I am an assistant professor in Departments of Mechanical & Industrial Engineering and Computer Science (by courtesy) at Northeastern University. I worked as a Postdoctoral Fellow in the School of Engineering & Applied Sciences at Harvard University, hosted by Professor Vahid Tarokh. Prior to that, I obtained my Ph.D. in the Department of Electrical & Systems Engineering, at the University of Pennsylvania, where I was advised by Professors Ali Jadbabaie and Alexander Rakhlin. I also completed an A.M. in Statistics from the The Wharton School and a B.S. in Electrical Engineering from Sharif University of Technology.
My main research goal is to develop computationally efficient and scalable methods for approximation and online decision-making in engineering systems. The fields relevant to my research are Machine Learning, Control and Optimization, and Statistical Signal Processing. Specific research interests include:
- Distributed convex and non-convex optimization with a focus on finite-time analysis
- Online optimization, optimal control, and real-time prediction in dynamic environments
- Reinforcement learning
- Cross-modal and multi-modal statistical learning
I am always looking for motivated graduate students with strong background in mathematics for research in the broad area of machine learning, control and optimization.
Our research is multi-disciplinary and prospective students may have background in applied mathematics, industrial and systems engineering, mechanical engineering, electrical and computer engineering, computer science, or statistics. If you are interested in joining our group, please mention that in your application to the graduate program in Mechanical and Industrial Engineering at Northeastern University. Please also send an email to (s.shahrampour[at]northeastern[dot]edu) with your CV, transcripts, and past research experience.
