◾ Assistant Professor at UMRAM & Aysel Sabuncu Brain Research Center
◾ Assistant Professor at Department of Industrial Engineering
Taghi Khaniyev is an assistant professor at Bilkent University, Department of Industrial Engineering since September 2021. Prior to joining Bilkent, he was a postdoctoral fellow at MIT Sloan School of Management working in collaboration with Massachusetts General Hospital (MGH) on hospital operations management. His research focuses on developing and implementing data-driven analytical tools with the interplay of machine learning and optimization with a specific focus on healthcare and neuroscience applications. Prior to joining MIT/MGH, he acquired his PhD in Management Science at the University of Waterloo. His main research interests are brain connectivity networks, hospital operations management, deep neural networks, data-driven optimization, structure detection and decomposition in mathematical programs. His research has been published in prestigious scientific journals such as INFORMS Journal on Computing, Frontiers in Neuroscience, and European Journal of Operations Research, an algorithm he developed for decomposition and parallel processing of large-scale optimization problems have been adopted by the software company SAS Inc., the machine learning tool he developed for discharge prediction has become an integral part of the Capacity Coordination Center’s workflow at MGH (Harvard), a surgery duration prediction model he developed was used by Lucile Packard Children’s Hospital (Stanford), and his paper on the network optimization approach for identifying the hub regions in the human brain won the best student paper award by Canadian Operations Research Society (CORS).