Hello! 
I am an interdisciplinary researcher who works at the intersection of HCI, behavior science, and AI/ML. I am interested in improving human data collection for AI development and personalizing user experiences at scale.
My research contributions have been applied across diverse fields, including behavior sciences, search and recommendation systems, wearable computing, crowdsourcing, and developer tools.
I work at MongoDB as their first Quantitative User Researcher, personalizing developer experiences for the Atlas platform. I was also a Research Scientist at Spotify, where I was a member of the Human-in-the-AI (HAI) Lab, focused on human evaluation of interactive recommender systems and scalable content understanding methods for long-tail recommendations.
I completed my PhD in Computer and Behavior Sciences from Northeastern University, Boston, MA working with Prof. Stephen Intille. For my dissertation, I introduced a novel experience sampling method using smartwatches to collect large-scale personalized self-report data in real-world settings. In addition, I built open-source tools to perform multi-level modeling and AI-assisted annotation of longitudinal user behavior data for pattern recognition tasks.
I regularly publish my work in peer-reviewed venues including PACM IMWUT (UbiComp), CSCW, IUI, WebSci, CHI PLAY, NeurIPS Workshops, Behavior Research Methods, Journal of Medical Internet Research, and Translational Behavior Medicine. I am always excited about new product-oriented research or applied science opportunities.
Updates
Jan, 2025 🔎 Excited to be the Associate Chair of CHI 2025, Late Breaking Work (LBW) track. Send in your most exciting work!
Nov, 2024. 🚀 Our PACM IMWUT paper on personalized adaptive experience sampling is now available on ACM DL.
Oct, 2024. ⌚ Had a great time giving an invited talk at BostonCHI on “Scaling Experience Sampling with Microinteractions”
Jun, 2024. 🙏 Thanks to everyone who attended my QuantUXCon talk on “Scaling Experience Sampling with Smartwatch Interactions.” Here are the slides for those interested.
May, 2024. 🎙️ Gave an invited lecture on human-centered recommender systems, focusing on music and podcast recommendations at Northeastern University.
May, 2024. 🎸 Our Spotify R&D blog on large-scale patterns in new music streaming behavior is now live.
April, 2024. 🎹 I was interviewed by the Industry PLaylist newsletter, India’s leading source of indie music news on music recommendations and new music streaming behavior.
April, 2024. 👨🎤 Our ACM WebSci’24 paper on the first large-scale analysis of new music streaming behavior patterns is now available on ACM DL.
Past updates
Oct, 2023. 🏆 Our PACM IMWUT paper on long-term contextual biases in micro-EMA non-response received the distinguished paper award (~1% award rate).
Sept, 2023. 🙂 Finally concluded my last organized talk at BostonCHI as a chair. This is a special one by Gregory Abowd on the CHI Lifetime Achievement award.
Jun, 2023. Our intensive longitudinal data collection in TIME study is complete. Stay tuned for the year-long longitudinal data on behaviors and decision-making to go live!
April, 2023. 🎙️ Our Spotify R&D blogpost on goal-based podcast recommendations from our IUI’23 paper is now live.
Sept, 2022. Presented our PACM IMWUT paper on contextual biases with micro-EMA non-response at UbiComp 2022. Was great to meet a lot of old collaborators and friends.
Feb, 2022. 🎮 Was interviewed by VentureBeat magazine on using videogames to generate large-scale AI training data.