Companies
Stanford University
Product category: Not a vendor 99% confident
Org type: University / research 100% confident
Also listed as 13 other names
Stanford · Stanford / SLAC National Laboratory · Stanford AI Lab · Stanford ICME · Stanford University / Bigspin · Stanford University / Databricks · Stanford University / NVIDIA · Stanford University / Together AI · Stanford University Libraries · Stanford University Research Computing Center · Stanford University | Apple · Stanford University, ICME · Stanford; Google
Conferences sponsored2
Events sponsored2
Speaker slots10978 distinct people
Conferences present at39sponsor or speaker
Years active2019–2027
Circuit mix
Where Stanford University shows up, by circuit. Each event counts once: 2 if it sponsored, 1 if it only had speakers. Hover a segment for the conference.
- Research39%31 events
- AI engineering & MLOps19%14 events
- Vendor flagships & roadshows11%9 events
- Python & R data science11%9 events
- Modern data stack & practitioner10%7 events
- Geospatial & mapping5%4 events
- Streaming1%1 event
- Cloud providers1%1 event
- Software engineering1%1 event
The year around now
Conferences where Stanford University sponsored or had speakers in the past 12 months, and the announced events it is already listed for. One row per conference, January to December; hover a mark for the event and the company's role.
Presence by conference and year
Each cell is one conference in one year. Fill shows the company sponsored, shaded by its best tier that year; a dot means it had speakers there. Hover for details; click to open the event.
- Title
- Platinum
- Gold
- Silver
- Bronze
- Other / unlabeled tier
- Had speakers
Activity by year
Three measures on one year axis; each panel has its own scale.
Conferences present at
Distinct conferences each year, split by whether the company sponsored or only had speakers there.
- Sponsored
- Speakers only
10
5
3
6
12
13
14
10
Distinct speakers
People from this company on a program that year, each counted once.
14
6
4
8
17
16
14
14
Sponsorships by tier
Sponsorship rows per year (one per event and listing), stacked by normalized tier.
- Other / unlabeled
1
1
Where they've grown or pulled back
DownNothing recorded in 2026; sponsored 1 conference in 2020.
Counted per conference. 2026 is the latest year whose conferences have mostly happened. Tiers use the best tier each year; swatches show the path, oldest first. A conference counts as pulled out only when a later event published a complete sponsor list, since most events don’t say whether their list is complete.
Once or on and off 2
No clear direction, or a gap we can’t confirm because later sponsor lists are incomplete.
- ScaledML (Scaled Machine Learning Conference)once, 2019, unranked tier
- Women in Data Science (WiDS) Conferenceonce, 2020, tier not listed
Lookalikes
Companies with the most similar conference footprint: they sponsor and speak at the same conferences. Bars are cosine similarity, from 0 (nothing shared) to 1 (identical).
- University of Washington0.85
- Meta0.82
- UC Berkeley0.79
- University of California, Berkeley0.77
- Harvard University0.75
- Massachusetts Institute of Technology0.75
- Carnegie Mellon University0.70
- Two Sigma0.70
0 Cluster: NeurIPS · ICML circuit →
Often sponsors alongside
Companies that sponsored the same events, by number of shared events (out of 2 this company sponsored).
| Company | Shared events | Share |
|---|---|---|
| 2 | 100% | |
| Apple | 1 | 50% |
| Dell Technologies | 1 | 50% |
| General Motors | 1 | 50% |
| Graphcore | 1 | 50% |
| HP | 1 | 50% |
| IBM | 1 | 50% |
| Intel | 1 | 50% |
| Intuit | 1 | 50% |
| MathWorks | 1 | 50% |
| Matroid | 1 | 50% |
| Meta | 1 | 50% |
| Microsoft | 1 | 50% |
| Quora | 1 | 50% |
| Samsung Electronics | 1 | 50% |
Neighborhood: companies with nearby conference footprints
Stanford University (ringed) and the 30 companies closest to it on the company map. Close together means they sponsor and speak at many of the same conferences. Distances are only meaningful locally; the axes have no meaning. Dot size: conferences present at. Color: cluster.
Sponsorships 2
| Event | Date | Place | Tier as listed | Normalized tier |
|---|---|---|---|---|
| WiDS Stanford Conference 2020 | Mar 2, 2020 | Stanford, United States | — | Unlabeled |
| ScaledML 2019 | Mar 27–28, 2019 | Mountain View, United States | Sponsor | Other |
Speakers 109
| Speaker | Event | Role | Talk | Links |
|---|---|---|---|---|
| Liana Patel | CIDR 2027 | paper | What Happens When the Model Eats the Stack? Rethinking the Research Agenda for Data Agents | — |
| Quito Tsui | SatSummit St. Louis 2026 | panelist | Can I Get a Witness? | — |
| Christopher G. Potts | 7th Annual MLOps World | GenAI Summit 2026 | speaker (virtual day) | — | — |
| Yegor Denisov-Blanch | 7th Annual MLOps World | GenAI Summit 2026 | speaker (virtual day) | — | — |
| Maty Bohacek | AI Engineer New York 2026 | speaker | The Human Verification Bottleneck: What agents do when a human is the only thing in the way | — |
| Shaghayegh Moradirad | Data Streaming Summit 2026: The Data+Agent Conference | speaker | MCP Is Not Free Context | Video |
| Balasubramanian Narasimhan | useR! 2026 | speaker | Metamorphoses: Transforming CVXR to S7 with an AI Agent | — |
| Balasubramanian Narasimhan | useR! 2026 | workshop | Convex Optimization in R Using CVXR | — |
| Susan Athey | ICML 2026 | keynote | Causal Inference with Transformer Models | — |
| James Zou | AI Engineer World's Fair 2026 | speaker | Harnessing Collective Agent Intelligence for Open Science | Video |
| John Ousterhout | AI Engineer World's Fair 2026 | keynote | TCP and RDMA are Killing Inference Throughput; Homa can Fix It | — |
| Simran Arora | AI Engineer World's Fair 2026 | speaker | Can LLMs write fast multi-GPU kernels? We built a benchmark to find out. | Video |
| Doug Berman | Data Citizens on the Road 2026: San Francisco | panelist | From friction to flow: Navigating the real challenges of AI | — |
| Percy Liang | ICLR 2026 | keynote | Marin: Open Development of Frontier AI | — |
| Le Cong | GTC 2026 | featured | — | — |
| Percy Liang | GTC 2026 | featured | — | — |
| Edward Feigenbaum | AAAI-26 (40th AAAI Conference on Artificial Intelligence) | keynote | 1956 to 2026: Highlights (and Advice) from 70 Years of Navigating the AI Spectrum | — |
| Yejin Choi | NeurIPS 2025 (San Diego) | keynote | The Art of (Artificial) Reasoning | Video |
| Yegor Denisov-Blanch | AI Engineer Code Summit 2025 | speaker | How to Quantify AI ROI in Software Engineering (Stanford Study / 120k Devs) | Video |
| Peter Norvig | AI By the Bay 2025 | keynote | The present and future of programming with AI | Video |
| Selene Yang Rappaccioli | FOSS4G 2025 | keynote | We don't build tech, but we build communities. | — |
| David Donoho | JupyterCon 2025 | keynote | Keynote: Nobel Prizes for Data Science | — |
| David Hall | Ray Summit 2025 | featured | — | — |
| Percy Liang | PyTorch Conference 2025 | keynote | Keynote: Marin: An Open Lab for Frontier AI | — |
| Yegor Denisov-Blanch | 6th Annual MLOps World | GenAI Summit 2025 | speaker | Impact of AI on Developer Productivity | — |
| Angela Tsao | 2025 Geo for Good Summit NYC | speaker | Effective use of Google's Satellite Embedding dataset | — |
| Liza Goldberg | 2025 Geo for Good Summit NYC | speaker | Beyond the Basemap: Empowering Users in a Geospatial World | — |
| Malcolm Barrett | useR! 2025 | workshop | Causal Machine Learning in R | — |
| Christopher Manning | KDD 2025 (31st ACM SIGKDD Conference) | keynote | Meaning and Intelligence in Language Models: From History and Philosophy to Universal Transformers and Web Agents | — |
| Robert Tibshirani | JSM 2025 (Joint Statistical Meetings) | named lecture | — | — |
| Filippo Balzaretti | SciPy 2025 | speaker | Can Scientific Python Tools Unlock the Secrets of Materials? The Electrons That Machine-Learning Can't Handle | — |
| Yegor Denisov-Blanch | AI Engineer World's Fair 2025 | speaker | Does AI Actually Boost Developer Productivity? (Stanford / 100k Devs Study) | Video |
| Christos Kozyrakis | CIDR 2025 | keynote | The State of Hardware | — |
| Fei-Fei Li | NeurIPS 2024 | keynote | From Seeing to Doing: Ascending the Ladder of Visual Intelligence | Video |
| Kim Durante | FOSS4G 2024 | speaker | FAIR Principles for Geospatial Data Curation | — |
| Percy Liang | EMNLP 2024 | keynote | Open-Source and Science in the Era of Foundation Models | — |
| Malcolm Barrett | posit::conf(2024) | workshop | Causal Inference in R | — |
| Mika Braginsky | posit::conf(2024) | lightning | DataPages for interactive data sharing using Quarto | Video |
| Robert Tibshirani | JSM 2024 (Joint Statistical Meetings) | named lecture | Pre-Training and the Lasso | — |
| Chelsea Finn | ICML 2024 | keynote | "What robots have taught me about machine learning" | — |
| Fei-Fei Li | CVPR 2024 | panelist | Societal opportunities and challenges of AI | — |
| Fei-Fei Li | Data + AI Summit 2024 | featured | — | — |
| Christos Kozyrakis | ICDE 2024 (40th IEEE International Conference on Data Engineering) | keynote | AI Systems beyond Accelerating Linear Algebra | — |
| Douglas Berman | Data Citizens '24: The Data Intelligence Conference | speaker | — | — |
| Fei-Fei Li | GTC 2024 | featured | — | — |
| Percy Liang | GTC 2024 | featured | — | — |
| Ashley Raigosa | WiDS Stanford Conference 2024 | panelist | Space Panel | Video |
| Ashley Raigosa | WiDS Stanford Conference 2024 | speaker | Traversing the Data Desert: Pioneering Low-Cost CubeSats | Video |
| Aya Mouallem | WiDS Stanford Conference 2024 | speaker | — | — |
| Jenny Martinez | WiDS Stanford Conference 2024 | keynote | Opening Address | Video |
| Kimberly Babiarz | WiDS Stanford Conference 2024 | panelist | Child Safety and Health Panel | Video |
| Kimberly Babiarz | WiDS Stanford Conference 2024 | speaker | Bringing AI-Driven Technologies to the Fight Against Human Trafficking in Brazil | Video |
| Laura Bravo Sánchez | WiDS Stanford Conference 2024 | speaker | How Can Computer Vision Guide the Understanding of Parent-Child Interactions? | Video |
| Laura Bravo Sánchez | WiDS Stanford Conference 2024 | panelist | Child Safety and Health Panel | Video |
| Manisha Desai | WiDS Stanford Conference 2024 | keynote | Keynote: Can Data Science and AI Deliver on its Promise for Improving Public Health? | Video |
| Ziheng Wang | CIDR 2024 | paper | A Model for Query Execution Over Heterogeneous Instances | Paper |
| Christopher Ré | NeurIPS 2023 | keynote | Systems for Foundation Models, and Foundation Models for Systems. | Video |
| Percy Liang | NeurIPS 2023 | panelist | Beyond Scaling Panel | Video |
| Christopher D. Manning | EMNLP 2023 | keynote | Academic NLP research in the Age of LLMs: Nothing but blue skies! | — |
| Amir Bahmani | AWS re:Invent 2023 | breakout | Building a precision medicine platform using AWS HealthOmics | Video |
| Mike Snyder | AWS re:Invent 2023 | breakout | Building a precision medicine platform using AWS HealthOmics | Video |
| Chelsea Finn | ODSC West 2023 | keynote | — | — |
| Tony Wang | Ray Summit 2023 | speaker | Building a distributed query engine with Ray | — |
| Wing-Hung Wong | JSM 2023 (Joint Statistical Meetings) | named lecture | Causal Inference by Encoding Generative Modeling | — |
| Eric Sager Luxenberg | SciPy 2023 | tutorial | Controlling Self-Landing Rockets Using CVXPY | — |
| Eric Sager Luxenberg | SciPy 2023 | speaker | Disciplined Saddle Programming | — |
| Jacob Schreiber | SciPy 2023 | speaker | tfmodisco-lite: an attribution-based motif discovery algorithm | — |
| Jure Leskovec | SIGMOD/PODS 2023 | PODS keynote | Databases as Graphs: Predictive Queries for Declarative Machine Learning | — |
| Matei Zaharia | MLSys 2023 | keynote | Improving the Quality and Factuality of Large Language Model Applications | — |
| Keith Winstein | QCon London 2023 | speaker | What We Talk About When We Talk About Networks | — |
| Carolyn Bertozzi | WiDS Stanford Conference 2023 | speaker | — | — |
| Jennifer Pan | WiDS Stanford Conference 2023 | speaker | Uncovering Online Censorship and Propaganda in China | Video |
| Jennifer Pan | WiDS Stanford Conference 2023 | speaker | Putting our values into practice in data science | Video |
| Sanne Smith | WiDS Stanford Conference 2023 | speaker | Preparing for a career in DS | Video |
| Qian Li | CIDR 2023 | paper | Transactions Make Debugging Easy | Slides · Video · Paper |
| Monica S. Lam | ODSC West 2022 | keynote | — | — |
| Kunle Olukotun | MLSys 2022 | keynote | Systems for ML and ML for Systems: A Virtuous Cycle | — |
| Guido Imbens | ICML 2022 | keynote | Synthetic Control Methods and Difference-In-Differences | — |
| Christopher Manning | Data + AI Summit 2022 | featured | — | — |
| Chris Ré | SIGMOD/PODS 2022 | keynote | Is Data Management the Beating Heart of AI Systems? | — |
| Daniel Kang | CIDR 2022 | paper | VIVA: An End-to-End System for Interactive Video Analytics | Video · Paper |
| Laurel Orr | CIDR 2022 | paper | Data Management Opportunities for Foundation Models | Video · Paper |
| Qian Li | CIDR 2022 | paper | A Progress Report on DBOS: A Database-oriented Operating System | Video · Paper |
| Carlos Guestrin | ODSC West 2021 | keynote | — | — |
| Jeffrey Ullman | KDD 2021 (virtual, Singapore) | keynote | On the Nature of Data Science | — |
| Fiodar Kazhamiaka | CIDR 2021 | paper | Challenges and Opportunities for Autonomous Vehicle Query Systems | Video · Paper |
| Laurel Orr | CIDR 2021 | paper | Bootleg: Chasing the Tail with Self-Supervised Named Entity Disambiguation | Video · Paper |
| Vanessa Sochat | Airflow Summit 2020 | talk | Adding an executor to Airflow: A contributor overflow exception | Video |
| Christopher Ré | MLSys 2020 | keynote | Theory and Systems for Weak Supervision | — |
| Karen Matthys | WiDS Stanford Conference 2020 | speaker | — | — |
| Lucy Bernholz | WiDS Stanford Conference 2020 | speaker | — | — |
| Susan Athey | AAAI-20 (34th AAAI Conference on Artificial Intelligence) | keynote | The Economic Value of Data for Targeted Pricing | — |
| Jayesh Ahire | Redis Day Bangalore 2020 | speaker | Building a Deep Learning Application using TensorFlow 2.0 & Redis | — |
| Evan Patterson | PyData New York City 2019 | speaker | Semantic modeling of data science code | Video |
| Rajesh Golani | PyData Delhi 2019 | talk | Building interactive data visualisations with Altair & Django | — |
| Trevor J. Hastie | JSM 2019 (Joint Statistical Meetings) | named lecture | Wald II: Statistical Learning with Sparsity | — |
| Trevor J. Hastie | JSM 2019 (Joint Statistical Meetings) | named lecture | Wald III: Statistical Learning with Sparsity | — |
| Trevor J. Hastie | JSM 2019 (Joint Statistical Meetings) | named lecture | Wald I: Statistical Learning with Sparsity | — |
| Brian Jackson | JuliaCon 2019 | lightning | TrajectoryOptimization.jl: A testbed for optimization-based robotic motion planning | — |
| Ludovic Räss | JuliaCon 2019 | speaker | Porting a massively parallel Multi-GPU application to Julia: a 3-D nonlinear multi-physics flow solver | — |
| Timnit Gebru | Spark + AI Summit 2019 | keynote | — | — |
| Alex Ratner | Data Council San Francisco 2019 | talk | Accelerating Machine Learning with Training Data Management | — |
| Chris Re | O'Reilly Artificial Intelligence Conference New York 2019 | keynote | Software 2.0 & Snorkel | — |
| Daniel Rubin | GTC 2019 | featured | Frontiers of AI in Medicine: Overcoming Current Challenges and Moving Beyond Classification | — |
| Emma Brunskill | WiDS Stanford Conference 2019 | speaker | Better Reinforcement Learning for Human in the Loop Systems | Video |
| Jennifer Widom | WiDS Stanford Conference 2019 | keynote | Opening Address | Video |
| Karen Matthys | WiDS Stanford Conference 2019 | speaker | — | — |
| Alexander J Ratner | CIDR 2019 | paper | The Role of Massively Multi-Task and Weak Supervision in Software 2.0 | Paper |
| Daniel Kang | CIDR 2019 | paper | Challenges and Opportunities in DNN-Based Video Analytics: A Demonstration of the BlazeIt Video Query Engine | Paper |