Educating Tomorrow's Technology Leaders for Career Success

Ramin Moghaddass, Assistant Professor

Education: University of Alberta, Canada, PhD 2008-2013 MIT (Sloan & CSAIL), Research Scholar 2013- 2015

Research Interests: Data-Driven Decision Making under Uncertainty and Dynamic Environments Survival Analysis and Condition Monitoring for Degrading Systems Time-series (and Longitudinal) Data Analysis Big Data Analytics Healthcare Analytics & Causal Inference

Man Application: Energy Grid Condition Monitoring and Decision-Making Healthcare Analytics

Educating Tomorrow's Technology Leaders for Career Success

Research PlanMethodologies:

Advanced Machine Learning Methods Hierarchical Bayesian Framework High dimensional Time-Series Analysis Stochastic Programming and Control

Main Focus: Interpretable modeling Large-scale datasets Actionable insights from data that can be used for Decision-

Making

Funding Agencies: NSF NIH …

Educating Tomorrow's Technology Leaders for Career Success

Predictive Analytics (1)Relationship between time-varying drug exposures and health conditionsDataset Format:

Example:

Recent Paper: • Ramin Moghaddass, Cynthia Rudin, David Madigan, 2015, The Factorized Self-Controlled Case Series Method: An

Approach for Estimating the Effects of Many Drugs on Many Outcomes, Journal of Machine Learning Research (JMLR).

Estimating the effects of various time-sensitive treatments for diabetes.

Large longitudinal observational datasets with many patients, many drugs and many outcome events

Educating Tomorrow's Technology Leaders for Career Success

Predictive Analytics (2)Case-based Reasoning (CBR) and medical assessment from past dataDataset Format:

Example:

Recent Paper: • Moghaddass, R., Rudin, C. (2015). Bayesian Patchworks: An Approach to Case-Based Reasoning. IEEE Transactions on

Pattern Analysis and Machine Intelligence (TPAM), submitted.

Heart disease prediction Breast cancer prediction

A large dataset of [attributes, health outcomes] for many patients