1. Educating Tomorrow's Technology Leaders for Career Success Ramin Moghaddass, Assistant Professor Education: University of Alberta, Canada, PhD2008-2013 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

2. Educating Tomorrow's Technology Leaders for Career Success Research Plan Methodologies : 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 …

3. Educating Tomorrow's Technology Leaders for Career Success Predictive Analytics (1) Relationship between time-varying drug exposures and health conditions Dataset 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

4. Educating Tomorrow's Technology Leaders for Career Success Predictive Analytics (2) Case-based Reasoning (CBR) and medical assessment from past data Dataset 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