Email
xliu14@wpi.edu
Office
Unity Hall, #362
Affiliated Department or Office
Education
PhD in Information Science and Technology from Syracuse University

Dr. Xiaozhong Liu is a Professor of Data Science and Computer Science at Worcester Polytechnic Institute. His research focuses on artificial intelligence, data science, and their applications in healthcare, with particular interests in longitudinal patient modeling, chronic disease management, clinical decision support, human-AI collaboration, and trustworthy personalized AI.

His recent work investigates how multimodal longitudinal data, including electronic health records, wearable sensing, patient interactions, and real-world behavioral data, can be used to model evolving patient states, identify emerging risks, support treatment adherence, and enable timely clinical interventions. Current research directions include AI-assisted triage and decision-making, continuous monitoring for chronic disease, cancer treatment toxicity surveillance, digital twin models for longitudinal care, and adaptive allocation of responsibilities among AI systems, caregivers, nurses, and clinicians.

Methodologically, his work spans large language models, memory and personalization, machine learning, causal and decision modeling, information retrieval, graph learning, and privacy-aware AI. He has published more than 150 peer-reviewed papers and has led or participated in research funded by NIH, NSF, NSA, and other organizations.

Before joining WPI, Dr. Liu was a faculty member at Indiana University Bloomington and served as a Research Director and Senior Consultant at Alibaba DAMO Academy, where he led a multidisciplinary AI/NLP team and helped develop large-scale production AI systems serving more than 170 million API calls per day.

I’m actively looking for PhD students with good experience in NLP and/or deep learning.

Email
xliu14@wpi.edu
Affiliated Department or Office
Education
PhD in Information Science and Technology from Syracuse University

Dr. Xiaozhong Liu is a Professor of Data Science and Computer Science at Worcester Polytechnic Institute. His research focuses on artificial intelligence, data science, and their applications in healthcare, with particular interests in longitudinal patient modeling, chronic disease management, clinical decision support, human-AI collaboration, and trustworthy personalized AI.

His recent work investigates how multimodal longitudinal data, including electronic health records, wearable sensing, patient interactions, and real-world behavioral data, can be used to model evolving patient states, identify emerging risks, support treatment adherence, and enable timely clinical interventions. Current research directions include AI-assisted triage and decision-making, continuous monitoring for chronic disease, cancer treatment toxicity surveillance, digital twin models for longitudinal care, and adaptive allocation of responsibilities among AI systems, caregivers, nurses, and clinicians.

Methodologically, his work spans large language models, memory and personalization, machine learning, causal and decision modeling, information retrieval, graph learning, and privacy-aware AI. He has published more than 150 peer-reviewed papers and has led or participated in research funded by NIH, NSF, NSA, and other organizations.

Before joining WPI, Dr. Liu was a faculty member at Indiana University Bloomington and served as a Research Director and Senior Consultant at Alibaba DAMO Academy, where he led a multidisciplinary AI/NLP team and helped develop large-scale production AI systems serving more than 170 million API calls per day.

I’m actively looking for PhD students with good experience in NLP and/or deep learning.

Office
Unity Hall, #362
Professional Highlights & Honors
An Artificial Intelligence Approach to Understanding Trade-offs in Emergency Department Decision-making (R01), 2026 - 2030
National Institutes of Health
VitalDiagnosis: AI-Driven Ecosystemfor24/7 VitalMonitoring and Chronic Disease Management, 2025 - 2029
Venture Capital
DRiving Automotive Industry WorkForce Transformation (DRlFT): Excellence and Innovation in Cybersecurity and Artificial Intelligence, 2024 - 2027
National Security Agency
Collaborative Research: SaTC:CORE:Medium: Audacity of Exploration: Toward Automated Discovery of Security Flaws in Networked Systems through Intelligent Documentation Analysis, 2023 - 2026
National Science Foundation
Constructing Heterogeneous Scholarly Graphs to Examine Social Capital During Mentored K Awardees' Transition to Research Independence: Explicating a Matthew Mechanism, 2022 - 2025
National Science Foundation
Embedded Systems Security/Artificial Intelligence (ESS/AI) Research and Workforce Development, 2021 - 2022
Department of Defense

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