Regular biography
Negar Kiyavash is a Full Professor at École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the Department of Business / Management. She holds the Chair of Business Analytics and is based in ODY 1 01.1. Her research interests include causal inference and machine learning methods in econometrics, with a focus on their application in business analytics. She teaches courses such as Causal Inference (MGT-416) and Machine Learning Methods in Econometrics (MGT-424). She is also involved in PhD supervision and program committees at EPFL.
Scholar-generated biography
Negar Kiyavash is a researcher at École polytechnique fédérale de Lausanne (EPFL) with expertise in causality, applied probability, network forensics, random graphs, and time series. Her work focuses on understanding and modeling complex systems through probabilistic and causal frameworks. She has contributed to areas such as directed information graphs, network flow watermarking, and causal structure learning. Her research also explores secure authentication mechanisms, covert communication, and the analysis of network traffic for forensic purposes. Kiyavash's publications highlight her interest in developing robust statistical methods for inference and optimization in nonconvex and minimax problems.