Abstract

The availability of eye tracking sensors is set to explode, with billions of units expected in future eXtended (Virtual, Augmented, Mixed) Reality platforms. The presentation will discuss the basics of eye tracking sensors and why they are fundamental to eXtended Reality (XR) development. A vision for the future development and deployment of eye tracking in XR devices will be presented. The talk will also cover a variety of applications of XR under the Contextual and Behavioral AI umbrella that have the power to benefit society on a large scale when XR solutions are widely adopted.

Biography

Dr. Oleg Komogortsev is currently a Denise M. Trauth Endowed Presidential Research Professor and Regents’ and University Distinguished Professor of Computer Science at Texas State University. He conducts research in eye tracking ecosystem with a focus on user understanding via authentication and state detection, privacy, behavioral AI, human–computer interaction, and usability. This work has thus far yielded a multitude of publications and patents. In addition, his research was supported by the National Science Foundation, National Institute of Health, National Institute of Standards, and various industrial sources.

His research has been covered by national media, including NBC News, Discovery, Yahoo, Livescience, and others. He was a recipient of 4 Google and 8 Facebook/Meta Research Awards. He has also received the National Science Foundation CAREER Award and the Presidential Early Career Award for Scientists and Engineers (PECASE) from President Barack Obama. Previously, over the period of 6 years Dr. Komogortsev worked as a Scientist at Meta Reality Labs where he contributed to such platforms as Meta Quest Pro, Aria, Orion Glasses and future products. He was inducted as senior elite member of National Academy of Inventors in 2025.

Abstract

Evaluating emerging technologies remains a key challenge for both research and real-world deployment. In eye-tracking systems, this challenge is particularly observed due to variability in performance, context of use, and data sensitivity. This talk outlines what is needed to effectively evaluate eye-tracking technologies, focusing on key dimensions such as performance, usability, robustness, and privacy. It reflects on current practices and discusses practical considerations for moving from controlled experiments to reliable real-world applications.

Biography

Dr. Yasmeen Abdrabou is a Postdoctoral Researcher and Team Leader at the Technical University of Munich (TUM), where she leads the VIVA project on evaluating emerging eye-tracking technologies. Her research focuses on human-computer interaction, with an emphasis on eye-tracking systems and security. Previously, she was a Senior Research Associate at Lancaster University on the ERC-funded GEMINI project, working on gaze and body interaction in HCI and immersive environments. She received her PhD from Universität der Bundeswehr München, where her research explored eye gaze-based security mechanisms. Her work spans academia and industry, including collaborations with the University of Glasgow and applied research with Tobii on eye-tracking systems.

Abstract

Sensing technologies in AR/VR typically require wearable smart sensors that rely on: compact form factor, fast and sufficient data acquisition, and low power consumption. I will talk about how low-power sensor technology from SynSense has joined these closely intertwined pillars. Building on extensive experience in event-based sensing and computing, I will review the strengths and potential of this technology for enabling real-time, seamless XR applications.  

Biography

Mina Khoei holds a Ph.D. in Computational Neuroscience and brings over 10 years of academic and industrial R&D experience at the intersection of neuroscience and engineering. Her work spans computational and experimental neuroscience, the design of energy-efficient and neuromorphic applications, spiking neural networks (SNNs), and event-based vision sensors.

Abstract

Event‑based vision sensors offer unique advantages for eye tracking due to their asynchronous operation, high temporal resolution, and low latency. In this talk, we explore the use of event sensors for eye‑tracking applications, with a focus on a system design and power consumption.  

Biography

Aziz Dziri is a Staff Computer Vision Engineer and Team Lead at Prophesee, where he specializes in leveraging event-based cameras for image deblurring, eye tracking, and object detection. Prior to this role, he led the SAVIM project at the VEDECOM Institute, focusing on perception systems for smart infrastructure and autonomous vehicle. Aziz earned his PhD from the French Alternative Energies and Atomic Energy Commission (CEA) under the supervision of Roland Chapuis and Marc Duranton, with research centered on object detection and tracking using smart cameras.