I am an Assistant Professor (Research) at the Graduate School of Education and Computer Science (by courtesy) at Stanford University. I am also the Ram and Vijay Shriram Faculty Fellow at the Institute for Human-Centered AI (HAI) and a core faculty member of Stanford HCI. My research asks how we design AI to extend human thinking rather than replace it. I take a cognitively grounded approach to HCI, studying how people build knowledge through acts of creation: writing arguments, building models, drawing diagrams. I then design interfaces that make these cognitive structures visible and interactive, so that AI can meaningfully participate in the process without taking it over. This work spans AI thinking tools that preserve learners' roles as active creators, pedagogical systems that help teachers see and support how students learn, and design methods that give educators real agency in shaping the AI tools entering their classrooms. I received my MS and PhD in Information from the University of Michigan School of Information, advised by Eytan Adar.

Across seven modules we introduce various topics important for understanding science in the news, including correlation and causation, sampling and selection in experiments, effect size, and source reliability. For each unit we provide teaching materials in the form of PowerPoint and PDFs to be taught in the classroom, lesson plans, and student activities/homework.

• Vincent Cavez
• David Chuan-En Lin (co-advised with Sean Follmer)

• Zoe Kaputa (co-advised with James Landay)
• Neha Rajagopalan (co-advised with Bruce McCandliss)
• Alberto Tono (co-advised with Martin Fischer)

• Anna Gutowska, Stanford CS
• Marielle Zheng, Stanford GSE
• Oliver Huang, University of Toronto
• Xinman (yoyo) Liu, Stanford GSE
• Nidhi Parthasarathy, Lynbrook High School
• Anika Rajaram, Harker High School
• Zoe Kaputa, MS, Stanford CS
• Priyanshi Sharma, Stanford GSE
• Nikki Nasseri, Berkeley Ed
• Lena Hegemann, Aalto University
• Momin Siddiqui, MS, Georgia Tech
• Mayank Sharma, MS, Stanford GSE
• Kaiyu Ren, BS, Stanford CS
• Anchal Sayal, MS, Stanford GSE
• Seonghee Lee, MS, Stanford CS
• Wengxi Li, MS, University of Michigan
• Yiling Zhao, MS, Stanford GSE
• Dylan Iskander, BS, Stanford GSE
• Neha Gupta, PhD, Duke University
• Maho Kohga, MS, Stanford GSE
• Jasmine Shih, MS, Stanford CS
• Miroslav Ivan Suzara, PhD, Stanford GSE
• Vishal Mohanty, MS, Stanford CS
• Madhurima Mahajan, MS, Material Science
• Mei Tan, MS, Stanford GSE
• Chris Pondoc, MS, Stanford CS
• Kelly Chen, MS, Stanford CS
• Jenny Li Han, Masters, Stanford CS
• Tyler Angert, Masters, Harvard GSE
• Yuyu Lin, Masters, Stanford CS
• Hansol Lee, PhD, Stanford GSE
• Steven Moore, Technical University Munich

Tools for Thought: Research and Design for Understanding, Protecting, and Augmenting Human Cognition with Generative AI [CHI 2025]
with Lev Tanklevitch, Jessica He, Aniket Kittur, Srishti Palani, Gonzalo Ramos, Elena L. Glassman, Majeed Kazemitabaar, Mina Lee, Advait Sarkar, and Yvonne Rogers
Workshop Website

Human–AI Coevolution [ICLR 2025]
with Jacy Anthis, Dylan M. Asmar, Katherine Driggs-Campbell, Amelia Hardy, Kiana Jafari, Geoff Keeling, Mykel J. Kochenderfer, Houjun Liu, Shuijing Liu, Roberto Martín-Martín, Ahmad Rushdi, Marc Schlichting, Peter Stone, and Diyi Yang
PDF

Dynamic Abstractions: Building the Next Generation of Cognitive Tools and Interfaces [UIST 2024]
with Sangho Suh, Hai Dang, Ryan Yen, Josh M. Pollock, Ian Arawjo, Rubaiat Habib Kazi, Jingyi Li, Nazmus Saquib, and Arvind Satyanarayan
Workshop Website

AI-Driven Support for People with Speech & Language Difficulties [CHI 2024]
with Aayushi Dangol, Yun Huang, Srirangaraj Setlur, Adele Smolansky, Hyewon Suh, Jinjun Xiong, and Julie A. Kientz
PDF

Designing for AI-Powered Social Computing Systems [CSCW 2023]
with Gionneve Lim, Hyunwoo Kim, Yoonseo Choi, Toby Jia-Jun Li, Chinmay Kulkarni, Joseph Seering, Michael S. Bernstein, Amy X. Zhang, Elena L. Glassman, Simon Perrault, and Juho Kim
PDF

LLMs and the Infrastructure of CSCW [CSCW 2023]
with Chinmay Kulkarni, Tongshuang Wu, Kenneth Holstein, Q. Vera Liao, Min Kyung Lee, and Mina Lee
PDF

Shortcomings of Visualizations for Human-in-the-Loop Machine Learning [Oct 9, 2023] 🔗
While visualizations can help developers better design, train, and understand their models, new research shows gaps between ambitions and evidence.

Spellburst: A Large Language Model-Powered Interactive Canvas for Generative Artists [Sept 13, 2023] 🔗
This new creativity support tool helps artists who work in code explore ideas using natural language and iterate with precision.

Finding a Fit with Learning Technology [Nov 22, 2022] 🔗
Hari Subramonyam and students investigate interfaces that optimize what humans and technology each do best.

New App VideoSticker Uses AI To Help Students Take Rich Notes from Video Lessons [Aug 25, 2022] 🔗
The tool allows students to break down video imagery and transcripts to ease and improve note-taking and comprehension.

In Human-Centered AI, the Boundaries Between UX and Software Roles Are Evolving [Apr 26, 2022] 🔗
"Leaky abstractions" are transforming software design and programming and leading to better, human-focused technology.