Murad, M.M., and Y. Yilmaz. 2026. “Cluster-Aware Causal Mixer for Online Anomaly Detection in Multivariate Time Series”. International Conference on Machine Learning (ICML).
Secure and Intelligent Systems (SIS) Lab
At SIS Lab, we do interdisciplinary Machine Learning (ML) research with a focus on Real-Time Inference and Security Analysis for delay-sensitive applications.
Research Areas
Exploring cutting-edge topics at the intersection of Real-time ML and Cybersecurity.
We work on different formulations of Sequential Learning and Inference problems, namely real-time anomaly detection, reinforcement learning, and supervised learning (parametric hypothesis testing and change detection) with applications in several interdisciplinary topics, such as communication assistant for stroke-related speech disorders in collaboration with medical doctors, sea level rise scenario planning in collaboration with urban planners, and permafrost thaw monitoring with geoscientists.