Presentations

2020

• Personalized input-output hidden Markov models for disease progression modeling. CBE Computing Seminar at the University of Wisconsin, Virtual.

• Personalized input-output hidden Markov models for disease progression modeling. Machine Learning for Healthcare, Virtual.

• Applications of machine learning in battery research. University of Waterloo Electrochemical Society Student Chapter, Virtual recording

2019

• Subtype insights for Parkinson’s disease using a medication-aware disease progression model. Computational Neuroscience Outcomes Center Symposium, Boston.

• Data-driven prediction of battery cycle life before capacity degradation. AI in Process Automation Symposium, Boston.

• Medication-aware disease progression modeling for Parkinson’s disease. IBM, Cambridge.

• Big-data analytics - An introduction. AIChE Spring Meeting, New Orleans.

• Unsupervised learning with contrastive latent variable models. AAAI, Honolulu.

2018

• Unsupervised learning with contrastive latent variable models. Poster. Machine Learning for Healthcare, NeurIPS, Montreal.

• Machine learning applications in chemical and biological engineering. MIT, Cambridge.

• Data-driven modeling of complex systems. Northeastern University, Boston.

• Data-driven modeling of complex systems. University of Delaware, Newark.

• Data-driven modeling of complex systems. Carnegie Mellon University, Pittsburgh.

• Data-driven modeling of complex systems. Princeton University, Princeton.

2017

• Building data-driven models in the presence of missing data. 2017 Smith School Distinguished Junior Researchers Seminar, Cornell University, Ithaca.

• Semi-supervised anomaly detection for production oil wells. AIChE Annual Meeting, Minneapolis.

• The data analytics triangle. AIChE Spring Meeting, San Antonio.

2016

• A method for learning a sparse classifier in the presence of missing data for high-dimensional biological datasets. AIChE Annual Meeting, San Francisco.

• Building classifiers in the presence of missing data. MIT, Cambridge.

2015

• Elastic net with Monte Carlo sampling for data-based modeling in biopharmaceutical manufacturing facilities. AIChE Annual Meeting, Salt Lake City.

• A case study of data analytics for the manufacture of a monoclonal antibody. AIChE Annual Meeting, Salt Lake City.

2012

• Simultaneous optimization and heat integration for the production of algae-based biodiesel using bioethanol. AIChE Annual Meeting, Pittsburgh.