Research

Research Interests

• • Operations Research, Optimization (Mixed Integer Optimization, Combinatorial Optimization)

  • Data Mining & Machine Learning

  • Our overall research goal is to develop problem-driven, data-informed decision models and computational tools by discovering patterns from large-scale, complex data for supporting decision-making and scientific findings in two directions, including, but not limited to:

    1. Interpretable decision models and data-centric analytics for health informatics, computational medicine, and healthcare operations; 

    2. Data-driven modeling and learning for multi-modal dynamic pattern recognition (Explainable AI) in complex system applications such as human body network, healthcare, neuroscience, logistics, and environment.

Research Projects

• • Decoding Multi-Modal Physiological Response Patterns for Assessing Post-Stroke Cognitive Impairment in VR-based Driving, NIH Tufts CTSI. PI

  • Data-Driven Method for Recognizing and Learning Dynamical Systems in Computational Neuroscience, BWF CRTG Program. PI

  • New Paradigm for Assessment Decision Support of Sensorimotor Impairments, NEU TIER 1 Seed Grant Program. PI

  • Decoding Situational Empathy: A Graph Theoretic Approach Towards Introducing a Quantitative Empathy Measure, NEU TIER 1 Seed Grant Program. Co-PI

  • Biosensor Data Fusion for Real-Time Monitoring of Global Neurophysiological Function, National Science Foundation. Co-PI

  • Develop Hospital Readmission Prediction Algorithms and Identify Metrics of Interest in Patient-Centered Care, SUNY Strategic Partnership for Industrial Resurgence (SPIR) program. Sole-PI

  • Real-Time Monitoring of Global Neurophysiological Function Using Customized 3D-Printed BioSensors and Sensor Data Fusion Algorithms, Interdisciplinary Collaboration Grant, Binghamton University. Co-PI

  • Healthcare Systems Engineering and Operational Excellence, United Health Services Hospital. Co-PI

  • A Machine Learning-Based Approach for Optimizing the Discovery of Brain-Based Risk Markers for Psychiatric Illness, Interdisciplinary Collaboration Grant, Binghamton University. Co-PI

  • Developing Novel Optimization Based Learning Systems for Detection and Interpretation of Brain Aneurysm Rupture, Research Foundation for SUNY. Sole-PI (with in-kind support by United Health Services Hospital) [link] [link] 

  • Healthcare Systems Engineering and Analytics Research, United Health Services Hospital. Co-PI