Hello!

I am an interdisciplinary researcher at the intersection of Human-Computer Interaction (HCI), Behavior Science, and Applied AI. My research uses human behavioral data to address two distinct problems: measuring how users experience AI-powered products, and evaluating AI model behavior against human judgment. I develop methods and frameworks for behavioral measurement, human data collection, and AI evaluation — applied across recommendation systems, developer tools, agentic AI experiences, and wearable health.

I am currently a Staff Researcher at MongoDB, leading quantitative UX research and behavioral AI evaluation for developer-facing AI products — including benchmark design to assess how large language models handle real-world developer tasks. Previously, I was a Research Scientist at Spotify in the Human-in-the-AI (HAI) Lab, where I focused on human evaluation of recommender systems and modeling users’ interactions with the platform.

I completed my PhD in Human-Computer Interaction from Northeastern University (Boston, MA), working with Stephen Intille. I introduced a novel experience-sampling method using smartwatches (and multimodal sensor signals) to collect large-scale, personalized self-report data in real-world settings. I also built open-source tools for multi-level modeling and AI-assisted annotation of longitudinal behavioral data—adopted in NIH-funded workshops and downloaded over 2,000 times—to support behavioral modeling and train pattern recognition algorithms.

I regularly publish my work in highly competitive venues, including PACM IMWUT (UbiComp), PACM CSCW, ACM IUI, NeurIPS Workshops, Behavior Research Methods, JMIR, and Translational Behavior Medicine.

I live in the Greater Boston Area, enjoying the beautiful New England 🍁 with my wife, daughter, and our dog Sushi 🍣

I am always excited about new product-oriented research or applied science opportunities.

Updates

Sep 2026 🎓 Chairing ACM IUI doctoral consortium. Our call for proposals is now live. Deadline is Oct 19, 2026. Send in your best work in progress and get feedback from experts!

Aug 2026 ⌚ Presented microEMA research at a panel focused on reducing response burden in longitudinal data collection, as part of the Society for Ambulatory Assessment (SAA 2026 conference in Vienna, Austria

April 2026 📌 Gave a seminar talk at Georgia Tech on “Modeling User Preferences using Explicit and Implicit Signals,” hosted by Prof. Andrea Parker

Jan, 2026 💡 Our paper titled “Semantically Enriching Personal Mobility Data using OpenStreetMap: A Case Study using Smartphone Users’ Frequently Visited Places” has been accepted by the Journal of Location-based Services.

Nov, 2025 🥇 Presented our personalized experience sampling approach at QuantUXCOn 2025. Jixin Li led the presentation.

Oct, 2025 🤖 Gave a seminar talk at Bentley University on “Interfaces for human data collection for AI and pattern recognition”, summarizing my research in this area over the past 6 years.

Oct, 2025 🔬 Our longitudinal evaluation of microinteraction ecological momentary assessment is now available on ACM DL. We are presenting this work, along with personalized experience sampling at ACM UbiComp 2025, in Espoo, Finland.

Aug, 2025 📝 Excited to join as an Associate Chair for CHI 2026 Computational Interaction subcommittee. Send in your best work!

July, 2025 🎉 Paper titled “Longitudinal User Engagement with Microinteraction Ecological Momentary Assessment (μEMA)” accepted at Proceedings of the ACM IMWUT!

April, 2025 🤗 TIME study data codebook is now public! This is one of the most intense multimodal behavior datasets. We can’t wait to see what you build with it.