Phased array systems in silicon. - Ali Hajimiri; Abbas Komijani; Arun Natarajan 001; Rumi Chunara; Xiang Guan; Hossein Hashemi 001 (IEEE Commun. Mag., 2004)

Participatory disease surveillance in Latin America. - Michael A. Johansson; Oktawia Wojcik; Rumi Chunara; Mark Smolinski; John S. Brownstein (WWW (Companion Volume), 2013)

First Feasibility of a Surveillance Platform Combining Community-Submitted Symptoms and Specimens for Molecular Diagnostic Testing. - Jennifer Goff; Aaron A. Rowe; Rumi Chunara (AMIA, 2014)

Network inference from multimodal data: A review of approaches from infectious disease transmission. - Bisakha Ray; Elodie Ghedin; Rumi Chunara (J. Biomed. Informatics, 2016)

New data paradigms: From the crowd and back. - Rumi Chunara (IEEE BigData, 2017)

Assessing Behavior Stage Progression From Social Media Data. - Jiaxin Liu; Elissa R. Weitzman; Rumi Chunara (CSCW, 2017)

Using Sparse Digital Traces to Fill in Individual Level Mobility Timelines. - Nabeel Abdur Rehman; Kunal Relia; Rumi Chunara (CoRR, 2017)

High-resolution Temporal Representations of Alcohol and Tobacco Behaviors from Social Media Data. - Tom Huang; Anas Elghafari; Kunal Relia; Rumi Chunara (Proc. ACM Hum. Comput. Interact., 2017)

Creating full individual-level location timelines from sparse social media data. - Nabeel Abdur Rehman; Kunal Relia; Rumi Chunara (SIGSPATIAL/GIS, 2018)

From the User to the Medium: Neural Profiling Across Web Communities. - Mohammad Akbari 001; Kunal Relia; Anas Elghafari; Rumi Chunara (ICWSM, 2018)

Reports of the Workshops Held at the 2018 International AAAI Conference on Web and Social Media. - Jisun An; Rumi Chunara; David J. Crandall; Darian Frajberg; Megan French; Bernard J. Jansen; Juhi Kulshrestha; Yelena Mejova; Daniel M. Romero; Joni Salminen; Amit Sharma 007; Amit P. Sheth; et al. (AI Mag., 2018)

Domain Adaptation for Infection Prediction from Symptoms Based on Data from Different Study Designs and Contexts. - Nabeel Abdur Rehman; Maxwell Matthaios Aliapoulios; Disha Umarwani; Rumi Chunara (CoRR, 2018)

Population-aware Hierarchical Bayesian Domain Adaptation. - Vishwali Mhasawade; Nabeel Abdur Rehman; Rumi Chunara (CoRR, 2018)

Tracking health seeking behavior during an Ebola outbreak via mobile phones and SMS. - Shuo Feng; Karen A. Grépin; Rumi Chunara (npj Digit. Medicine, 2018)

Socio-spatial Self-organizing Maps: Using Social Media to Assess Relevant Geographies for Exposure to Social Processes. - Kunal Relia; Mohammad Akbari 001; Dustin Duncan; Rumi Chunara (Proc. ACM Hum. Comput. Interact., 2018)

Deep Landscape Features for Improving Vector-borne Disease Prediction. - Nabeel Abdur Rehman; Umar Saif; Rumi Chunara (CVPR Workshops, 2019)

Race, Ethnicity and National Origin-Based Discrimination in Social Media and Hate Crimes across 100 U.S. Cities. - Kunal Relia; Zhengyi Li; Stephanie H. Cook; Rumi Chunara (ICWSM, 2019)

Using Contextual Information to Improve Blood Glucose Prediction. - Mohammad Akbari; Rumi Chunara (MLHC, 2019)

Reports of the Workshops Held at the 2019 International AAAI Conference on Web and Social Media. - Diego Alburez-Gutierrez; Eshwar Chandrasekharan; Rumi Chunara; Sofia Gil-Clavel; Aniko Hannak; Roberto Interdonato; Kenneth Joseph; Kyriaki Kalimeri; Momin M. Malik; Katja Mayer; Yelena Mejova; Daniela Paolotti; et al. (AI Mag., 2019)

Population-aware Hierarchical Bayesian Domain Adaptation via Multiple-component Invariant Learning. - Vishwali Mhasawade; Nabeel Abdur Rehman; Rumi Chunara (CoRR, 2019)

Using Contextual Information to Improve Blood Glucose Prediction. - Mohammad Akbari 001; Rumi Chunara (CoRR, 2019)

Fair Predictors under Distribution Shift. - Harvineet Singh; Rina Singh; Vishwali Mhasawade; Rumi Chunara (CoRR, 2019)

Population-aware hierarchical bayesian domain adaptation via multi-component invariant learning. - Vishwali Mhasawade; Nabeel Abdur Rehman; Rumi Chunara (CHIL, 2020)

Quasi-Experimental Designs for Assessing Response on Social Media to Policy Changes. - Yijun Tian 001; Rumi Chunara (ICWSM, 2020)

No Computation without Representation: Avoiding Data and Algorithm Biases through Diversity. - Caitlin Kuhlman; Latifa Jackson; Rumi Chunara (KDD, 2020)

Machine Learning in Population and Public Health. - Vishwali Mhasawade; Yuan Zhao; Rumi Chunara (CoRR, 2020)

Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty. - Umang Bhatt; Yunfeng Zhang; Javier Antorán; Q. Vera Liao; Prasanna Sattigeri; Riccardo Fogliato; Gabrielle Gauthier Melançon; Ranganath Krishnan; Jason Stanley; Omesh Tickoo; Lama Nachman; Rumi Chunara; et al. (CoRR, 2020)

COVID-19 transforms health care through telemedicine: Evidence from the field. - Devin M. Mann; Ji Chen; Rumi Chunara; Paul A. Testa; Oded Nov (J. Am. Medical Informatics Assoc., 2020)

Uncertainty as a Form of Transparency: Measuring, Communicating, and Using Uncertainty. - Umang Bhatt; Javier Antorán; Yunfeng Zhang; Q. Vera Liao; Prasanna Sattigeri; Riccardo Fogliato; Gabrielle Gauthier Melançon; Ranganath Krishnan; Jason Stanley; Omesh Tickoo; Lama Nachman; Rumi Chunara; et al. (AIES, 2021)

Causal Multi-level Fairness. - Vishwali Mhasawade; Rumi Chunara (AIES, 2021)

Fairness Violations and Mitigation under Covariate Shift. - Harvineet Singh; Rina Singh; Vishwali Mhasawade; Rumi Chunara (FAccT, 2021)

ICWSM 2021 Workshop on Data for the Wellbeing of Most Vulnerable: Promises and Challenges. - Yelena Mejova; Kyriaki Kalimeri; Daniela Paolotti; Rumi Chunara (ICWSM Workshops, 2021)

Telemedicine and healthcare disparities: a cohort study in a large healthcare system in New York City during COVID-19. - Rumi Chunara; Yuan Zhao; Ji Chen; Katharine Lawrence; Paul A. Testa; Oded Nov; Devin M. Mann (J. Am. Medical Informatics Assoc., 2021)

Machine learning and algorithmic fairness in public and population health. - Vishwali Mhasawade; Yuan Zhao; Rumi Chunara (Nat. Mach. Intell., 2021)

Segmenting across places: The need for fair transfer learning with satellite imagery. - Miao Zhang; Harvineet Singh; Lazarus Chok; Rumi Chunara (CVPR Workshops, 2022)

ICWSM 2022 Workshop on Data for the Wellbeing of Most Vulnerable: Global Problems, Local Solutions. - Yelena Mejova; Kyriaki Kalimeri; Daniela Paolotti; Rumi Chunara (ICWSM Workshops, 2022)

Data science in public health: building next generation capacity. - Nicholas Mirin; Heather Mattie; Latifa Jackson; Zainab Samad; Rumi Chunara (CoRR, 2022)

Fair contrastive pre-training for geographic images. - Miao Zhang; Rumi Chunara (CoRR, 2022)

Measures of Disparity and their Efficient Estimation. - Harvineet Singh; Rumi Chunara (AIES, 2023)

When do Minimax-fair Learning and Empirical Risk Minimization Coincide? - Harvineet Singh; Matthäus Kleindessner; Volkan Cevher; Rumi Chunara; Chris Russell 001 (ICML, 2023)

A Brief Tutorial on Sample Size Calculations for Fairness Audits. - Harvineet Singh; Fan Xia; Mi-Ok Kim; Romain Pirracchio; Rumi Chunara; Jean Feng (CoRR, 2023)

Mitigating Urban-Rural Disparities in Contrastive Representation Learning with Satellite Imagery. - Miao Zhang; Rumi Chunara (AIES (1), 2024)

Understanding Disparities in Post Hoc Machine Learning Explanation. - Vishwali Mhasawade; Salman Rahman; Zoé Haskell-Craig; Rumi Chunara (FAccT, 2024)

Impact on Public Health Decision Making by Utilizing Big Data Without Domain Knowledge. - Miao Zhang; Salman Rahman; Vishwali Mhasawade; Rumi Chunara (CoRR, 2024)

Generalization in Healthcare AI: Evaluation of a Clinical Large Language Model. - Salman Rahman; Lavender Yao Jiang; Saadia Gabriel; Yindalon Aphinyanaphongs; Eric Karl Oermann; Rumi Chunara (CoRR, 2024)

Leveraging CLIP for Inferring Sensitive Information and Improving Model Fairness. - Miao Zhang; Rumi Chunara (CoRR, 2024)

Disparate Effect Of Missing Mediators On Transportability of Causal Effects. - Vishwali Mhasawade; Rumi Chunara (CLeaR, 2025)

Quantifying Greenspace with Satellite Images in Karachi, Pakistan, Using a New Data Augmentation Paradigm. - Miao Zhang; Hajra Arshad; Manzar Abbas; Hamzah Jehanzeb; Izza Tahir; Javerya Hassan; Zainab Samad; Rumi Chunara (ACM J. Comput. Sustain. Soc., 2025)

Identifying and mitigating algorithmic bias in the safety net. - Shaina Mackin; Vincent J. Major; Rumi Chunara; Remle Newton-Dame (npj Digit. Medicine, 2025)

Cost-Efficient Continual Learning with Sufficient Exemplar Memory. - Dongkyu Cho; Taesup Moon; Rumi Chunara; Kyunghyun Cho; Sungmin Cha (CoRR, 2025)

Dealing with the Evil Twins: Improving Random Augmentation by Addressing Catastrophic Forgetting of Diverse Augmentations. - Dongkyu Cho; Rumi Chunara (CoRR, 2025)