Mark Crowley

Site being updated, see my Research Lab page for current information.

My research seeks dependable and transparent ways to augment human decision making in complex domains in the presence of spatial structure, large scale streaming data, or uncertainty. My focus is on developing new algorithms within the fields of Reinforcement Learning, Deep Learning and Ensemble Methods, and Manifold Learning (Dimensionality Reduction) as well as other Research Topics.
I often work in collaboration with researchers in applied fields such as Computational Sustainability (including Sustainable Forest Management), Autonomous Driving, AI for Physics (including Combustion Modelling and Digital Chemistry) and Medical Imaging.

Note, that I do not take on many incoming graduate students, so if you are hoping to join my lab as a graduate student for research please read this note.

Besides my publications, you can follow my Computationally Thinking blog or @compthink on twitter for links and thoughts on Artificial Intellgience, Machine Learning and how technology and science are advancing. I’m always happy to talk to people about my research, or the impact of AI/ML/RL on our world and its role in our society in the future.

news

Nov 2, 2021 Recently Accepted Papers
more: Three great papers accepted to AAAI, NeurIPS Workshop and EMBC in past month!
Nov 1, 2021 Patent arose in collaboration with DENSO Inc. on a remote controlled car demo for CES.
more: Patent awarded for Multi-level collaborative vehicle control

selected showcase publications

  1. Mean Field MARL
    Decentralized Mean Field Games
    Ganapathi Subramanian, Sriram, Taylor, Mathew, Crowley, Mark, and Poupart, Pascal
    In Proceedings of the AAAI Conference on Artificial Intelligence (AAAI-2022) 2022
  2. MARLEmpircal
    Investigation of Independent Reinforcement Learning Algorithms in Multi-Agent Environments
    Lee, Ken Ming, Ganapathi Subramanian, Sriram, and Crowley, Mark
    Frontiers in Artificial Intelligence (Machine Learning and Artificial Intelligence) 2021
  3. MARLEmpircal
    Investigation of Independent Reinforcement Learning Algorithms in Multi-Agent Environments
    Lee, Ken Ming, Ganapathi Subramanian, Sriram, and Crowley, Mark
    In NeurIPS 2021 Deep Reinforcement Learning Workshop 2021
  4. Multi-Advisor-QL
    Multi-Agent Advisor Q-Learning
    Ganapathi Subramanian, Sriram, Larson, Kate, Taylor, Mathew, and Crowley, Mark
    Journal of Artificial Intelligence Research (JAIR) 2022
  5. Acceleration of Large Margin Metric Learning for Nearest Neighbor Classification Using Triplet Mining and Stratified Sampling
    Poorheravi, Parisa, Ghojogh, Benyamin, Gaudet, Vincent, Karray, Fakhri, and Crowley, Mark
    Journal of Computational Vision and Imaging Systems 2021