Eyal Amir

Eyal Amir is an Associate Professor at the University of Illinois at Urbana-Champaign, specializing in Artificial Intelligence with a focus on probabilistic reasoning, machine learning, and multi-agent systems. His work integrates formal logic, game theory, and cognitive science to address challenges in social dynamics, robotics, and educational technology.

Research interests include deception detection in social games, bullying analysis through computer games, and scalable inference methods for complex systems. His contributions span theoretical advancements in relational Kalman filtering, lifted inference, and probabilistic modeling, alongside applied projects in environmental monitoring and behavioral interventions.

Notable contributions include developing game-based methods for studying bullying and cyberbullying, real-time anomaly detection systems, and foundational work on logical filtering and knowledge representation. While no formal awards are listed here, his extensive publication record reflects impactful contributions to AI and interdisciplinary research.

Eyal's advising and grant activities are not explicitly detailed in the provided text, but his research often involves collaborations across computer science, psychology, and engineering domains. No lab or team affiliations are specified in the current data.