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 sits at the intersection of Human-Computer Interaction (HCI) and the Learning Sciences. I study ways to augment human learning using AI by (1) engaging in cognitively informed design practices, (2) co-designing with learners and educators, and (3) developing transformative AI-enabled learning experiences. Through my research, I also contribute tools and methodologies that prioritize ethical considerations, responsible design practices, and human values when creating AI experiences. I received my PhD in Information at the University of Michigan, advised by Eytan Adar.
harihars [at] stanford [dot] edu 
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@HariSubramonyam
hari subramonyamI will be at CHI 2025 in Yokohama, Japan where we will be presenting 4 papers.
I will be visiting the National University of Singapore to share work in AI and education, as well human-centered generative AI.
I am co-organizing a workshop on Tools for Thought 🔗 at CHI 2025.
🏆 We received a Best Paper Award at CHI for our work on geneative AI prototyping [Tweet 🔗 ].
🥇 We received an Honorable Mention Award at CHI for our work on LLM augmented writing using a layered interface paradigm [Tweet 🔗 ].
Cover Story in Interactions Magazine Volume 31, Issue 4 "UX Matters: The Critical Role of UX in Responsible AI 🔗 "
We received a HAI Hoffman Yee Grant 🔗 to investigate Integrating Intelligence: Building Shared Conceptual Grounding for Interacting with Generative AI (PI Agrawala).
"Bridging Concept and Computation: Interactive Abstractions for Generative AI Systems" at University of Michigan 🔗
"Rethinking the AI-UX Boundary for Designing Human-AI Experiences." at BayCHI 🔗 .
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.
- Neha Rajagopalan [co-advised with Bruce McCandliss]
Other Student Researchers:
- Nidhi Parthasarathy, Lynbrook High School
- Anika Rajaram, Harker High School
- Zoe Kaputa, MS, Stanford CS
- Priyanshi Sharma, Stanford GSE
- 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
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 sits at the intersection of Human-Computer Interaction (HCI) and the Learning Sciences. I study ways to augment human learning using AI by (1) engaging in cognitively informed design practices, (2) co-designing with learners and educators, and (3) developing transformative AI-enabled learning experiences. Through my research, I also contribute tools and methodologies that prioritize ethical considerations, responsible design practices, and human values when creating AI experiences. I received my PhD in Information at the University of Michigan, advised by Eytan Adar.
PDF | VIDEO | Project Website
Tools for Thought: Research and Design for Understanding, Protecting, and Augmenting Human Cognition with Generative AI [CHI 2025]
Workshop Website
Human–AI Coevolution [ICLR 2025]
PDF
Dynamic Abstractions: Building the Next Generation of Cognitive Tools and Interfaces [UIST 2024]
Workshop Website
AI-Driven Support for People with Speech & Language Difficulties [CHI 2024]
PDF
Designing for AI-Powered Social Computing Systems [CSCW 2023]
PDF
LLMs and the Infrastructure of CSCW [CSCW 2023]
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.