Email ↗Research / Mission
How can we learn from complex, incomplete, and evolving healthcare data to make better decisions about patient risk, care pathways, and limited resources?
My research brings together operations research, statistical modeling, and applied analytics to study these questions. I develop and apply quantitative approaches to identify patterns that are difficult to see, understand how risks change, and inform decisions about where care and resources may be needed most.
01 / Research directions
Healthcare decisions depend on understanding who faces risk, when it changes, and how and where limited resources can be directed. My selected projects examine these connected challenges through different quantitative approaches.
This work focuses on which patients face elevated cardiovascular risk and how dynamic stratification could inform specialty referral decisions.
Approach: Bipartite stochastic block models · Risk stratification · Specialty referral decisions
A preprint using EHR data from 9,450 primary-care patients to study relationships between early diabetes detection, post-diagnosis glycemic control, and subsequent cardiovascular risk.
Approach: Order-based Bayesian network · Machine Learning
Research on clinic allocation in Western Massachusetts, examining how rurality and transportation barriers can inform equitable healthcare facility placement to address disparities in access. Published in the proceedings of the IISE Annual Conference & Expo (2024).
Approach: Mixed Integer Programming · Rurality Index
02 / Emerging directions
I’m interested in research that moves beyond prediction to understand causes, compare interventions, and support better decisions in healthcare. Several directions especially intrigue me—both as methodological challenges and as opportunities to tackle important health problems.
Developing reliable decision tools that combine prediction with optimization, sequential decisions, evolving patient information, and operational constraints.
Understanding heterogeneous treatment effects through longitudinal and multimodal data, including EHR trajectories, molecular measurements, and patient-generated data.
Exploring cost-effectiveness, disease and policy simulation, population health, budget impact, and how evidence informs clinical and health-system choices.
I'm particularly drawn to women's health, diseases disproportionately affecting women, and rare diseases, alongside opportunities at the intersection of biotechnology, pharmaceutical research, healthcare delivery, and entrepreneurship.
These interests reflect questions and research possibilities I want to investigate, not a fixed list of future specialties.
03 / Research record
Yukti Kathuria, Kristen Miller, Elizabeth Selden, William Gallagher, Muge Capan
medRxiv preprint; manuscript under revision for PLOS Digital HealthR. Mahalingam, P. Sarathy, M. K. Mannava, Yukti Kathuria
International Journal of Applied Informatics and Media Design, 5(1), 32–41Muge Capan, Lily Bigelow, Yukti Kathuria, Amanda Paluch, Joohyun Chung
PLOS ONE, 19(5), e0304214Yukti Kathuria, Muge Capan, Jessica Boakye, Chaitra Gopalappa
Proceedings of the IISE Annual Conference & ExpoV. Vedant, Yukti Kathuria, A. Ghosh
41st Annual AAS Rocky Mountain Section Guidance and Control ConferenceYukti Kathuria, Brian Nathanson, Muge Capan
Manuscript in preparation04 / Sharing the work
05 / Beyond the papers