Dr. Krishnamurti develops processes, (digital) tools, and communication strategies, grounded in psychological theory, to support informed decision making. Her work addresses critical challenges in healthcare by developing patient-centered interventions that identify and remediate health risks, particularly in maternal and mental health.
Dr. Krishnamurti's research has been funded by the National Science Foundation, the National Institutes of Health, and the Centers for Disease Control, as well as foundation and industry grants. She has participated in expert panels hosted by the Nobel Prize Summit, FDA, NIH, and National Academies. She co-founded a startup company, which uses behavioral science and machine learning to engage patients in their clinical care and holds multiples patents on methods for identifying patients at risk of adverse health events.
Dr. Krishnamurti’s work has been published in peer-reviewed journals such as PNAS, Medical Decision Making, and the JAMA family of journals. Her research was identified as an Idea of the Year in The New York Times and has been cited by major news organizations, such as The New York Times, NPR, and MSNBC. Dr. Krishnamurti is active on multiple scientific advisory boards and committees. She was the 2020 recipient of S&R Evermay’s Kuno Award for Applied Science for the Social Good.
Dr. Krishnamurti enjoys adventurous travel with her husband and two sons, and she doesn’t leave town without a good mystery novel in her bag.
Education & Training
- General Course (Cultural Anthropology), The London School of Economics and Political Science, 2002
- BS (Biological Anthropology), Carnegie Mellon University, 2003
- MS (Behavioral Decision Research), Carnegie Mellon University, 2006
- PhD (Behavioral Decision Research), Carnegie Mellon University, 2010
Representative Publications
Krishnamurti T, Rodriguez S, Wilder B, Gopalan P, Simhan HN. Predicting first time depression onset in pregnancy: applying machine learning methods to patient-reported data. Archives of Women's Mental Health. 2024 May 22:1-3.
This study applies machine learning methods to predict first-time depression onset during pregnancy using patient-reported data, offering new pathways for early intervention and prevention in maternal mental health.
Krishnamurti T, Davis AL, Wong-Parodi G, Fischhoff B, Sadovsky Y, Simhan HN. Development and testing of the MyHealthyPregnancy app: a behavioral decision research-based tool for assessing and communicating pregnancy risk. JMIR Mhealth Uhealth. 2017;5(4):e42.
This study demonstrates the application of a behavioral decision research approach to the creation of a mobile health platform designed to identify clinical risks not detected in routine care, including preeclampsia, depression, and intimate partner violence.
Krishnamurti T, Woloshin S, Schwartz LM, Fischhoff B. A randomized trial testing US Food and Drug Administration "breakthrough" language. JAMA Internal Medicine. 2015;175(11):1856-1858.
This randomized trial revealed that FDA’s "breakthrough" terminology significantly increased public beliefs in drug effectiveness, providing evidence that influenced national regulatory communication practices.
Krishnamurti T, Murtaugh KL, Van Nunen L, Davis AL, Ipser J, Shoptaw S. Spending money to make change: Association of methamphetamine abstinence and voucher spending among contingency management pilot participants in South Africa. Journal of Substance Abuse Treatment. 2020;112:60-67.
This study demonstrated that spending patterns in a contingency management program predict treatment success better than earnings alone, applying behavioral economics principles to optimize substance use disorder interventions.
Click here for a more complete bibliography of Dr. Krishnamurti’s works.
Research Interests
- Maternal health
- Risk communication
- Digital health tools
- Predictive algorithms
- Health equity