Rumi Chunara
Rumi Chunara
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Associate Professor of Biostatistics
Associate Professor of Computer Science and Engineering, Tandon
Director of Center for Health Data Science
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Professional overview
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The overarching goal of Dr. Rumi Chunara's research is to develop computational and statistical approaches for acquiring, integrating and using data to improve population-level public health. She focuses on the design and development of data mining and machine learning methods to address challenges related to data and goals of public health, as well as fairness and ethics in the design and use of data and algorithms embedded in social systems.
At NYU, Dr. Chunara also leads the Chunara Lab, which develops computational and statistical methods across data mining, natural language processing, spatio-temporal analyses and machine learning, to study population health. Previously, she was a Postdoctoral Fellow and Instructor at HealthMap and the Children's Hospital Informatics Program at Harvard Medical School. She completed her PhD at the Harvard-MIT Division of Health Sciences and Technology and BSc at Caltech.
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Education
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BS, Electrical Engineering (Honors), CaltechMS, Electrical Engineering and Computer Science, MITPhD, Medical and Electrical Engineering, MIT (Harvard-MIT Division of Health Sciences and Technology)
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Honors and awards
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Max Planck Sabbatical Award (2021)speaker at NSF Computer and Information Science and Engineering Directorate Career Proposal Writing Workshop (2020)Invited tutorial on Public Health and Machine Learning at ACM Conference on Health, Inference and Learning (2020)Keynote at Human Computation and Crowdsourcing (2019)Invited Speaker at Expert Group Meeting at United Nations Population Fund, Advances in Mobile Technologies for Data Collection Panel (2019)Keynote at ''Mapping the Equity Dimensions of Artificial Intelligence in Public Health'', University of Toronto (2019)Facebook Research Award (2019)Gates Foundation Grand Challenges Exploration Award (2019)NSF CAREER Award (2019)MIT Technology Review Top 35 Innovators Under 35 (2014)MIT Presidential Fellow (2004)
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Areas of research and study
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Health DisparitiesMachine learningSocial ComputingSocial Determinants of Health
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Publications
Publications
Forget Forgetting: Continual Learning in a World of Abundant Memory
AbstractCho*, D., Moon, T., myname{}, Cho, K., Cha, S., Chunara, R., & Chunara, R. (n.d.).Publication year
2026Abstract~Identity-Robust Language Model Generation via Content Integrity Preservation
AbstractZhang*, M., Chen*, K., Tanjim, M., myname{}, Chunara, R., & Chunara, R. (n.d.).Publication year
2026Abstract~Incorporating Expert Knowledge in Data Augmentation using Query-based Model Collaboration
AbstractCho*, D., Zhang*, M., Lyng, G. D., myname{}, Chunara, R., & Chunara, R. (n.d.).Publication year
2026Abstract~Mapping social determinants of health data in sub-Saharan Africa: a scoping review protocol
AbstractAnyiam*, F. E., Gjonaj*, J., Osango, N. A., Mugo, R., Aber, P., Shah, J., Mangeni, J., Vedanthan, R., Hogan, J. W., Mwangi, A., myname{}, Chunara, R., & Chunara, R. (n.d.).Publication year
2026Journal title
BMJ openVolume
16Issue
2Page(s)
e105390Abstract~Monsoon weather and food security in Pakistan
AbstractConte, K. R., myname{}, Chunara, R., & Chunara, R. (n.d.).Publication year
2026Journal title
Food SecurityAbstract~Prior Authorization Requirements and Prescription Fill Patterns Among Patients With Heart Failure
AbstractMukhopadhyay, A., Adhikari, S., Li, X., Kazi, D. S., Berman, A. N., Kronish, I., Hamo, C., Dodson, J. A., myname{}, Ladino, N., others, Chunara, R., & Chunara, R. (n.d.).Publication year
2026Journal title
JACC: AdvancesVolume
5Issue
2Page(s)
102583Abstract~Testing the effects of segmented crowdsource-selected messages to improve intentions to follow colorectal cancer screening recommendations: study protocol for a randomized controlled trial
AbstractKing, A. J., Liao, Y. i., Chen, T., Kanrar, R., myname{}, Margolin, D., Nettleton, D., Niederdeppe, J., Chunara, R., & Chunara, R. (n.d.).Publication year
2026Journal title
BMC Public HealthAbstract~Associations between Anti-Gay Prejudice, Traditional Masculine Self-Concept, and Colorectal Cancer Screening-Related Outcomes among Black and White Men in the US
AbstractChen, T., Wicke, R., King, A. J., Margolin, D., myname{}, Niederdeppe, J., Chunara, R., & Chunara, R. (n.d.).Publication year
2025Journal title
Cancer Epidemiology, Biomarkers & PreventionAbstract~Associations between Anti-Gay Prejudice, Traditional Masculine Self-Concept, and Colorectal Cancer Screening–Related Outcomes among Black and White Men in the United States
AbstractChen, T., Wicke, R., King, A. J., Margolin, D., Chunara, R., Chunara, R., & Niederdeppe, J. (n.d.).Publication year
2025Journal title
Cancer Epidemiology Biomarkers and PreventionVolume
34Issue
5Page(s)
714-721AbstractBackground: Colorectal cancer screening can reduce colorectal cancer risk, yet many men are not up to date with screening guidelines. Although previous qualitative studies have suggested links among anti-gay prejudice, traditional masculine self-concept, racial identity, and colorectal cancer screening among men, scholars have yet to fully explore these associations using quantitative data. This study used a nationally representative sample of Black and White men in the United States to test these associations and examine the sociodemographic correlates. Methods: Using the National Opinion Research Center (NORC)/ AmeriSpeak probability-based panel, we recruited a sample of Black and White men in the United States ages 45 to 74 years who had never been diagnosed with colorectal cancer (N ¼ 909). Participants completed an online questionnaire measuring anti-gay prejudice, traditional masculine self-concept, sociodemographic variables, and screening-related outcomes (awareness of screening test options, screening intention, and adherence to screening recommendations). Results: Black participants reported higher levels of anti-gay prejudice and traditional masculine self-concept than White participants. Anti-gay prejudice was associated with lower awareness and lower screening intention. Black participants reported higher intention to follow screening recommendations but not higher odds of actual adherence than White participants. Conclusions: Men with anti-gay prejudice are less likely to be aware of colorectal cancer screening test options and less likely to intend to engage in colorectal cancer screening. The results have implications for the design and development of future interventions aimed at increasing colorectal cancer screening rates.Colorectal Cancer Racial Equity Post Volume, Content, and Exposure : Observational Study Using Twitter Data
AbstractTong, C., Margolin, D., Niederdeppe, J., Chunara, R., Chunara, R., Liu, J., Jih-Vieira, L., & King, A. J. (n.d.).Publication year
2025Journal title
Journal of medical Internet researchVolume
27AbstractBackground: Racial inequity in health outcomes, particularly in colorectal cancer (CRC), remains one of the most pressing issues in cancer communication and public health. Social media platforms like Twitter (now X) provide opportunities to disseminate health equity information widely, yet little is known about the availability, content, and reach of racial health equity information related to CRC on these platforms. Addressing this gap is essential to leveraging social media for equitable health communication. Objective: This study aims to analyze the volume, content, and exposure of CRC racial health equity tweets from identified CRC equity disseminator accounts on Twitter. These accounts were defined as those actively sharing information related to racial equity in CRC outcomes. By examining the behavior and impact of these disseminators, this study provides insights into how health equity content is shared and received on social media. Methods: We identified accounts that posted CRC-related content on Twitter between 2019 and 2021. Accounts were classified as CRC equity disseminators (n=798) if they followed at least 2 CRC racial equity organization accounts. We analyzed the volume and content of racial equity–related CRC tweets (n=1134) from these accounts and categorized them by account type (experts vs nonexperts). Additionally, we evaluated exposure by analyzing follower reach (n=6,266,269) and the role of broker accounts—accounts serving as unique sources of CRC racial equity information to their followers. Results: Among 19,559 tweets posted by 798 CRC equity disseminators, only 5.8% (n=1134) mentioned racially and ethnically minoritized groups. Most of these tweets (641/1134, 57%) addressed disparities in outcomes, while fewer emphasized actionable content, such as symptoms (11/1134, 1%) or screening procedures (159/1134, 14%). Expert accounts (n=479; 716 tweets) were more likely to post CRC equity tweets compared with nonexpert accounts (n=319; 418 tweets). Broker accounts (n=500), or those with a substantial portion of followers relying on them for equity-related information, demonstrated the highest capacity for exposing followers to CRC equity content, thereby extending the reach of these critical messages to underserved communities. Conclusions: This study emphasizes the critical roles played by expert and broker accounts in disseminating CRC racial equity information on social media. Despite the limited volume of equity-focused content, broker accounts were crucial in reaching otherwise unexposed audiences. Public health practitioners should focus on encouraging equity disseminators to share more actionable information, such as symptoms and screening benefits, and implement measures to amplify the reach of such content on social media. Strengthening these efforts could help bridge disparities in cancer outcomes among racially minoritized groups.Colorectal Cancer Racial Equity Post Volume, Content, and Exposure: Observational Study Using Twitter Data
AbstractTong, C., Margolin, D., Niederdeppe, J., myname{}, Liu, J., Jih-Vieira, L., King, A. J., Chunara, R., & Chunara, R. (n.d.).Publication year
2025Journal title
Journal of medical Internet researchVolume
27Page(s)
e63864Abstract~Correct Reasoning Paths Visit Shared Decision Pivots
AbstractCho*, D., Zhang, A. B., Fehri, B., Wang, S., myname{}, Song, R., Cai, H., Chunara, R., & Chunara, R. (n.d.).Publication year
2025Abstract~Disparate Effect Of Missing Mediators On Transportability of Causal Effects
AbstractMhasawade*, V., myname{}, Chunara, R., & Chunara, R. (n.d.).Publication year
2025Abstract~From Algorithms to Action: Deploying AI for Healthy Communities
Abstractmyname{}, Chunara, R., & Chunara, R. (n.d.).Publication year
2025Page(s)
72--77Abstract~Identifying and mitigating algorithmic bias in the safety net
AbstractMackin, S., Major, V. J., myname{}, Newton-Dame, R., Chunara, R., & Chunara, R. (n.d.).Publication year
2025Journal title
npj Digital MedicineVolume
8Issue
1Page(s)
1--11Abstract~Identifying and mitigating algorithmic bias in the safety net
AbstractMackin, S., Major, V. J., Chunara, R., Chunara, R., & Newton-Dame, R. (n.d.).Publication year
2025Journal title
npj Digital MedicineVolume
8Issue
1AbstractAlgorithmic bias occurs when predictive model performance varies meaningfully across sociodemographic classes, exacerbating systemic healthcare disparities. NYC Health + Hospitals, an urban safety net system, assessed bias in two binary classification models in our electronic medical record: one predicting acute visits for asthma and one predicting unplanned readmissions. We evaluated differences in subgroup performance across race/ethnicity, sex, language, and insurance using equal opportunity difference (EOD), a metric comparing false negative rates. The most biased classes (race/ethnicity for asthma, insurance for readmission) were targeted for mitigation using threshold adjustment, which adjusts subgroup thresholds to minimize EOD, and reject option classification, which re-classifies scores near the threshold by subgroup. Successful mitigation was defined as 1) absolute subgroup EODsMachine learning based prediction of medication adherence in heart failure using large electronic health record cohort with linkages to pharmacy-fill and neighborhood-level data
AbstractAdhikari, S., Stokes, T., Li, X., Zhao, Y., Fitchett, C., Ladino, N., Lawrence, S., Qian, M., Cho, Y. S., Hamo, C., Dodson, J., myname{}, Kronish, Mukhopadhyay, Blecker, S., Chunara, R., & Chunara, R. (n.d.).Publication year
2025Journal title
Journal of the American Medical Informatics AssociationPage(s)
ocaf162Abstract~Post-processing methods for mitigating algorithmic bias in healthcare classification models: An extended umbrella review
AbstractMackin, S., Major, V. J., myname{}, Newton-Dame, R., Chunara, R., & Chunara, R. (n.d.).Publication year
2025Journal title
BMC Digital HealthVolume
3Issue
1Page(s)
26Abstract~Proceedings of the Second Artificial Intelligence in Primary Immunodeficiencies (AIPI) Meeting
AbstractRivi`ere, J. G., Bastarache, L., Campos, L. C., Carot-Sans, G., Chin, A., myname{}, Cunningham-Rundles, C., Erra, L., Farmer, J., Garcelon, N., others, Chunara, R., & Chunara, R. (n.d.).Publication year
2025Journal title
Journal of Allergy and Clinical ImmunologyAbstract~Quantifying greenspace with satellite images in Karachi, Pakistan using a new data augmentation paradigm
AbstractZhang, M., Arshad, H., Abbas, M., Jehanzeb, H., Tahir, I., Hassan, J., Samad, Z., Chunara, R., & Chunara, R. (n.d.).Publication year
2025Journal title
ACM Journal on Computing and Sustainable SocietiesAbstract~Association between visit frequency, continuity of care, and pharmacy fill adherence in heart failure patients
AbstractHamo, C. E., Mukhopadhyay, A., Li, X., Zheng, Y., Kronish, I. M., Chunara, R., Chunara, R., Dodson, J., Adhikari, S., & Blecker, S. (n.d.).Publication year
2024Journal title
American Heart JournalVolume
273Page(s)
53-60AbstractBackground: Despite advances in medical therapy for heart failure with reduced ejection fraction (HFrEF), major gaps in medication adherence to guideline-directed medical therapies (GDMT) remain. Greater continuity of care may impact medication adherence and reduced hospitalizations. Methods: We conducted a cross-sectional study of adults with a diagnosis of HF and EF ≤40% with ≥2 outpatient encounters between January 1, 2017 and January 10, 2021, prescribed ≥1 of the following GDMT: 1) Beta Blocker, 2) Angiotensin Converting Enzyme Inhibitor/Angiotensin Receptor Blocker/Angiotensin Receptor Neprilysin Inhibitor, 3) Mineralocorticoid Receptor Antagonist, 4) Sodium Glucose Cotransporter-2 Inhibitor. Continuity of care was calculated using the Bice-Boxerman Continuity of Care Index (COC) and the Usual Provider of Care (UPC) index, categorized by quantile. The primary outcome was adherence to GDMT, defined as average proportion of days covered ≥80% over 1 year. Secondary outcomes included all-cause and HF hospitalization at 1-year. We performed multivariable logistic regression analyses adjusted for demographics, insurance status, comorbidity index, number of visits and neighborhood SES index. Results: Overall, 3,971 individuals were included (mean age 72 years (SD 14), 71% male, 66% White race). In adjusted analyses, compared to individuals in the highest COC quartile, individuals in the third COC quartile had higher odds of GDMT adherence (OR 1.26, 95% CI 1.03-1.53, P = .024). UPC tertile was not associated with adherence (all P > .05). Compared to the highest quantiles, the lowest UPC and COC quantiles had higher odds of all-cause (UPC: OR 1.53, 95%CI 1.23-1.91; COC: OR 2.54, 95%CI 1.94-3.34) and HF (UPC: OR 1.81, 95%CI 1.23-2.67; COC: OR 1.77, 95%CI 1.09-2.95) hospitalizations. Conclusions: Continuity of care was not associated with GDMT adherence among patients with HFrEF but lower continuity of care was associated with increased all-cause and HF-hospitalizations.Associations between news coverage, social media discussions, and search trends about celebrity deaths, screening, and other colorectal cancer-related events
AbstractLiu, J., Niederdeppe, J., Tong, C., Margolin, D., Chunara, R., Chunara, R., Smith, T., & King, A. J. (n.d.).Publication year
2024Journal title
Preventive MedicineVolume
185AbstractObjective: Colorectal cancer (CRC) is the third leading cause of cancer death among both men and women in the United States. CRC-related events may increase media coverage and public attention, boosting awareness and prevention. This study examined associations between several types of CRC events (including unplanned celebrity cancer deaths and planned events like national CRC awareness months, celebrity screening behavior, and screening guideline changes) and news coverage, Twitter discussions, and Google search trends about CRC and CRC screening. Methods: We analyzed data from U.S. national news media outlets, posts scraped from Twitter, and Google Trends on CRC and CRC screening during a three-year period from 2020 to 2022. We used burst detection methods to identify temporal spikes in the volume of news, tweets, and search after each CRC-related event. Results: There is a high level of heterogeneity in the impact of celebrity CRC events. Celebrity CRC deaths were more likely to precede spikes in news and tweets about CRC overall than CRC screening. Celebrity screening preceded spikes in news and tweets about screening but not searches. Awareness months and screening guideline changes did precede spikes in news, tweets, and searches about screening, but these spikes were inconsistent, not simultaneous, and not as large as those events concerning most prominent public figures. Conclusions: CRC events provide opportunities to increase attention to CRC. Media and public health professionals should actively intervene during CRC events to increase emphasis on CRC screening and evidence-based recommendations.Constructing social vulnerability indexes with increased data and machine learning highlight the importance of wealth across global contexts
AbstractZhao, Y., Paul, R., Reid, S., Coimbra, V. C., Wolfe, C., Zhang, Y., Chunara, R., & Chunara, R. (n.d.).Publication year
2024Journal title
Social Indicators ResearchVolume
175Issue
2Page(s)
639--657Abstract~Correction to : Constructing Social Vulnerability Indexes with Increased Data and Machine Learning Highlight the Importance of Wealth Across Global Contexts (Social Indicators Research, (2024), 10.1007/s11205-024-03386-9)
AbstractZhao, Y., Paul, R., Reid, S., Vieira, C. C., Wolfe, C., Zhang, Y., Chunara, R., & Chunara, R. (n.d.).Publication year
2024Journal title
Social Indicators ResearchVolume
174Issue
3Page(s)
1141-1142AbstractThe wrong Supplementary file was originally published with this article; it has now been replaced with the correct file. The original article has been corrected.Making Sense of Social Media Data About Colorectal Cancer Screening
AbstractKing, A. J., Margolin, D., Tong, C., Chunara, R., Chunara, R., & Niederdeppe, J. (n.d.).Publication year
2024Journal title
Journal of the American College of RadiologyVolume
21Issue
4Page(s)
543-544Abstract~