Research Areas

Our core topics and methods

Computer Vision for Sports

Player and ball tracking, pose estimation, event detection

We design robust vision models for real-world broadcast and training data to extract actionable spatiotemporal insights.

tracking pose estimation event detection broadcast analysis

Machine Learning for Performance

Predictive and causal modeling for athlete and team performance

From forecasting and counterfactuals to interpretable models that support coaching and tactical decisions.

forecasting causal inference explainability optimization

Human-Centered AI & Fairness

Trustworthy systems to assist coaches, referees, and athletes

We study usability, transparency, and fairness of AI in sports, focusing on human-AI collaboration.

explainable AI fairness HCI sports officiating