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Gabriel DiazView profile

Associate Professor

• Eye Tracking
• Human-Computer Interaction
• Neuroscience
• +5 more

Gabriel Diaz is an Associate Professor at the Chester F. Carlson Center for Imaging Science within the College of Science at Rochester Institute of Technology (RIT). His research focuses on eye tracking hardware and algorithms, the role of eye movements in visually guided actions, and the application of virtual reality (VR) and motion capture technologies to study human behavior. He teaches courses such as Probability and Statistics for Imaging , Vision & Psychophysics , and graduate-level research thesis courses. Dr. Diaz earned a BFA from Skidmore College, followed by an MS and PhD from Rensselaer Polytechnic Institute. His work spans neuroscience, computer science, and human-computer interaction, particularly in understanding how the brain processes visual information for movement and how this can be applied to rehabilitation for cortical blindness patients. Research Interests : Eye tracking, visual perception, predictive control in motor tasks, VR-based neurorehabilitation, and multisensory integration. Projects : Development of mobile eye tracking systems using machine learning (e.g., RITNet), rehabilitation of vision post-stroke via VR, and exploration of predictive strategies in high-speed steering and obstacle avoidance. The PerForM (Perception for Movement) Lab, directed by Dr. Diaz, leverages VR, motion capture, and eye tracking to conduct controlled naturalistic studies of human visual and motor systems. His recent publications emphasize the use of deep learning in eye tracking, cortical blindness rehabilitation, and perceptual learning in VR environments. Scientific Recognition : Member of RIT's PI Millionaires group, which contributed to the university's record $92M in research awards. Dr. Diaz mentors graduate students in Imaging Science and Computing and Information Science, and his research has been supported by grants from Meta/Facebook and the National Institutes of Health (NIH). He collaborates with institutions like the University of Rochester, Rensselaer Polytechnic Institute (RPI), and the University of Texas at Austin.

• Robot Learning
• Reward Inference
• Imitation Learning
• +5 more

Daniel Brown is an Assistant Professor at the University of Utah's Robotics Center and School of Computing . Previously, he completed a postdoc at UC Berkeley (2020–2022) and earned his PhD in Computer Science at UT Austin in 2020 under Scott Niekum . He leads the Aligned, Robust and Interactive Autonomy (ARIA) Lab , focusing on human-robot interaction and AI safety. Research interests include: Robot learning under uncertainty Reward inference from human input Robust policy optimization Bayesian reward inference High-confidence performance bounds Assistive AI systems Awards : NIH Trailblazer Award (2024) RSS Pioneer (2021) Teaching : CS 5955/6955 Advanced Artificial Intelligence (Spring 2025) CS 6300 Artificial Intelligence (Spring 2024) CS 5960/6960 Human-AI Alignment (Fall 2023)

• Signal Processing
• Computer Vision
• Robotics
• +5 more

Petros Maragos is a Professor at the National Technical University of Athens (NTUA) in the School of Electrical and Computer Engineering, where he directs the Division of Signals, Control and Robotics. He founded the Computer Vision, Speech Communication & Signal Processing Lab (1999) and the Hellenic Robotics Center of Excellence (2025). His research spans signal processing, computer vision, robotics, and machine learning, with 450+ publications and leadership in 50+ EU/Greek/US projects. Education includes a Dipl.Ing. from NTUA (1980), M.Sc./Ph.D. from Georgia Tech (1982/1985), and faculty positions at Harvard University (1985-1993) and Georgia Tech (1993-1998). Research Focus: Multimodal perception, nonlinear systems, assistive robotics, and deep learning. Recent work integrates tropical geometry with neural networks, robotic healthcare applications, and sign language technologies. Articles emphasize neural architectures, real-world robotics, and AI for social good. Awards: IEEE Fellow (1995), EURASIP Fellow (2010) IEEE W.R.G. Baker Prize (1995) NSF Presidential Young Investigator Award (1987-1992) CVPR/PETRA Best Paper Awards (2022-2025) Advising & Grants: Supervised 30+ PhDs and 130+ Master's students. Secured funding from EU Horizon 2020, NSF, and Greek national programs for projects like i-Walk (robotic mobility) and e-Prevention (mental health monitoring). Labs: Leads NTUA's Intelligent Robotics Lab and co-founded the Robotics Institute at Athena Research Center, focusing on human-robot interaction and perception systems.

Michael RyooView profile

Associate Professor

• Deep Learning
• Computer Vision
• Robotics
• +3 more

Michael Ryoo serves as a SUNY Empire Innovation Associate Professor in the Department of Computer Science at Stony Brook University while concurrently working as a Research Scientist with Google Brain's "Robotics at Google" team. Previously, he held positions as an Assistant Professor at Indiana University Bloomington and a Staff Researcher at NASA's Jet Propulsion Laboratory. His academic background includes a Ph.D. from the University of Texas at Austin (2008) and a B.S. from Korea Advanced Institute of Science and Technology (KAIST) in 2004. Ryoo's research centers on deep learning and computer vision with specific focus on convolutional neural network (CNN) models for video semantic understanding. His work bridges visual perception and robotic action through applications in robot perception, robot learning, and human-robot interaction. Key innovations involve developing efficient architectures for processing multimodal data and translating visual understanding into robotic control systems. Analysis of his 15 most recent publications reveals strong emphasis on multimodal AI integration, particularly vision-language models applied to robotics. His 2025 work shows significant advancement in token-efficient video representation, motion-controllable diffusion models, and zero-shot learning frameworks specifically designed for robotic control systems. The research trajectory demonstrates consistent focus on making video understanding more accessible and applicable to real-world robotic scenarios. Scientific awards: No awards were mentioned in the provided source material. Regarding academic advising, the source text does not list any students or mentoring activities. Similarly, no grant funding information is provided, though his dual academic-industry role suggests substantial research support. His Google Brain affiliation likely involves industry-sponsored research initiatives. Ryoo maintains active laboratory affiliations through Stony Brook's AI Innovation Institute and Google's Robotics team. His prior work at NASA JPL indicates experience with space robotics systems, while his current Google role focuses on large-scale robot learning infrastructure. The LAM SIMULATOR project represents his current focus on advancing data generation techniques for training large action models.

• Computer Vision
• Human-Computer Interaction
• IoT
• +6 more

Roberto Vezzani is an Associate Professor at the University of Modena and Reggio Emilia's Enzo Ferrari Department of Engineering, specializing in information processing systems (ING-INF/05). Previously Director of the Artificial Intelligence Research and Innovation Center (2018-2021), he holds a PhD in Information Engineering from the same institution. As senior member of AimageLab, he coordinates research on human-computer interaction using multi-sensor systems. His research spans: Computer vision for IoT and video surveillance Motion detection and action classification 3D vision with depth/thermal/event cameras Sensor fusion and automatic video annotation He leads competitive projects funded by Toyota, Ferrari, and EU programs, focusing on industrial applications of computer vision. Recent publications (2024-2025) demonstrate strong focus on 3D pose estimation, robot perception, and efficient embedded vision systems, with applications in automotive, robotics, and UAVs. Awards include: Best Paper - ICPR 2020 (IAPR) Best Paper - VISAPP 2020 Best Paper - THEMIS'2008 Industrial collaborations feature multi-year projects with Ferrari (RedVision lab), Toyota Europe, and Tetra Pak. Teaching includes courses on Computer Architecture, IoT systems, and industrial AI.