Visualization of time-series sensor data to inform the design of just-in-time adaptive stress interventions. - Moushumi Sharmin; Andrew Raij; David H. Epstein; Inbal Nahum-Shani; J. Gayle Beck; Sudip Vhaduri; Kenzie Preston; Santosh Kumar 001 (UbiComp, 2015)

Center of excellence for mobile sensor data-to-knowledge (MD2K). - Santosh Kumar 001; Gregory D. Abowd; William T. Abraham; Mustafa al'Absi; J. Gayle Beck; Duen Horng Chau; Tyson Condie; David E. Conroy; Emre Ertin; Deborah Estrin; Deepak Ganesan; Cho Lam; et al. (J. Am. Medical Informatics Assoc., 2015)

Finding Significant Stress Episodes in a Discontinuous Time Series of Rapidly Varying Mobile Sensor Data. - Hillol Sarker; Matthew Tyburski; Md. Mahbubur Rahman; Karen Hovsepian; Moushumi Sharmin; David H. Epstein; Kenzie L. Preston; C. Debra Furr-Holden; Adam Milam; Inbal Nahum-Shani; Mustafa al'Absi; Santosh Kumar 001 (CHI, 2016)

From Markers to Interventions: The Case of Just-in-Time Stress Intervention. - Hillol Sarker; Karen Hovsepian; Soujanya Chatterjee; Inbal Nahum-Shani; Susan A. Murphy; Bonnie Spring; Emre Ertin; Mustafa al'Absi; Motohiro Nakajima; Santosh Kumar 001 (Mobile Health - Sensors, Analytic Methods, and Applications, 2017)

SARA: a mobile app to engage users in health data collection. - Mashfiqui Rabbi; Meredith Philyaw-Kotov; Jinseok Lee; Anthony Mansour; Laura Dent; Xiaolei Wang; Rebecca M. Cunningham; Erin E. Bonar; Inbal Nahum-Shani; Predrag V. Klasnja; Maureen A. Walton; Susan A. Murphy (UbiComp/ISWC Adjunct, 2017)

ewrapper: operationalizing engagement strategies in mHealth. - Blake Wagner III; Elaine Liu; Steven D. Shaw; Gleb Iakovlev; Linlu Zhou; Christina N. Harrington; Gregory D. Abowd; Carolyn Yoon; Santosh Kumar 001; Susan A. Murphy; Bonnie Spring; Inbal Nahum-Shani (UbiComp/ISWC Adjunct, 2017)

Center of Excellence for Mobile Sensor Data-to-Knowledge (MD2K). - Santosh Kumar 001; Gregory D. Abowd; William T. Abraham; Mustafa al'Absi; Duen Horng Chau; Emre Ertin; Deborah Estrin; Deepak Ganesan; Timothy Hnat; Syed Monowar Hossain; Zachary G. Ives; Jacqueline Kerr; et al. (IEEE Pervasive Comput., 2017)

ewrapper: Perceived Receptivity to Engagement Strategies in mHealth. - Blake Wagner III; Michael Barskey; Inbal Nahum-Shani; Sun Young Park (CSCW Companion, 2019)

A Robust Functional EM Algorithm for Incomplete Panel Count Data. - Alexander Moreno; Zhenke Wu; Jamie Yap; Cho Lam; David W. Wetter; Inbal Nahum-Shani; Walter H. Dempsey; James M. Rehg (NeurIPS, 2020)

A Functional EM Algorithm for Panel Count Data with Missing Counts. - Alexander Moreno; Zhenke Wu; Jamie Yap; David W. Wetter; Cho Lam; Inbal Nahum-Shani; Walter H. Dempsey; James M. Rehg (CoRR, 2020)

Translating Behavioral Theory into Technological Interventions: Case Study of an mHealth App to Increase Self-reporting of Substance-Use Related Data. - Mashfiqui Rabbi; Meredith Philyaw-Kotov; Jinseok Li; Katherine Li; Bess Rothman; Lexa Giragosian; Maya Reyes; Hannah Gadway; Rebecca M. Cunningham; Erin E. Bonar; Inbal Nahum-Shani; Maureen A. Walton; et al. (CoRR, 2020)

The Micro-Randomized Trial for Developing Digital Interventions: Experimental Design Considerations. - Ashley E. Walton; Linda M. Collins; Predrag V. Klasnja; Inbal Nahum-Shani; Mashfiqui Rabbi; Maureen A. Walton; Susan A. Murphy (CoRR, 2020)

Transformers for prompt-level EMA non-response prediction. - Supriya Nagesh; Alexander Moreno; Stephanie Marita Carpenter; Jamie Yap; Soujanya Chatterjee; Steven Lloyd Lizotte; Neng Wan; Santosh Kumar 001; Cho Lam; David W. Wetter; Inbal Nahum-Shani; James M. Rehg (CoRR, 2021)

Dynamic models of stress-smoking responses based on high-frequency sensor data. - Sahar Hojjatinia; Elyse R. Daly; Timothy Hnat; Syed Monowar Hossain; Santosh Kumar 001; Constantino M. Lagoa; Inbal Nahum-Shani; Shahin Alan Samiei; Bonnie Spring; David E. Conroy (npj Digit. Medicine, 2021)

Designing Reinforcement Learning Algorithms for Digital Interventions: Pre-Implementation Guidelines. - Anna L. Trella; Kelly W. Zhang; Inbal Nahum-Shani; Vivek Shetty; Finale Doshi-Velez; Susan A. Murphy (Algorithms, 2022)

New Directions for Motivational Incentive Interventions for Smoking Cessation. - Lara N. Coughlin; Erin E. Bonar; Maureen A. Walton; Anne C. Fernandez; Isabelle Duguid; Inbal Nahum-Shani (Frontiers Digit. Health, 2022)

MCMTC: A Pragmatic Framework for Selecting an Experimental Design to Inform the Development of Digital Interventions. - Inbal Nahum-Shani; John J. Dziak; David W. Wetter (Frontiers Digit. Health, 2022)

mRisk: Continuous Risk Estimation for Smoking Lapse from Noisy Sensor Data with Incomplete and Positive-Only Labels. - Md. Azim Ullah; Soujanya Chatterjee; Christopher P. Fagundes; Cho Lam; Inbal Nahum-Shani; James M. Rehg; David W. Wetter; Santosh Kumar 001 (Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2022)

Reward Design for an Online Reinforcement Learning Algorithm Supporting Oral Self-Care. - Anna L. Trella; Kelly W. Zhang; Inbal Nahum-Shani; Vivek Shetty; Finale Doshi-Velez; Susan A. Murphy (AAAI, 2023)

Dyadic Reinforcement Learning. - Shuangning Li; Lluis Salvat Niell; Sung Won Choi; Inbal Nahum-Shani; Guy Shani; Susan A. Murphy (CoRR, 2023)

Multiple imputation of missing data in multilevel ecological momentary assessments: an example using smoking cessation study data. - Linying Ji; Yanling Li; Lindsey N. Potter; Cho Lam; Inbal Nahum-Shani; David W. Wetter; Sy-Miin Chow (Frontiers Digit. Health, 2023)

Time-varying model of engagement with digital self reporting: Evidence from smoking cessation longitudinal studies. - Michael Sobolev; Aditi Anand; John J. Dziak; Lindsey N. Potter; Cho Lam; David W. Wetter; Inbal Nahum-Shani (Frontiers Digit. Health, 2023)

Editorial: Digital technology for tobacco control: Novel data collection, study designs, and interventions. - Lindsey N. Potter; Inbal Nahum-Shani; David W. Wetter (Frontiers Digit. Health, 2023)

ReBandit: Random Effects Based Online RL Algorithm for Reducing Cannabis Use. - Susobhan Ghosh; Yongyi Guo; Pei-Yao Hung; Lara N. Coughlin; Erin E. Bonar; Inbal Nahum-Shani; Maureen A. Walton; Susan A. Murphy (IJCAI, 2024)

Monitoring Fidelity of Online Reinforcement Learning Algorithms in Clinical Trials. - Anna L. Trella; Kelly W. Zhang; Inbal Nahum-Shani; Vivek Shetty; Iris Yan; Finale Doshi-Velez; Susan A. Murphy (CoRR, 2024)

Oralytics Reinforcement Learning Algorithm. - Anna L. Trella; Kelly W. Zhang; Stephanie Marita Carpenter; David Elashoff; Zara M. Greer; Inbal Nahum-Shani; Dennis Ruenger; Vivek Shetty; Susan A. Murphy (CoRR, 2024)

MiWaves Reinforcement Learning Algorithm. - Susobhan Ghosh; Yongyi Guo; Pei-Yao Hung; Lara N. Coughlin; Erin E. Bonar; Inbal Nahum-Shani; Maureen A. Walton; Susan A. Murphy (CoRR, 2024)

Effective Monitoring of Online Decision-Making Algorithms in Digital Intervention Implementation. - Anna L. Trella; Susobhan Ghosh; Erin E. Bonar; Lara N. Coughlin; Finale Doshi-Velez; Yongyi Guo; Pei-Yao Hung; Inbal Nahum-Shani; Vivek Shetty; Maureen A. Walton; Iris Yan; Kelly W. Zhang; et al. (CoRR, 2024)

A Deployed Online Reinforcement Learning Algorithm in an Oral Health Clinical Trial. - Anna L. Trella; Kelly W. Zhang; Hinal Jajal; Inbal Nahum-Shani; Vivek Shetty; Finale Doshi-Velez; Susan A. Murphy (AAAI, 2025)

Reinforcement Learning on Dyads to Enhance Medication Adherence. - Ziping Xu; Hinal Jajal; Sung Won Choi; Inbal Nahum-Shani; Guy Shani; Alexandra M. Psihogios; Pei-Yao Hung; Susan A. Murphy (AIME (1), 2025)

Reinforcement Learning on AYA Dyads to Enhance Medication Adherence. - Ziping Xu; Hinal Jajal; Sung Won Choi; Inbal Nahum-Shani; Guy Shani; Alexandra M. Psihogios; Pei-Yao Hung; Susan A. Murphy (CoRR, 2025)

"It felt more real": Investigating the User Experience of the MiWaves Personalizing JITAI Pilot Study. - Susobhan Ghosh; Pei-Yao Hung; Lara N. Coughlin; Erin E. Bonar; Yongyi Guo; Inbal Nahum-Shani; Maureen A. Walton; Mark W. Newman; Susan A. Murphy (CoRR, 2025)