Ben Marlin

Ben Marlin is a Professor in the Manning College of Information and Computer Sciences at the University of Massachusetts Amherst, directing the Robust and Efficient Machine Learning (REML) Lab. He holds affiliations with the Center for Data Science, Center for Intelligent Information Retrieval, and others. His research focuses on robust and efficient machine learning models, particularly for time series data and clinical/mHealth applications. He has received NSF CAREER and Yahoo! Faculty awards, and previously held postdoctoral fellowships with the Killam Trusts and Pacific Institute for the Mathematical Sciences.

Marlin earned his PhD in computer science from the University of Toronto (2008), MS from the same university (2004), and BS in mathematics and computer science from McGill University (2002). His work bridges probabilistic modeling, deep learning, and real-world applications in health, IoT, and embedded systems.

Research interests include hierarchical graphical models, Bayesian methods, and scalable algorithms for irregularly sampled data. Recent projects emphasize robustness to missing data and computational efficiency. His lab collaborates on grants like the MD2k Center and mDOT, addressing challenges in wearable sensors and adaptive interventions.

• Awards: NSF CAREER (2014), Yahoo! Faculty (2013), Best Paper (ACM Recommender Systems 2009).
• Grants/Labs: REML Lab, MD2k, MassAITC, IoBT Collaborative Research Alliance.
• Education: PhD (Toronto), MS (Toronto), BS (McGill).

Publications span time series imputation, sensor fusion, and Bayesian deep learning. Ongoing work explores edge-cloud optimization and AI-driven clinical trial digitization.