Mashfiqui Rabbi

For More Information

• Mashfiqui Rabbi's home page
• Google Scholar

Education

• Postdoc, Statistics Department, Harvard University, 2017-19
• PhD, Information Science, Cornell University, 2016
• Bachelor of Science, Computer Science and Engineering, Bangladesh University of Engineering and Technology, 2008

Biography

Mashfiqui Rabbi is an assistant research professor at the Siebel School of Computing and Data Science. Previously he was a senior research scientist at Optum AI under UnitedHealth Group, the largest payer and one of the largest providers in US healthcare. Before Optum, Mashfiqui was a research scientist at Apple Health AI and a postdoctoral fellow at Harvard University, where he worked with Professor Susan Murphy. Before his postdoc, he received a Ph.D. in Information Science from Cornell University. His Ph.D. advisor was Professor Tanzeem Choudhury. Mashfiqui's Ph.D. thesis led to the creation of the MyBehavior app, the first mobile recommender system to automatically generate personalized physical activity and food suggestions from mobile phone data. In his postdoc at Harvard, Mashfiqui created the first just-in-time intervention for improving health app engagement. This engagement intervention was later adopted by multiple NIH-funded grants focusing on youth substance abuse, cancer rehabilitation, and sickle cell disease. Mashfiqui also helped establish the AI-based intervention group at Apple's Health AI team, and his sub-goal app was adopted for the customized plan feature in Apple's Fitness+ app, which is currently used by millions of iPhone users. Mashfiqui's work has also been featured in MIT Technology Review, New Scientist, the Economist, Mashable, and the NY Times.

Other Professional Employment

• Applied Research Scientist, Health AI, Apple Inc., 2020-22
• Senior Principal Research Scientist, Optum Labs, UnitedHealthGroup, 2022-25

Resident Instruction

• CS 598: AI Applied to Behavioral Health (Spring 2026)

Research Interests

• Mobile health
• Mobile and wearable sensing
• Personalized and just-in-time interventions
• Sequential experimentation and reinforcement learning
• Applied machine learning

Selected Articles in Journals

• Rabbi, Mashfiqui, Angela Pfammatter, Mi Zhang, Bonnie Spring, and Tanzeem Choudhury. "Automated personalized feedback for physical activity and dietary behavior change with mobile phones: a randomized controlled trial on adults." JMIR mHealth and uHealth 3, no. 2 (2015): e4160.
• Rabbi, Mashfiqui, Meredith Philyaw Kotov, Rebecca Cunningham, Erin E. Bonar, Inbal Nahum-Shani, Predrag Klasnja, Maureen Walton, and Susan Murphy. "Toward increasing engagement in substance use data collection: development of the substance abuse research assistant app and protocol for a microrandomized trial using adolescents and emerging adults." JMIR research protocols 7, no. 7 (2018): e9850.
• Rabbi, Mashfiqui, Min SH Aung, Geri Gay, M. Cary Reid, and Tanzeem Choudhury. "Feasibility and acceptability of mobile phone–based auto-personalized physical activity recommendations for chronic pain self-management: pilot study on adults." Journal of medical Internet research 20, no. 10 (2018): e10147.
• Nahum-Shani, Inbal, Mashfiqui Rabbi, Jamie Yap, Meredith L. Philyaw-Kotov, Predrag Klasnja, Erin E. Bonar, Rebecca M. Cunningham, Susan A. Murphy, and Maureen A. Walton. "Translating strategies for promoting engagement in mobile health: A proof-of-concept microrandomized trial." Health Psychology 40, no. 12 (2021): 974.
• Qian, Tianchen, Ashley E. Walton, Linda M. Collins, Predrag Klasnja, Stephanie T. Lanza, Inbal Nahum-Shani, Mashfiqui Rabbi et al. "The microrandomized trial for developing digital interventions: Experimental design and data analysis considerations." Psychological methods 27, no. 5 (2022): 874.

Articles in Conference Proceedings

• Lane, Nicholas D., Mashfiqui Rabbi, Mu Lin, Xiaochao Yang, Hong Lu, Shahid Ali, Afsaneh Doryab, Ethan Berke, Tanzeem Choudhury, and Andrew Campbell. "Bewell: A smartphone application to monitor, model and promote wellbeing." In 5th international ICST conference on pervasive computing technologies for healthcare, vol. 10. 2011.
• Rabbi, Mashfiqui, Shahid Ali, Tanzeem Choudhury, and Ethan Berke. "Passive and in-situ assessment of mental and physical well-being using mobile sensors." In Proceedings of the 13th international conference on Ubiquitous computing, pp. 385-394. 2011.
• Lu, Hong, Mashfiqui Rabbi, Denise Frauendorfer,  Marianne Schmid Mast, Gokul T. Chittaranjan, Andrew T. Campbell, Daniel Gatica-Perez, and Tanzeem Choudhury. "Stresssense: Detecting stress in unconstrained acoustic environments using smartphones." In Proceedings of the 2012 ACM conference on ubiquitous computing, pp. 351-360. 2012.
• Adams, Phil, Mashfiqui Rabbi, Tauhidur Rahman, Mark Matthews, Amy Voida, Geri Gay, Tanzeem Choudhury, and Stephen Voida. "Towards personal stress informatics: comparing minimally invasive techniques for measuring daily stress in the wild." In Proceedings of the 8th International Conference on Pervasive Computing Technologies for Healthcare, pp. 72-79. 2014.
• Rabbi, Mashfiqui, Min Hane Aung, Mi Zhang, and Tanzeem Choudhury. "MyBehavior: automatic personalized health feedback from user behaviors and preferences using smartphones." In Proceedings of the 2015 ACM international joint conference on pervasive and ubiquitous computing, pp. 707-718. 2015.
• Rabbi, Mashfiqui, Katherine Li, H. Yanna Yan, Kelly Hall, Predrag Klasnja, and Susan Murphy. "ReVibe: a context-assisted evening recall approach to improve self-report adherence." Proceedings of the ACM on interactive, mobile, wearable and ubiquitous technologies 3, no. 4 (2019): 1-27.

Research Honors

• 2022 Ubicomp 10 year impact award