Jon Saad-Falcon
Jon Saad-Falcon
| jonsaadfalcon@stanford.edu | jonsaadfalcon.com | Google Scholar |
Scaling Intelligence Lab and Hazy Research, Stanford University
Education
Ph.D., Computer Science, Stanford University (2023 – present) Advisors: Christopher Re and Azalia Mirhoseini
M.B.A., Stanford Graduate School of Business (2023 – present)
B.S. – M.S., Computer Science, Georgia Institute of Technology (2018 – 2022) Advisor: Duen Horng (Polo) Chau Minors: Mathematics and Linguistics
Research Experience
2023 – present | PhD Researcher, Stanford University, Computer Science Areas: language models, ML systems, intelligence efficiency, inference-time techniques.
| 2026 – present | Google Student Researcher, Google – TPU and Gemini teams |
2023 | Research Intern, Databricks, Office of the CTO (San Francisco, CA) Research internship with Prof. Matei Zaharia. Built automated evaluation system for retrieval-augmented generation (RAG).
2022 – 2023 | Fulbright Scholar, Humboldt-Universitat zu Berlin (Germany) Research collaboration with Prof. Ulf Leser. Developed AI-powered techniques for patient treatment design using EHRs.
2021 – 2022 | Predoctoral Young Investigator, Allen Institute for Artificial Intelligence (AI2) – Semantic Scholar Mentors: Doug Downey and Daniel Weld. Designed efficiency techniques for caching and reusing sequence representations in language models.
2021 | Research Intern, Stanford University, Center for the Study of Language and Information (CSLI) Research internship with Prof. Christopher Potts and Prof. Matei Zaharia. NSF-funded REU; built the LoTTE benchmark and contributed to ColBERTv2.
2019 – 2022 | Undergraduate Research Assistant, Georgia Institute of Technology Advisors: Duen Horng (Polo) Chau and Diyi Yang. Projects in NLP, data visualization, and computational social science.
Awards & Honors
| 2025 | JP Morgan AI/ML Fellowship |
| 2023 | Stanford Graduate Fellowship |
| 2023 | Stanford EDGE Fellowship |
| 2023 | GEM PhD Fellowship, National GEM Consortium |
| 2023 | Knight-Hennessy Scholarship, Finalist, Stanford University |
| 2023 | Gates-Cambridge Scholarship, Bill & Melinda Gates Foundation |
| 2023 | College of Engineering Fellowship, University of California, Berkeley |
| 2022 | Fulbright Scholarship, Research Award, U.S. State Department and German Federal Foreign Office |
| 2022 | Summer Venture in Management Program (SVMP), Harvard Business School |
| 2021 | Donald V. Jackson Fellowship, Georgia Tech |
| 2021 | Computer Science Research Mentorship Program, Google |
| 2021 | U.N. Millennium Fellowship, United Nations |
| 2020 | D.E. Shaw Nexus Fellowship |
| 2020 | President’s Undergraduate Research Award, Georgia Tech |
| 2018 | Stamps President’s Scholarship, Georgia Tech |
Publications
Preprints
P1. Saad-Falcon, Jon et al. OpenJarvis: Personal AI, On Personal Devices. 2026. Blog: https://scalingintelligence.stanford.edu/blogs/openjarvis/ Code: https://github.com/open-jarvis/OpenJarvis
P2. Saad-Falcon, Jon, Narayan, A., Akengin, O., Griffin, W., Shandilya, H., Lafuente, A., Goel, M., Joseph, R., Natarajan, S., Guha, E., Zhu, S., Athiwaratkun, B., Hennessy, J., Mirhoseini, A. & Re, C. Intelligence per Watt: Measuring Intelligence Efficiency of Local AI. 2025. https://arxiv.org/abs/2511.07885
Peer-reviewed Conference Proceedings
C1. Saad-Falcon, Jon, Buchanan, E. K., Chen, M. F., Huang, T.-H., McLaughlin, B., Bhathal, T., Zhu, S., Athiwaratkun, B., Sala, F., Linderman, S., Mirhoseini, A. & Re, C. Weaver: Shrinking the Generation-Verification Gap with Weak Verifiers. NeurIPS 2025. https://arxiv.org/abs/2506.18203
C2. Saad-Falcon, Jon, Vivek, R., Berrios, W., Naik, N., Franklin, M., Vidgen, B., Singh, A., Kiela, D. & Mehri, S. LMUnit: Fine-grained Evaluation with Natural Language Unit Tests. EMNLP 2025. https://arxiv.org/abs/2412.13091
C3. Saad-Falcon, Jon, Lafuente Gamarra, A., Natarajan, S., Maru, N., Todorov, H., Guha, E., Buchanan, E. K., Chen, M., Guha, N., Re, C. & Mirhoseini, A. Archon: An Architecture Search Framework for Inference-Time Techniques. ICML 2025. https://arxiv.org/abs/2409.15254 Also: ICLR 2025, Scaling Self-Improving Foundation Models (SSI FM), Oral Presentation.
C4. Saad-Falcon, Jon, Fu, D. Y., Arora, S., Guha, N. & Re, C. Benchmarking and Building Long-Context Retrieval Models with LoCo and M2-BERT. ICML 2024. https://arxiv.org/abs/2402.07440
C5. Saad-Falcon, Jon, Barrow, J., Siu, A., Nenkova, A., Yoon, S., Rossi, R. A. & Dernoncourt, F. PDFTriage: Question Answering over Long, Structured Documents. EMNLP Industry 2024. https://aclanthology.org/2024.emnlp-industry.13.pdf
C6. Saad-Falcon, Jon, Khattab, O., Potts, C. & Zaharia, M. ARES: An Automated Evaluation Framework for Retrieval-Augmented Generation Systems. NAACL 2024, Oral Presentation. https://arxiv.org/abs/2311.09476
C7. Saad-Falcon, Jon, Khattab, O., Santhanam, K., Florian, R., Roukos, S., Sultan, M. A., Sil, A., Zaharia, M. & Potts, C. UDAPDR: Unsupervised Domain Adaptation via LLM Prompting and Distillation of Rerankers. EMNLP 2023.
C8. Saad-Falcon, Jon, Singh, A., Soldaini, L., D’Arcy, M., Cohan, A. & Downey, D. Embedding Recycling for Language Models. EACL 2023. https://arxiv.org/abs/2207.04993
C9. Santhanam*, K., Saad-Falcon*, Jon, Franz, M., Khattab, O., Sil, A., Florian, R., Sultan, M. A., Roukos, S., Zaharia, M. & Potts, C. Moving Beyond Downstream Task Accuracy for Information Retrieval Benchmarking. ACL Findings 2023.
C10. Lahav, D., Saad-Falcon, Jon, Kuehl, B., Johnson, S., Parasa, S., Shomron, N., Chau, D. H., Yang, D., Horvitz, E., Weld, D. S. & Hope, T. A Search Engine for Discovery of Scientific Challenges and Directions. AAAI 2022, Oral Presentation. https://arxiv.org/abs/2108.13751
C11. Santhanam*, K., Khattab*, O., Saad-Falcon, Jon, Potts, C. & Zaharia, M. ColBERTv2: Effective and Efficient Retrieval via Lightweight Late Interaction. NAACL 2022. https://arxiv.org/abs/2112.01488
C12. Li, K., Yang, H., Upadhayay, A., Zhou, Z., Saad-Falcon, Jon & Chau, D. H. Argo Scholar: Interactive Visual Exploration of Literature in Browsers. IEEE VIS 2021, Best Poster, Honorable Mention.
C13. Shaikh, O., Saad-Falcon, Jon, Wright, A. P., Das, N., Freitas, S., Asensio, O. I. & Chau, D. H. EnergyVis: Interactively Tracking and Exploring Energy Consumption for ML Models. CHI LBW 2021.
C14. Shaikh, O., Chen, J., Saad-Falcon, Jon, Chau, D. H. & Yang, D. Examining the Ordering of Rhetorical Strategies in Persuasive Requests. EMNLP Findings 2020.
C15. Saad-Falcon, Jon, Shaikh, O., Wang, Z. J., Wright, A. P., Richardson, S. & Chau, D. H. Mapping Researchers with PeopleMap. IEEE VIS 2020, Best Poster, Honorable Mention. https://arxiv.org/abs/2009.00091
Invited Talks
T1. Saad-Falcon, Jon. Intelligence per Watt: Measuring Intelligence Efficiency of Local AI. EE292P: Atoms, Bits, and National Interest (ABNI), Stanford University. Feb. 2026. T2. Saad-Falcon, Jon. Intelligence per Watt: Measuring Intelligence Efficiency of Local AI. Two Sigma. Jan. 2026. T3. Saad-Falcon, Jon. Intelligence per Watt: Measuring Intelligence Efficiency of Local AI. MBZUAI Speech and NLP Symposium. Jan. 2026. T4. Saad-Falcon, Jon. Weaver: Shrinking the Generation-Verification Gap with Weak Verifiers. Measuring Intelligence Summit at PyTorch Conference. Oct. 2025. T5. Saad-Falcon, Jon. Weaver: Shrinking the Generation-Verification Gap with Weak Verifiers. Together AI. Jul. 2025. T6. Saad-Falcon, Jon. Archon: An Architecture Search Framework for Inference-Time Techniques. LLMs Meet Data Processing Workshop, UC Berkeley. May 2025. T7. Saad-Falcon, Jon. Archon: An Architecture Search Framework for Inference-Time Techniques. Databricks. Feb. 2025. T8. Saad-Falcon, Jon. Archon: An Architecture Search Framework for Inference-Time Techniques. Contextual AI. Oct. 2024.
Mentorship
Current Mentees
| 2024 – present | Hangoo Kang, Hannah Gao, Harsh Singh, Matthew Hart, Orhun Akengin, Tanvir Bhathal, Tarun Suresh |
Past Mentees
Adrian Lafuente Gamarra (now Salesforce), Brendan McLaughlin (now Reflection AI), Herumb Shandilya (now Mixed Bread), Robby Manihani (now Pace), Wes Griffin (Stanford)
Teaching
| Autumn 2025 | Teaching Assistant, CS 224V: Conversational Virtual Assistants with Deep Learning, Stanford University |
| Winter 2025 | Teaching Assistant, CS329A: Self-Improving Agents, Stanford University |
Service & Community
Academic Service
| 2025 | Reviewer, NeurIPS 2025 |
| 2024 | Reviewer, EMNLP 2024 |
| 2024 | Reviewer, ICML 2024 |
| 2022 | Reviewer, NAACL 2022 |
| 2020 | Reviewer, EMNLP 2020 |
| 2020 | Reviewer, ACL 2020 |
Leadership & Community Engagement
2025 – present | SoE Dean’s Graduate Student Advisory Council (DGSAC), Chair for Computer Science, Stanford University Built first centralized database of fellowships, RA/CA, and internship opportunities across 9 departments with SoE leadership. Connected 30+ students with fellowships, 50+ with internships, and 40+ with RA placements in 2025-26.
2021 – 2022 | Georgia Tech Venture Capital Fund, Co-founder and Student Director Collaborated with Georgia Tech president’s office and alumni association to establish first GT-backed VC fund. Created educational curriculum for teaching 40+ students. Raised an inaugural $10+ million early-stage fund.
2020 – 2022 | Georgia Tech Computer Science Outreach Club, Founding Member and Volunteer Developed coding workshops and lectures to teach 50+ underprivileged youth from Atlanta-area high schools.
Other Experience
2020 | Research Analyst, Goldman Sachs, Global Investment Research (New York City, NY) Used quantitative techniques and NLP tools for company valuation. Collaborated with traders and external clients.
Last updated: April 2026