Madison, Wisconsin, United States
* Machine Learning and Operations Research in Health Care Systems * Ph.D Dissertation: "A Smart and Connected Healthcare Delivery Process: From Prediction to Decision Support" * Details: - Built machine learning prediction models for Chronic Obstructive Pulmonary Disease (COPD) patients’ hospital readmission and developed a graphical intervention optimization model - Proposed a causal Bayesian network training method identifying critical risk factors for COPD readmission and developed a Markov decision process integrating the causal Bayesian network for designing a personalized dynamic intervention plan - Developed a semi-supervised classification model for detecting opioid overdose patients and a stochastic optimization model for the optimal dose prescription - Developed a transient stochastic process model for analyzing the optimal workflow process of primary care physicians
* Worked as an applied scientist intern in Amazon Device-Demand Planning * Details: - Developed machine learning models for forecasting future demands of Amazon devices using the historical sales-related data and future prices - Proposed Feature Grouping Sequence-to-Sequence deep learning model in order to facilitate better use of the data specific to Amazon devices
* Worked as a research intern in Digital Health Lab * Details: - Conducted a clinical research study collecting mobile sensor and audio data from COPD and asthma patients, and built machine learning models to detect cough or sounds related to the lung diseases - Developed speech obfuscation algorithms to collect audio sounds, which can be used to detect health-related information, from wearable devices without any concern of privacy
* Conducted researches in Smart Management Strategy for Health Lab
* Conducted researches regarding Machine Learning Algorithms and Deep Learning in Statistical Learning and Computational Finance Lab * M.S Thesis: "A Study on Recurrent Neural Network Training Methods for Sequential Data Regression"