Sherry Ruan â–®

Hi there! 👋

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Hi, I’m Sherry — founder of ComputerX.ai, a StartX-backed AI agent startup automating knowledge work through multimodal agents. We’ve helped users automate hundreds of thousands of workflows across tasks that were previously manual and repetitive.

Previously, I earned my Ph.D. in Computer Science from Stanford University, where I worked on sequence modeling, chatbot and agent systems, human-AI interaction, and reinforcement learning for education with Professors James Landay and Emma Brunskill, in close collaboration with the Stanford Human-Centered AI Institute. I’ve also conducted research at Google Cloud AI under Dr. Wei Wei on variational autoencoders, and at Baidu’s Silicon Valley AI Lab on deep learning–based speech recognition systems under Chief Scientist Andrew Ng. I’ve also advised enterprise clients on AI and ML strategy and deployment as a consultant at BCG, and was selected as an Accel Innovation Scholar.

During my undergraduate studies at McGill University, I worked with Professor Prakash Panangaden and Dr. Gheorghe Comanici on bisimulation metrics for representation discovery in reinforcement learning. I also briefly worked on programming languages, and my undergraduate research received First Place at the ACM SIGPLAN International Conference on Functional Programming (ICFP) Student Research Competition.

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Highlights


Education

Ph.D. in Computer Science, Stanford University – GPA 4.09/4.00
M.S. in Computer Science, Stanford University – GPA 4.09/4.00
B.Sc., Joint Honors in Mathematics and Computer Science, McGill University – GPA 3.99/4.00


Selected Publications

LLMs & Agent Systems

Learning What to Learn: Curriculum Curation for Test-Time Agent Learning
Q. Zhang*, S. Ruan*, S. Upasani, F. Hong, C. Ji, C. Hu, B. Li, H. Li, K. Olukotun
ICLR Workshop on Lifelong Agents: Learning, Aligning, Evolving, 2026
Paper · Code

MCP Explorer: Interactive Learning Experience
J. He*, S. Ruan*, J. A. Landay
Neural Information Processing Systems (NeurIPS) AI Education Resource Showcase, 2025
Demo · Code · Oral Presentation

JungleGPT: Designing and Optimizing Compound AI Systems for E-Commerce
S. Ruan, T. Zhao
Compound AI Systems, 2024
Paper

Representation Learning & Reinforcement Learning

Reinforcement Learning Tutor Better Supported Lower Performers in a Math Task
S. Ruan*, A. Nie*, W. Steenbergen, J. He, J. Zhang, M. Guo, Y. Liu, K. D. Nguyen, C. Y. Wang, R. Ying, J. A. Landay, E. Brunskill
Machine Learning, Volume 113, Issue 5, pp. 3023–3048, 2024
Paper · Code

Variational Deep Knowledge Tracing for Language Learning
S. Ruan, W. Wei, J. A. Landay
International Learning Analytics and Knowledge Conference, 2021
Paper

Adaptive Natural-Language Targeting for Student Feedback
Y. A. Kolchinski*, S. Ruan*, D. Schwartz, E. Brunskill
Proceedings of the Annual ACM Conference on Learning at Scale, 2018
Paper

Representation Discovery for MDPs Using Bisimulation Metrics
S. Ruan, G. Comanici, P. Panangaden, D. Precup
Proceedings of the AAAI Conference on Artificial Intelligence, 2015
Paper · Code

Interactive AI Systems

EnglishBot: An AI-Powered Conversational System for Second Language Learning
S. Ruan*, L. Jiang*, Q. Xu*, Z. Liu, G. M. Davis, E. Brunskill, J. A. Landay
Proceedings of the International Conference on Intelligent User Interfaces, 2021
Paper · Video

BookBuddy: Turning Digital Materials into Interactive Foreign Language Lessons Through a Voice Chatbot
S. Ruan, A. Willis, Q. Xu, G. M. Davis, L. Jiang, E. Brunskill, J. A. Landay
Proceedings of the Annual ACM Conference on Learning at Scale, 2019
Paper

QuizBot: A Dialogue-Based Adaptive Learning System for Factual Knowledge
S. Ruan, L. Jiang, J. Xu, B. J.-K. Tham, Z. Qiu, Y. Zhu, E. L. Murnane, E. Brunskill, J. A. Landay
Proceedings of the CHI Conference on Human Factors in Computing Systems, 2019
Paper · Code · Video · Stanford AI Lab Blog · World Economic Forum

Human-AI Interaction

Supporting Children’s Math Learning with Feedback-Augmented Narrative Technology
S. Ruan, J. He, R. Ying, J. Burkle, D. Hakim, A. Wang, Y. Yin, L. Zhou, Q. Xu, A. AbuHashem, G. Dietz, E. L. Murnane, E. Brunskill, J. A. Landay
Proceedings of the Interaction Design and Children Conference, 2020
Paper · Video

Speech Is 3x Faster than Typing for English and Mandarin Text Entry on Mobile Devices
S. Ruan, J. O. Wobbrock, K. Liou, A. Ng, J. A. Landay
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 2018
Paper · Video · Project Page · NPR · VentureBeat

* Indicates equal contribution. For a complete list of publications, see my Google Scholar profile.


Teaching

CS 230: Deep Learning
Teaching Assistant, Stanford University
Instructor: Prof. Andrew Ng and Kian Katanforoosh
Winter 2021, Winter 2020


Academic Service

Conference Reviewer: NeurIPS, ICLR, CHI
Student Volunteer: NeurIPS, CHI, UAI
Research Mentor: Stanford CURIS, Stanford UGVR, Stanford CSLI


Selected Awards and Honors

Accel Innovation Scholar, Stanford University & Accel Partners
HAI Seed Grant Recipient, Stanford Human-Centered AI Institute
School of Engineering Fellowship, Stanford University
ACM SIGPLAN ICFP Student Research Competition First Place, ACM
CRA-W CREU Award, Canadian Computing Research Association
Edward Rosenthall Memorial Prize in Mathematics, McGill University
Sir Edward Beatty Memorial Scholarship in Mathematics, McGill University
William Moser Prize in Mathematics, McGill University
James McGill Scholarship, McGill University
Gold Medal, 9th China Girls’ Mathematical Olympiad (CGMO)


Miscellaneous

My interests outside of research span entrepreneurship, community leadership, and volunteer work. I received an Ignite Certificate in Innovation & Entrepreneurship from the Stanford Graduate School of Business and have passed CFA Level I through the CFA Institute.

I was a founding team member of the Stanford PhD Pathways Conference and served as Graduate Community Co-Chair for Stanford Women in Computer Science. I’ve also contributed as a website UX/UI volunteer for ACM SIGCHI.