Lina Al-Kanj

I am a Senior Applied Scientist at Amazon SCOT. I was an Associate Research Scholar at the Operations Research and Financial Engineering Department at Princeton University where I was a member of the Computational Stochastic Optimization and Learning (CASTLE) Lab working on Stochastic Optimization, Reinforcement Learning and Machine Learning. Before that, I was a Postdoctoral Research Fellow at the Electrical Engineering Department at Princeton University.

Google Scholar: Link.

I received the M.E. and Ph.D. degrees in Electrical and Computer Engineering from the American University of Beirut. I was a visiting PhD student at the University of Texas at Austin and a visiting Master student at Munich University of Technology.

My main research interest is sequential decision making where we make sequential decisions under uncertainty. I start first by modeling the uncertainty in the system using predictive modeling and machine learning. Depending on the characteristics of the uncertainty, I develop the optimal policy for making the decision using various techniques that include stochastic optimization, reinforcement learning and approximate dynamic programming. The applications that I have addressed have rich problem domains, due to inherent stochasticity and the curses of dimensionality (e.g., large state, action, and outcome spaces) which requires approximations to get attainable solutions.

My research interests include:

  • Sequential Decision Making (Stochastic Modeling and Optimization).

  • Reinforcement Learning, Dynamic Programming and Markov Decision Processes.

  • Machine Learning and Statistical Learning.

  • Neural Networks, Deep Learning and Deep Reinforcement Learning.

  • Resource Allocation and Scheduling (Stochastic and Deterministic Systems).

  • Artificial Intelligence for Computer, Communication, Transportation and Energy Systems.