Senior Principal Research Scientist
Optum AI, UnitedHealthGroup
Research Scientist, Apple Inc. (2020-22)
Postdoc at Statistics Department, Harvard University (2016-19)
Ph.D. in Information Science, Cornell University (2016)

I am interested in personalized and just-in-time intervention in the mobile health space. I build computational tools that analyze human behavior from phone data (e.g., sensors, self-input) and then intervenes in real time in ways that are personalized and contextualized to users' needs, daily routine, and the environments they live in.

Keywords: Adaptive health intervention, Mobile Sensing, Context-aware computing, Reinforcement learning, User-centered design

CV | Google Scholar

Short bio
I am a senior principal research scientist at Optum AI, part of UnitedHealthGroup. Before that, I was a Postdoc/Applied Research Scientist at Health AI at Apple, Inc (2020-2022). From 2016-19, I was a postdoc at Harvard University, where I was advised by Susan Murphy. I completed my PhD at Cornell University (2016). My PhD advisor was Tanzeem Chourdhury. I also had the opportunity to work with many amazing collaborators (Andrew Campbell, Predrag Klasnja, Nic Lane, Lama Nachman, Mi Zhang). I received my bacheor degree in computer science from Bangladesh University of Enigeering and Technology (BUET).

Past and upcoming invited talks


MyBehavior: Automatically turning mobile data into easy-to-follow suggestions using machine learning

MyBehavior learns a user's physical activity and dietary behavior from phone data and suggests personalized changes to these behaviors. MyBehavior is the first app that combined mobile data and reinforcement learning to provide personalized health recommendations.

See our JMIR and Ubicomp 2015 papers for more details on MyBehavior. We recently extended MyBehavior for chronic back pain and published an article in JMIR.

SARA: Just-in-time intervention for improving engagement

Self-report adherence of mobile health apps are generally low. SARA (Substance Abuse Research Assistant) is the first just-in-time intervention to increase self-report adherence with timely rewards or inspirational messages. Initial deployments of SARA target adolescents and younger adults at high risk of substance abuse.

Related papers: study protocol, results from micro-randomized trial, just-in-time intervention to improve substance use . See below the ADAPTS project that uses SARA for yonger adults with lukemia. A recent R01 grant is founded that will SARA on sickle cell disease patients.

Sub-goals: Automated personalized plan to achieve a daily health goal

The sub-goals app divides a daily goal into several sub-goals where each subgoal is assigned to a specific time segment of the day. When all sub-goals are added together, they sum to the daily goal. These sub-goals also reduce the burden as they ask users to be active when they are usually active. The time horizon to complete each subgoal is sooner than the daily goal, thus users will likely discount those rewards less and be more motivated. In iOS17, Apple shipped a feature similar to sub-goals in their Fitness+ app.


ReVibe uses context-assisted recall in the evening instead of in the moment Ecological Momentary Assessments (EMA) to increase self-report adherance


ADAPTS foucs on younger adults with lukemia and is 6-month long just-in-time intervention to improve self-report adherence on behavioral factors related to medication adherence.

Glucose spike control

Repeated glucose spikes can develop type-2 diabetes (T2D) or worsen existing T2D. This project creates a just-in-time walking intervention to curb glucose spikes before they reach harmful levels.

pi2 messages

pi2 messages are pesonalized just-in-time physical activity messages that use data-driven insights of a user's usual activity levels and progress towards their goals.


Mobilyze focueses on people with depression. It uses gamification and sensing to encourage visiting places a user is familiar with. Broadening these visited locations can improve depressive symptoms.


StressSense app infers stressful conversations in continuously-sensed audio data from phone microphones.
🏆 Receipient of 2022 10-year impact award at Ubicomp.


BeWell app provides multi-dimensional feedback on daily physical activity, sleep and socialization.

Mental health sensing

This 2011 project on passive sensing of mental health using audio and accelerometer data, kickstarted the research in mental health sensing.


NeuroPhone detects P-300 brain signal from an off-the-shelf EEG headsets on the phone.


MoodRhythm uses sensor-based biomarkers to improve symptoms of bipolar disorder by stabilizing daily routines.


Citation count: 3236 (updated December 31, 2023)

Google scholar contains a more up-to-date publication list.

Refereed conference and journal publications

  1. 28.

    Tianchen Qian, Ashley E Walton, Linda M Collins, Predrag Klasnja, Stephanie T Lanza, Inbal Nahum-Shani, Mashfiqui Rabbi, Michael A Russell, Maureen A Walton, Hyesun Yoo, Susan A Murphy The microrandomized trial for developing digital interventions: Experimental design and data analysis considerations. Psychological methods. 2022 [pdf]
  2. 27.

    Lara N Coughlin, Inbal Nahum-Shani, Erin E Bonar, Meredith L Philyaw-Kotov, Mashfiqui Rabbi, Predrag Klasnja, Maureen A Walton Toward a just-in-time adaptive intervention to reduce emerging adult alcohol use: testing approaches for identifying when to intervene. Substance use & misuse 56 (14), 2115-2125 [pdf]
  3. 26.

    Inbal Nahum-Shani, Mashfiqui Rabbi, Jamie Yap, Meredith L Philyaw-Kotov, Predrag Klasnja, Erin E Bonar, Rebecca M Cunningham, Susan A Murphy, Maureen A Walton Translating strategies for promoting engagement in mobile health: A proof-of-concept microrandomized trial. Health Psychology, 40(12), 974–987 [pdf]
  4. 25.

    Ananya Bhattacharjee, SM Taiabul Haque, Md Abdul Hady, SM Raihanul Alam, Mashfiqui Rabbi, Muhammad Ashad Kabir, Syed Ishtiaque Ahmed Understanding the social determinants of mental health of undergraduate students in Bangladesh: Interview study JMIR Formative Research 2021;5(11):e27114 [pdf]
  5. 24.

    Alexandra M Psihogios, Mashfiqui Rabbi, Annisa Ahmed, Elise R McKelvey, Yimei Li, Jean-Philippe Laurenceau, Stephen P Hunger, Linda Fleisher, Ahna LH Pai, Lisa A Schwartz, Susan A Murphy, Lamia P Barakat Understanding adolescent and young adult 6-mercaptopurine adherence and mHealth engagement during cancer treatment: protocol for ecological momentary assessment JMIR Research Protocol 2021;10(10):e32789 [pdf]
  6. 23.

    Lara N Coughlin, Inbal Nahum-Shani, Meredith L Philyaw-Kotov, Erin E Bonar, Mashfiqui Rabbi, Predrag Klasnja, Susan Murphy, Maureen A Walton Developing an Adaptive Mobile Intervention to Address Risky Substance Use Among Adolescents and Emerging Adults: sability Study JMIR Mhealth Uhealth 2021;9(1):e24424 [Impact factor 4.3] [pdf]
  7. 22.

    Shuang Li, Alexandra M Psihogios, Elise R McKelvey, Annisa Ahmed, Mashfiqui Rabbi, Susan Murphy Microrandomized trials for promoting engagement in mobile health data collection: Adolescent/young adult oral chemotherapy adherence as an example Current Opinion in Systems Biology, (2020), Elsevier
  8. 21.

    Mashfiqui Rabbi, Katherine Li, H Yanna Yan, Kelly Hall, Predrag Klasnja, 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, 4, 1--27 (2019), ACM New York, NY, USA:[pdf]
  9. 20.

    Marianne Menictas*, Mashfiqui Rabbi*, Predrag Klasnja, Susan Murphy Artificial intelligence decision-making in mobile health The Biochemist, 41, 5, 20--24 (2019):[pdf] * authors equally contributed
  10. 19.

    Mashfiqui Rabbi, Predrag Klasnja, Tanzeem Choudhury, Ambuj Tewari, and Susan Murphy. Optimizing mHealth Interventions with a Bandit Mobile Sensing and Digital Phenotyping: New Developments in Psychoinformatics, Springer: Berlin [preprint]
  11. 18.

    Mashfiqui Rabbi, 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. [Impact factor 4.6] [pdf]
  12. 17.

    Mashfiqui Rabbi, 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): e166. [pdf]
  13. 16.

    Mashfiqui Rabbi, Min Hane Aung, and Tanzeem Choudhury. Towards health recommendation systems: an approach for providing automated personalized health feedback from mobile data. In: Rehg J., Murphy S., Kumar S. (eds) Mobile Health. Springer, Cham, 2017 [pdf]
  14. 15.

    Eun Kyoung Choe, Saeed Abdullah, Mashfiqui Rabbi, Edison Thomaz, Daniel A. Epstein, Felicia Cordeiro, Matthew Kay et al. Semi-automated tracking: A balanced approach for self-monitoring applications. IEEE Pervasive Computing 16, no. 1 (2017): 74-84.[pdf]
  15. 14.

    Aung, Min S. Hane, Faisal Alquaddoomi, Cheng-Kang Hsieh, Mashfiqui Rabbi, Longqi Yang, John P. Pollak, Deborah Estrin, and Tanzeem Choudhury. Leveraging multi-modal sensing for mobile health: a case review in chronic pain. IEEE Journal of Selected Topics in Signal Processing 10, no. 5 (2016): 962-974.[ pdf]
  16. 13.

    Mashfiqui Rabbi, Jean Costa, Fabian Okeke, Max Schachere, Mi Zhang, and Tanzeem Choudhury. An Intelligent Crowd-worker Selection Approach for Reliable Content Labeling of Food Images. The Proceedings of Wireless Health 2015 [pdf].
  17. 12.

    Mashfiqui Rabbi, Min Hane Aung, Mi Zhang and Tanzeem Choudhury. MyBehavior: Automatic Personalized Health Feedback from User Behavior and Preference using Smartphones. The 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing (Ubicomp 2015) [pdf]
  18. 11.

    Mashfiqui Rabbi, 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 uHealth 2015;3(2):e42 [Impact factor 4.7] [pdf]
  19. 10.

    Phil Adams, 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. International Conference on Pervasive Computing Technologies for Healthcare, 2014 [pdf]
  20.  9.

    Nicholas D. Lane, Mu Lin, Mashfiqui Rabbi, Xiaochao Yang, Hong Lu, Giuseppe Cardone, Shahid Ali, Ethan Berke, Andrew T. Campbell, Tanzeem Choudhury Bewell: Sensing sleep, physical activities and social interactions to promote wellbeing. Mobile Networks and Applications 19, no. 3 (2014): 345-359 [pdf]
  21.  8.

    Mu Lin, Nicholas Lane, Mashfiqui Rabbi, Xiaochao Yang, Hong Lu, Giuseppe Cardone, Shahid Ali, Afsaneh Doryab, Ethan Berke, Andrew Campbell, and Tanzeem Choudhury. BeWell+: Multi-dimensional Wellbeing Monitoring with Community-guided User Feedback and Energy Optimization Appears in the Proceedings of Wireless Health 2012, October 2012 [pdf]
  22.  7.

    Hong Lu, Mashfiqui Rabbi, Gokul Chittaranjan, Denise Frauendorfer, Marianne Schmidt, Andrew Campbell, Daneil Gatica-Perez, and Tanzeem Choudhury. StressSense: Detecting Stress in Unconstrained Acoustic Environments using Smartphones. Appears in the Proceedings of Ubicomp 2012, September 2012 [pdf]
  23.  6.

    Mashfiqui Rabbi, Shahid Ali, Tanzeem Choudhury, and Ethan Berke. Passive and In-situ Assessment of Mental and Physical Well-being using Mobile Sensors. To appear in the Proceedings of Ubicomp 2011, September 2011. Beijing, China. [pdf]
  24.  5.

    Ethan Berke, Tanzeem Choudhury, Shahid Ali, and Mashfiqui Rabbi. Objective Sensing of Activity and Sociability: Mobile Sensing in the Community. Appears in the Annals of Family Medicine, Volume 9, Issue 4, Pages 344-350, July 2011. [pdf] [commentary]
  25.  4.

    Nicholas D. Lane, Mashfiqui Rabbi, Mu Lin, Xiaochao Yang, Afsaneh Doryab, Hong Lu, Shahid Ali, Tanzeem Choudhury, Andrew Campbell, and Ethan Berke, BeWell: A Smartphone Application to Monitor, Model and Promote Wellbeing, Pervasive Health 2011-- 5th International ICST Conference on Pervasive Computing Technologies for Healthcare, Dublin, 23-26 May 2011 [pdf]
  26.  3.

    Andrew T. Campbell, Tanzeem Choudhury, Shaohan Hu, Hong Lu, Matthew Mukerjee, Mashfiqui Rabbi, and Rajeev Raizada. NeuroPhone: Brain-Mobile Phone Interface using a Wireless EEG Headset. Appears in the Proceedings of MobiHeld 2010 [pdf]
  27.  2.

    M Jawaherul Alam, Md Abul Hassan Samee, Mashfiqui Rabbi, and Md Saidur Rahman. Minimum-Layer Upward Drawings of Trees. J. Graph Algorithms and Applications 14, no. 2 (2010): 245-267. [pdf]
  28.  1.

    M Jawaherul Alam, Mashfiqui Rabbi, and Md Saidur Rahman. Upright Drawings of Planar Graphs on Three Layers. Journal of Applied Mathematics and Informatics, 28(56): 1347-1358, 2010 [pdf]

Lightly reviewed posters and workshop papers

  1. 6.

    Mashfiqui Rabbi, Meredith Philyaw-Kotov, Jinseok Lee, Anthony Mansour, Laura Dent, Xiaolei Wang, Rebecca Cunningham et al. SARA: a mobile app to engage users in health data collection In Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers, pp. 781-789. ACM, 2017. [pdf]
  2.  5.

    Mashfiqui Rabbi, Thiago Caetano, Jean Costa, Saeed Abdullah, Mi Zhang, and Tanzeem Choudhury. SAINT: A Scalable Sensing and Inference Toolkit. Hotmobile 2015 poster [pdf]
  3.  4.

    Mashfiqui Rabbi, Syed Ishtiaque Ahmed. Sensing stress network for social coping CSCW Interactive Poster Session, 2014 [pdf | poster]
  4.  3.

    Steven Voida, Mark Matthews, Saeed Abdullah, Mengxi C. Chi, Mattew Green, W. J. Jang, D. Hu, Jon Weinrich, P. Patil, Mashfiqui Rabbi, et al. Moodrhythm: tracking and supporting daily rhythms.In Proceedings of the 2013 ACM conference on Pervasive and ubiquitous computing adjunct publication, pages 67-70. ACM, 2013 [pdf]
  5.  2.

    Stephen Voida, Tanzeem Choudhury, Geri Gay, Mark Matthews, Phil Adams, Mashfiqui Rabbi, JP Pollak, Mengxi Chi, Matthew Green, Andrew Campbell, Nic Lane, and Hong Lu. Personal Informatics Can Be Stressful: Collecting, Reflecting, and Embedding Stress Data in Personal Informatics. To Appear in the Proceeding of Personal Informatics Workshop, CHI. [pdf]
  6.  1.

    Mashfiqui Rabbi, Chien wen Yuan, and Kirsikka Kaipaien. An exploratory study to identify opportune moments in everyday life to promote healthy eating.Poster in ISBNPA, 2013 [pdf]

Ph.D. Thesis