Rose E. Wang

PhD, Computer Science, Stanford University

rewang [AT] cs.stanford.edu

Bio

I am a PhD student at Stanford University's Computer Science Department, advised by Diyi Yang and Dora Demszky. I also collaborate closely with Susanna Loeb. I develop machine learning (ML) and natural language processing (NLP) methods for real-world domains, with a focus on Education as a critical domain with profound societal impact. I tackle challenges that arise in human-human and human-AI interactions.

I'm on the academic and industry job market 2024-25. If you think I could be a good fit for your organization, please reach out!

My work introduces algorithms, benchmarks and large-scale interventions for scaling expertise, i.e., building language models that capture expert reasoning. My research is deployed in industry and directly improves the education of under-served students through partnerships I've cultivated during my Ph.D. at Stanford, including Title I school districts and several education companies, impacting 200,000+ students, 1,700+ teachers, 16,100+ tutors, in millions of tutoring sessions across the U.S., UK and India. My work is recognized by a Best Paper Award at CogSci, Best Paper Award at NeurIPS Cooperative AI, Best Paper Award at BEA, ICLR Oral, NSF Graduate Research Fellowship, Rising Star in Data Science, and Tools Competition Award.

I did my undergrad at MIT (2020) with Profs. Josh Tenenbaum, Jonathan How, Google Brain and Google Brain Robotics on multiagent systems & reinforcement learning. During my PhD, I interned at the Allen Institute for AI (AI2). Growing up, I was raised in Finland and Germany, was a passionate multilinguist in German (Abitur), Chinese (HSK Level 6), French (DELF B2), Spanish (DELE B2) and received the European plurilingual excellence award.

Recent News

December 2024: Invited talk at UT Austin
December 2024: Invited talk at Cohere for AI
December 2024: Attending NeurIPS! Feel free to reach out to chat...or run together! (NeurIPS unofficial run club)
November 2024: ✨ Highlighted as a Leader in AI & Education by AI for Education.
November 2024: Two grants awarded by the Gates Foundation to continue work on (a) developing AI and Education benchmarks and (b) developing Language CoPilots.
November 2024: Two works at EMNLP 2024: Evaluating LLMs on real-world math curriculum (link) and on Problem-Oriented Segmentation and Retrievel (link).
November 2024: Invited talk at Princeton University
November 2024: Invited talk at MIT
November 2024: Invited talk at UC Berkeley, Graduate School of Education
November 2024: Invited talk at the Learning Agency
November 2024: Invited talk at TeachFX
November 2024: Invited talk at Worcester Polytechnic Institute
October 2024: Invited talk at Harvard University, Graduate School of Education
October 2024: Invited talk at University of Washington
October 2024: Invited talk at KAIST
October 2024: Want to build your own Tutor CoPilot? I released code, Colab notebook and tutorial video showing how to!
October 2024: Tutor CoPilot research primer video is released. Watch it here.
October 2024: Tutor CoPilot, the first large-scale intervention of Human-AI approach in live tutoring with 1,800 K12 students and 900 tutors is released. ✨👉 News coverage includes MIT Technology Review, Education Week, the 74, K-12 Dive, MarkTechPost, Dan Meyer's blog, Stanford Accelerator for Learning.
October 2024: Invited talk at University of Maryland
September 2024: Invited talk at University of Bocconi
September 2024: Talk at University of Chicago AI in Social Science Conference
September 2024: Talk at SREE Invited Symposium on Exploring the AI Frontier: Innovations in Social Science Research
September 2024: Talk at SREE Symposium on Artificial Intelligence and the Future of Educational Measurement and Evaluation
September 2024: Poster at SREE on Split or Share Attention in Small-Group Tutoring
July 2024: 🏆 Winner of the Learning Engineering Tools Competition
July 2024: Invited talk at the Learning Analytics Learning Network
July 2024: Invited talk at the National Tutoring Observatory
July 2024: 🏆 Ambassador (Best) Paper Talk at the Articial Intelligence and Education Conference (AIED)
July 2024: Invited Presentation at the Education Data Mining, LLM for EdTech Workshop
May 2024: Invited talk at the National Council on Measurement in Education: AI in Measurement and Education
May 2024: Invited talk at CU Boulder
May 2024: Invited talk at the National Student Support Accelerator conference
April 2024: Invited talk at UC Irvine

Publications

Please find all publications on my Google Scholar.

* denotes equal contributions.

Tutor CoPilot: A Human-AI Approach for Scaling Real-Time Expertise PDF Preregistration Video Code

Rose E. Wang, Ana Ribeiro, Carly Robinson, Dora Demszky, Susanna Loeb.

Society for Research on Educational Effectiveness (SREE 2024), UChicago Becker Friedman Institute AI for Social Science Conference 2024, American Economic Association (AEA 2024).

Featured in MIT Technology Review, Education Week, the 74, K-12 Dive, MarkTechPost, Dan Meyer's blog, Stanford Accelerator for Learning.

🌁 Bridging the Novice-Expert Gap via Models of Decision-Making PDF Poster Video Code

Rose E. Wang, Qingyang Zhang, Carly Robinson, Susanna Loeb, Dora Demszky

North American Chapter of the Association for Computational Linguistics (NAACL 2024)

Invited Presentation at the National Student Support Accelerator Conference (2024).

Featured in Stanford HAI and Dan Meyer's blog

Edu-ConvoKit: An Open-Source Library for Education Conversation Data PDF Poster Video Code

Rose E. Wang, Dora Demszky

North American Chapter of the Association for Computational Linguistics (NAACL 2024)

Invited Presentation at Education Data Mining (EDM 2024) LLM for EdTech Workshop, National Tutoring Observatory, Learning Analytics Learning Network

ScaffGen: Scaling High-Leverage Curriculum Scaffolding in Middle-School Mathematics PDF

Rizwaan Malik, Dorna Abdi, Rose E. Wang, Dora Demszky

Learning at Scale (L@S 2024); Under journal submission.

Winner of 2024 Tools Competition 🏆

Featured in The Learning Agency

Is ChatGPT a Good Teacher Coach? Measuring Zero-Shot Performance For Scoring and Providing Actionable Insights on Classroom Instruction PDF Video Code

Rose E. Wang, Dora Demszky

Innovative Use of NLP for Building Educational Applications (BEA 2023)

Ambassador (Best) Paper 🏆

Language modeling via stochastic processes PDF Video Code

Rose E. Wang, Esin Durmus, Noah Goodman, Tatsu Hashimoto

ICLR 2022

Oral Presentation (<1.6%)

Tutor CoPilot: A Human-AI Approach for Scaling Real-Time Expertise PDF Preregistration Video Code

Rose E. Wang, Ana Ribeiro, Carly Robinson, Dora Demszky, Susanna Loeb.

Society for Research on Educational Effectiveness (SREE 2024), UChicago Becker Friedman Institute AI for Social Science Conference 2024, American Economic Association (AEA 2024).

Featured in MIT Technology Review, Education Week, the 74, K-12 Dive, MarkTechPost, Dan Meyer's blog, Stanford Accelerator for Learning.

🌁 Bridging the Novice-Expert Gap via Models of Decision-Making PDF Poster Video Code

Rose E. Wang, Qingyang Zhang, Carly Robinson, Susanna Loeb, Dora Demszky

North American Chapter of the Association for Computational Linguistics (NAACL 2024)

Invited Presentation at the National Student Support Accelerator Conference (2024).

Featured in Stanford HAI and Dan Meyer's blog

Edu-ConvoKit: An Open-Source Library for Education Conversation Data PDF Poster Video Code

Rose E. Wang, Dora Demszky

North American Chapter of the Association for Computational Linguistics (NAACL 2024)

Invited Presentation at Education Data Mining (EDM 2024) LLM for EdTech Workshop, National Tutoring Observatory, Learning Analytics Learning Network

How Tutors Share or Split Attention Across Students in Small-Group Tutoring

Qingyang Zhang*, Rose E. Wang*, Ana Ribeiro, Susanna Loeb, Dora Demszky

SREE 2024.

ScaffGen: Scaling High-Leverage Curriculum Scaffolding in Middle-School Mathematics PDF

Rizwaan Malik, Dorna Abdi, Rose E. Wang, Dora Demszky

Learning at Scale (L@S 2024); Under journal submission.

Winner of 2024 Tools Competition 🏆

Featured in The Learning Agency

Backtracing: Retrieving the Cause of the Query PDF Poster Video Code

Rose E. Wang, Pawan Wirawarn, Omar Khattab, Noah Goodman, Dora Demszky

European Chapter of the Association for Computational Linguistics (EACL 2024) Long Paper Findings

Featured in Stanford HAI

Does Feedback on Talk Time Increase Student Engagement? Evidence from a Randomized Controlled Trial on a Math Tutoring Platform PDF

Dora Demszky, Rose E. Wang, Sean Geraghty, Carol Yu

Learning Analytics and Knowledge Conference (LAK '24)

Problem-Oriented Segmentation and Retrieval: Case Study on Tutoring Conversations PDF Video Code

Rose E. Wang, Pawan Wirawarn, Kenny Lam, Omar Khattab, Dora Demszky

Conference on Empirical Methods in Natural Language Processing (EMNLP 2024) Long Paper Findings.

Evaluating Language Model Math Reasoning via Grounding in Educational Curricula PDF Code

Li Lucy, Tal August, Rose E. Wang, Luca Soldaini, Courtney Allison, Kyle Lo

Conference on Empirical Methods in Natural Language Processing (EMNLP 2024) Long Paper Findings.

Is ChatGPT a Good Teacher Coach? Measuring Zero-Shot Performance For Scoring and Providing Actionable Insights on Classroom Instruction PDF Video Code

Rose E. Wang, Dora Demszky

Innovative Use of NLP for Building Educational Applications (BEA 2023)

Ambassador (Best) Paper 🏆

SIGHT: A Large Dataset on Student Insights Gathered from Higher Education Transcripts PDF Video Code

Rose E. Wang*, Pawan Wirawarn*, Noah Goodman, Dora Demszky

Innovative Use of NLP for Building Educational Applications (BEA 2023)

“Mistakes Help Us Grow”: Facilitating and Evaluating Growth Mindset Supportive Language in Classrooms PDF Code

Kunal Handa, Margaret Clapper, Jessica Boyle, Rose E. Wang, Diyi Yang, David Yeager, Dora Demszky.

Conference on Empirical Methods in Natural Language Processing (EMNLP 2023)

Featured in Stanford HAI

Language modeling via stochastic processes PDF Video Code

Rose E. Wang, Esin Durmus, Noah Goodman, Tatsu Hashimoto

ICLR 2022

Oral Presentation (<1.6%)

Calibrate your listeners! Robust communication-based training for pragmatic speakers PDF Video Code

Rose E. Wang, Julia White, Jesse Mu, Noah Goodman

Conference on Empirical Methods in Natural Language Processing (EMNLP 2023) Findings

ELIGN: Expectation Alignment as a Multi-Agent Intrinsic Reward PDF Code

Zixian Ma, Rose E. Wang, Fei-Fei Li, Michael Bernstein, Ranjay Krishna

Conference on Neural Information Processing Systems (NeurIPS 2022)

In the ZONE: Measuring difficulty and progression in curriculum generation PDF Video

Rose E. Wang, Jesse Mu, Dilip Arumugam, Natasha Jaques, Noah Goodman

NeurIPS 2022 Deep Reinforcement Learning Workshop

CLaP: Conditional Latent Planners for Offline Reinforcement Learning PDF

Harry Shin, Rose E. Wang

NeurIPS 2022 Workshop on Foundation Models for Decision Making

Speaking with confidence: Investigating the effects of uncertainty in pragmatic language learning Poster

Pawan Wirawarn, Rose E. Wang, Noah Goodman

Know Thy Student: Interactive Learning with Gaussian Processes PDF

Rose E. Wang, Mike Wu, Noah Goodman

ICLR 2022 Workshop on From Cells to Societies: Collective Learning across Scales

On the Opportunities and Risks of Foundation Models PDF

Center for Research on Foundation Models

Journal for Machine Learning Research (JMLR 2023)

Too many cooks: Bayesian inference for coordination multi-agent collaboration PDF Video Code

Rose E. Wang*, Sarah Wu*, Joshua Tenenbaum, James Evans, David Parkes, Max Kleiman-Weiner

Topics in Cognitive Science (2021); Human-Like Machine Intelligence (Oxford University Press)

Best Paper Award, CogSci 🏆; Best Paper Award, NeurIPS Cooperative AI Workshop 🏆

Model-based Reinforcement Learning for Multiagent Goal Alignment PDF Video

Rose E. Wang, Chase Kew, Dennis Lee, Tsang-Wei Edward Lee, Tingnan Zhang, Brian Ichter, Jie Tan, Aleksandra Faust.

Conference on Robotic Learning (CoRL 2020)

Featured in the Google AI Year in Review 2020. Check out our blog post too!

R-MADDPG for Partially Observable Environments and Limited Communication PDF Code

Rose E. Wang, Michael Everett, Jonathan P. How

International Conference on Machine Learning (ICML 2019) RL for Real Life Workshop

Acknowledgement

This website uses the website design and template by Martin Saveski