Dr. Dundar's area of expertise is in machine learning with a special focus on self-adjusting models and inference, where the traditional brute-force approach of fitting a fixed model onto the data is replaced with more flexible models that can account for the non-stationary nature of real-world machine learning problems by dynamically updating data model to better accommodate prospective data in offline as well as online settings.

Management Information Systems, Information Science/Systems, Computer Science
PhD, Purdue University, Electrical and Computer Engineering, 2003
MS, Purdue University, Electrical and Computer Engineering, 1999
MS, Bogazici University, Systems and Control Institute, 1999
BS, Bogazici University, Electrical and Electronics Engineering, 1997
computer and information sciences