buenos Aires, 2019 Postdoctoral Researcher, Louisiana State University, 2020–2021 Postdoctoral Researcher, University of Edinburgh, 2021–2023 **Research Interests:** Underwater Robotics Reinforcement Learning Multi-Agent Systems Autonomous Systems Human-Robot Interaction Simulation Frameworks (e.g., MarineGym, Stonefish) His work emphasizes cooperative robotics, underwater vehicle control, and ad hoc teamwork in dynamic environments. **Publications:** Over 46 research outputs, with recent contributions focusing on underwater robotics simulation, reinforcement learning algorithms, and digital twins for teleoperation. Key frameworks include MarineGym (underwater RL platform) and Stonefish (machine learning support for marine robotics). **Awards:** No scientific awards explicitly listed in the provided texts. **Advising & Grants:** Accepting PhD students in reinforcement learning, robotics, and multi-agent systems. Collaborations include projects on underwater vehicle autonomy and ad hoc teamwork. **Labs & Teams:** Active in the Institute of Sensors, Signals & Systems, contributing to interdisciplinary robotics and marine technology initiatives.

Gennaro NotomistaView profile

Assistant Professor

• Robotics
• Control Systems
• Optimization
• +3 more

Gennaro Notomista is an Assistant Professor at the University of Waterloo, part of the Full-time faculty. His research focuses on robotics, control systems, and multi-agent coordination. Key areas include swarm intelligence, optimization of robotic tasks, and safety-critical control algorithms. He is affiliated with the Robotarium, a remotely accessible multi-robot testbed, and explores applications in autonomous vehicles, environmental monitoring, and creative robotics projects like music-driven swarm painting. His work emphasizes energy-efficient task allocation, decentralized control strategies, and safe navigation frameworks. Notable contributions include advancements in control barrier functions for ensuring safe operation and resilient task execution in dynamic environments. Recent publications address challenges in persistent environmental monitoring, long-duration autonomy, and the design of wire-traversing robots. Notomista’s research also bridges robotics with real-world applications, such as using robot swarms to model epidemiological dynamics and enhance teleoperation systems. His interdisciplinary approach combines optimization theory, machine learning, and mechanical design to tackle complex robotic systems challenges.

Stephen L. SmithView profile

Professor

• Robotics
• Artificial Intelligence
• Control Systems
• +3 more

Stephen L. Smith is a Professor and Tier 2 Canada Research Chair in the Department of Electrical and Computer Engineering at the University of Waterloo. He serves as Co-Director of the Waterloo Artificial Intelligence Institute, leading research in robotics and AI. His work focuses on autonomous systems, multi-robot coordination, and human-robot interaction, with applications in navigation, control systems, and collaborative task planning. Smith's research explores challenges such as path planning in uncertain environments, persistent monitoring, and adaptive decision-making. His contributions include algorithms for robot navigation in ice-covered waters, real-time replanning under constraints, and optimizing multi-agent systems for efficiency and safety. Key scientific awards include the Tier 2 Canada Research Chair designation. His research also addresses human-centric aspects, such as studying user preferences in collaborative tasks and developing frameworks for learning user intent through interaction.

Steven WaslanderView profile

Associate Professor

• Autonomous Vehicles
• Robotics
• Simultaneous Localization and Mapping (SLAM)
• +12 more

Steven Waslander is an Associate Professor at the University of Toronto Institute for Aerospace Studies and an Adjunct Professor in Mechanical and Mechatronics Engineering at the University of Waterloo. He previously directed the Waterloo Autonomous Vehicles Laboratory (WAVELab). Education: Doctorate in Aeronautics and Astronautics from Stanford University (2007) Master's in Aeronautics and Astronautics from Stanford University (2002) Bachelor's in Applied Mathematics and Mechanical Engineering from Queen's University (1998) His research focuses on autonomous vehicles , including aerial and ground systems, with an emphasis on Simultaneous Localization and Mapping (SLAM) , nonlinear estimation , multi-robot systems , and autonomous driving . He also explores convolutional and recurrent neural networks for motion planning and object detection . Recent articles highlight trends in 3D detection , LiDAR-based tracking , neural radiance fields for autonomous driving, and model-agnostic pretraining for motion prediction. These works span journals like IEEE Transactions on Robotics and conferences such as ICCV and NeurIPS . Professor Waslander has advised the University of Waterloo Robotics Team, mentored students like Evan Cook, Barza, and Marc, and collaborated with industry partners including Aeryon Labs and Clearpath Robotics. He is a member of the NSERC Canadian Field Robotics Network .

Suman BistaView profile

Research Fellow

• Robotics
• Computer Vision
• SLAM Algorithms
• +3 more

Dr. Suman Bista is a Research Fellow at the QUT Centre for Robotics, Queensland University of Technology. He holds a PhD in Signal Processing and Telecommunications from Université de Rennes. His primary research focuses on robotics, computer vision, and SLAM algorithms, with notable contributions to indoor navigation systems, semantic segmentation, and medical imaging applications. He has published extensively in top-tier journals like the International Journal of Robotics Research and conferences such as IEEE/RSJ IROS. Key research interests include visual servoing, resource-constrained robotics, and simulation environments for active scene understanding. His work bridges theoretical advancements with practical applications in autonomous systems and healthcare diagnostics. Dr. Bista’s publications highlight innovative solutions in robotics navigation, including the development of BenchBot environments for simulating real-world robotics challenges. His research emphasizes cross-disciplinary approaches, integrating computer vision techniques with robotics hardware design.