The lab is currently recruiting undergraduate/graduate students to participate in the data science projects starting in Fall 2024.
Intelligent Modeling and Parameter Selection in Distributed Optimization for Power Networks
In the context of the rapidly transforming power networks, characterized by millions of controllable nodes, achieving effective solutions necessitates a comprehensive grasp of the system’s complexities and advanced mathematical principles. Leveraging a fusion of optimization and engineering expertise, this project aims to pioneer innovative strategies, adapting new scalable optimization techniques and data-driven approaches for modern power networks. The primary goal is designing robust distributed algorithms where multiple agents communicate and collaborate to solve a large-scale problem. These algorithms aim to heighten efficiency, reliability, and adaptability in the face of evolving, decarbonized energy paradigms.
Advancing Predictive Models with SDOH Integration in Healthcare
This project aims to develop innovative predictive modeling, employing advanced data science tools to tackle prevalent challenges in the healthcare sector. This initiative is designed to elevate patient readmission outcomes and optimize cost-effectiveness, concentrating on two pivotal domains: 30-day readmission prediction and the refinement of the Medicare Shared Savings Program (MSSP) Cost Model. The digitization of clinical records presents a new opportunity to integrate Social Determinants of Health (SDOH) data into electronic health records (EHRs) to enhance care delivery and population health. SDOH data includes information on a person’s income, education, neighborhood, and other social or economic factors about an individual’s environment. These factors have a significant impact on overall health outcomes and can help us understand the root causes of health disparities. The SDOH data modeling can help healthcare providers understand a patient’s physical environment and socioeconomic status, further improve healthcare efficiency, and optimize healthcare resource allocation.