Companies
UC Berkeley
Product category (jev): Not a vendor 99% confident
Org type (jev): University / research 100% confident
Also listed as: UC Berkeley (BAIR) · UC Berkeley / Ambidextrous Robotics · UC Berkeley / Google DeepMind · UC Berkeley / Opaque Systems · UC Berkeley / Physical Intelligence · UC Berkeley / covariant.ai · UC Berkeley Electrical Engineering & Computer Sciences · UC Berkeley RISELab · UC Berkeley Sky Computing Lab · UC Berkeley; UC Berkeley Center for Responsible Decentralized Intelligence
Conferences sponsored2
Events sponsored2
Speaker slots8150 distinct people
Conferences present at26sponsor or speaker
Years active2019–2026
Circuit mix
Where UC Berkeley shows up, by circuit. Each event counts once: 2 if it sponsored, 1 if it only had speakers. Hover a segment for the conference.
- AI engineering & MLOps47%24 events
- Research21%11 events
- Python & R data science11%6 events
- Vendor flagships & roadshows8%3 events
- Modern data stack & practitioner6%3 events
- Software engineering & trading tech4%2 events
- Open-source data infrastructure2%1 event
- Cloud providers2%1 event
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. 2027, 2028 is still mostly ahead, so its bars are faded and incomplete.
Conferences present at
Distinct conferences each year, split by whether the company sponsored or only had speakers there.
- Sponsored
- Speakers only
9
5
4
6
6
5
4
6
Distinct speakers
People from this company on a program that year, each counted once.
12
8
3
11
10
5
15
7
Sponsorships by tier
Sponsorship rows per year (one per event and listing), stacked by normalized tier.
- Silver
- Other / unlabeled
1
1
Where they've grown or pulled back
FlatSponsored 1 conference in 2026, flat from 1 in 2019.
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.
New 1
First sponsored in 2025 or later.
- AI Engineer (World's Fair, Summit and regional editions)first sponsored 2026, unranked tier
Once or on and off 1
No clear direction, or a gap we can’t confirm because later sponsor lists are incomplete.
- Data + AI Summitonce, 2019, Silver
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).
- Stanford University0.79
- Runpod0.71
- Meta0.70
- FriendliAI0.67
- Two Sigma0.66
- LlamaIndex0.65
- Coatue0.62
- Together AI0.62
2 Cluster: CIDR · ACM SIGMOD/PODS 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 |
|---|---|---|
| Amazon Web Services | 2 | 100% |
| Bloomberg | 2 | 100% |
| 2 | 100% | |
| Microsoft | 2 | 100% |
| Neo4j | 2 | 100% |
| NVIDIA | 2 | 100% |
| Two Sigma | 2 | 100% |
| 1Password | 1 | 50% |
| Accenture | 1 | 50% |
| Acrew Capital | 1 | 50% |
| Adobe | 1 | 50% |
| Agentfield | 1 | 50% |
| AgentMail | 1 | 50% |
| AIDAChip | 1 | 50% |
| Aikido | 1 | 50% |
Neighborhood: companies with nearby conference footprints
UC Berkeley (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 |
|---|---|---|---|---|
| AI Engineer World's Fair 2026 | Jun 29, 2026 – Jul 2, 2026 | San Francisco, United States | Supporting Partners | Other |
| Spark + AI Summit 2019 | Apr 23–25, 2019 | San Francisco, United States | Silver | Silver |
Speakers 81
| Speaker | Event | Role | Talk | Links |
|---|---|---|---|---|
| Fernando Pérez | Compute! Paris 2026 | keynote | Jupyter, open source and AI: science and humans? | — |
| Frank Coyle | AI Engineer Code Summit 2026 | speaker | From Shared Language to Enforceable Contracts: Ontologies as Guardrails for Agents. | — |
| Dawn Song | AGNTCon + MCPCon North America 2026 | keynote | Keynote: Towards Building Safe & Secure Agentic AI | — |
| Parth Asawa | AI Engineer World's Fair 2026 | speaker | Beyond Static Intelligence: Evaluating Continual Learning | Video |
| Dawn Song | 10th Annual Toronto Machine Learning Summit (TMLS) 2026 | speaker | Towards Building Safe and Secure AI: Lessons and Open Challenges | — |
| Ion Stoica | 10th Annual Toronto Machine Learning Summit (TMLS) 2026 | speaker | An Open AI Stack | — |
| Dawn Song | MCP Dev Summit North America 2026 | speaker | Towards Building Safe & Secure Agentic AI | — |
| David Patterson | ScaledML 2026 | speaker | — | — |
| Shu Liu | CIDR 2026 | paper | Supporting Our AI Overlords: Redesigning Data Systems to be Agent-First | Slides · Paper |
| Allison Czapracki | JupyterCon 2025 | speaker | Creating Accessible Jupyter Notebooks: UC Berkeley’s JupyterLab-A11y-checker Prototype | Slides |
| Balaji Alwar | JupyterCon 2025 | speaker | Creating Accessible Jupyter Notebooks: UC Berkeley’s JupyterLab-A11y-checker Prototype | Slides |
| Eric Rawn | JupyterCon 2025 | tutorial | Tutorial: Teaching AI With Small Language Models on JupyterHub | — |
| Eric Van Dusen | JupyterCon 2025 | lightning talk | Lightning Talk: Scaling Data 8 With JupyterHub Across California’s Colleges | Slides |
| Eric Van Dusen | JupyterCon 2025 | tutorial | Tutorial: Teaching AI With Small Language Models on JupyterHub | — |
| Fernando Pérez | JupyterCon 2025 | speaker | JupyterHealth: Bridging Wearables, Clinical Data, & Computational Workflows in the Jupyter Ecosystem | — |
| Fernando Pérez | JupyterCon 2025 | speaker | GeoJupyter: An Open Community for Accessible, Collaborative, and Interactive Geospatial Computing | — |
| Jonathan Ferrari | JupyterCon 2025 | lightning talk | Lightning Talk: Jupyter Books for Education and Open Source Curriculum | Slides |
| Michael Ball | JupyterCon 2025 | lightning talk | Lightning Talk: Teaching Data Engineering at Scale With Jupyter Notebooks at UC Berkeley | Slides |
| Min Ragan-Kelley | JupyterCon 2025 | tutorial | Tutorial: JupyterHub User Workshop | — |
| Silas Santini | JupyterCon 2025 | tutorial | Tutorial: Teaching AI With Small Language Models on JupyterHub | — |
| Dawn Song | PyTorch Conference 2025 | keynote | Keynote: Towards Building Safe and Secure Agentic AI | — |
| Ion Stoica | PyTorch Conference 2025 | keynote | Keynote: Ray: A Distributed Compute Engine for AI | — |
| Sergey Levine | PyTorch Conference 2025 | keynote | Keynote: Robot Foundation Models | — |
| Woosuk Kwon | PyTorch Conference 2025 | speaker | Meet the vLLM Maintainers | — |
| Natacha Crooks | Data Council 2025 | talk | From Concurrency Control to Concurrent Scheduling | — |
| Rolando Garcia | CIDR 2025 | paper | Flow with FlorDB: Incremental Context Maintenance for the Machine Learning Lifecycle | — |
| Anca Dragan | EMNLP 2024 | keynote | My Journey in AI Safety and Alignment | — |
| Sergey Levine | ODSC West 2024 | keynote | Reinforcement Learning with Large Datasets: a Path to Resourceful Autonomous Agents | — |
| Ion Stoica | PyTorch Conference 2024 | keynote | Keynote: Ray: A Distributed Framework for Heterogeneous Computing | — |
| Shreya Shankar | AI Engineer World's Fair 2024 | keynote | What We Learned From A Year of Building With LLMs | Video |
| Tiemo Bang | CIDR 2024 | paper | Optimizing the cloud? Don’t train models. Build oracles! | Paper |
| Jelani Nelson | NeurIPS 2023 | keynote | Sketching: core tools, learning-augmentation, and adaptive robustness | Video |
| Raluca Ada Popa | ODSC West 2023 | keynote | — | — |
| Frank Luan | Ray Summit 2023 | speaker | The Ray Dataplane: History and the Cloudsort World Record | — |
| Zongheng Yang | Ray Summit 2023 | speaker | SkyPilot: Run AI on Any Cloud | — |
| Dawn Song | Data + AI Summit 2023 | featured | — | — |
| Balaji Alwar | JupyterCon 2023 | poster | Supporting new pedagogical approaches in Education using Jupyter Hubs at Berkeley | — |
| Fernando Pérez | JupyterCon 2023 | speaker | Two decades of IPython and Jupyter - strategy, community and technical thoughts for the road ahead. | — |
| Fernando Pérez | JupyterCon 2023 | speaker | State of the Union: Jupyter Community | — |
| shane knapp | JupyterCon 2023 | poster | Supporting new pedagogical approaches in Education using Jupyter Hubs at Berkeley | — |
| Raluca Ada Popa | ODSC East 2023 | keynote | — | — |
| Amy Ousterhout | CIDR 2023 | paper | Zed: Leveraging Data Types to Process Eclectic Data | Slides · Paper |
| Paras Jain | CIDR 2023 | paper | Analyzing and Comparing Lakehouse Storage Systems | Slides · Video · Paper |
| Joe Hellerstein | QCon Plus November/December 2022 | keynote | On Beyond Serverless: CALM Lessons and a New Stack for Programming the Cloud | — |
| Ion Stoica | ODSC West 2022 | keynote | — | — |
| Michael I. Jordan | ODSC West 2022 | keynote | — | — |
| Pieter Abbeel | ODSC West 2022 | keynote | — | — |
| Joe Hellerstein | QCon San Francisco 2022 | keynote | On Beyond Serverless: CALM Lessons and a New Stack for Programming the Cloud | — |
| Anca Dragan | Ray Summit 2022 | keynote | — | — |
| Hao Zhang | Ray Summit 2022 | speaker | Alpa: Simple large model training and inference on Ray | — |
| Zhanghao Wu | Ray Summit 2022 | speaker | SkyML: Infra-less machine learning on any cloud | — |
| Zongheng Yang | Ray Summit 2022 | speaker | SkyML: Infra-less machine learning on any cloud | — |
| Audrey Cheng | Fifteenth LDBC TUC Meeting | speaker | TAOBench: An end-to-end benchmark for social network workloads | Slides · Video |
| John Dagdelen | Berlin Buzzwords 2022 | talk | Matscholar: The search engine for materials science researchers | Video |
| David Turner | Tableau Conference 2022 (TC22) | keynote | The Promise of Data Keynote | — |
| Stuart Russell | ODSC West 2021 | keynote | — | — |
| Dawn Song | Ray Summit 2021 | keynote | — | — |
| Dawn Song | ICDE 2021 (37th IEEE International Conference on Data Engineering) | keynote | Towards Building a Responsible Data Economy | — |
| Alvin Cheung | CIDR 2021 | paper | New Directions in Cloud Programming | Video · Paper |
| David Patterson | Ray Summit 2020 | keynote | Artificial Innovation Accelerates Artificial Intelligence | — |
| Michael I. Jordan | Ray Summit 2020 | keynote | Every Five Decades: A New Field of Engineering | — |
| Raluca Ada Popa | Ray Summit 2020 | keynote | A Secure Collaborative Learning Platform | — |
| Ion Stoica | SIGMOD/PODS 2020 | keynote | Systems and ML: When the Sum is Greater than Its Parts | — |
| Meredith Lee | WiDS Stanford Conference 2020 | speaker | — | — |
| Aravind Srinivas | ScaledML 2020 | poster | — | — |
| Ion Stoica | ScaledML 2020 | speaker | ML for Systems | Slides · Video |
| Joshua Bloom | ScaledML 2020 | speaker | Towards Physics-informed ML Inference In Astrophysics | Video |
| Fernando Perez | PyCon Colombia 2020 | keynote | — | — |
| Richard Liaw | PyData Los Angeles 2019 | speaker | A Guide to Modern Hyperparameter Tuning Algorithms | Video |
| Dawn Song | ODSC West 2019 | keynote | AI and Security | — |
| Michael I. Jordan | ODSC West 2019 | keynote (AI X track) | — | — |
| Edward Oakes | O'Reilly Artificial Intelligence Conference London 2019 | speaker | — | — |
| Michael Mahoney | O'Reilly Artificial Intelligence Conference London 2019 | speaker | — | — |
| Peter Schafhalter | O'Reilly Artificial Intelligence Conference London 2019 | speaker | — | — |
| Michael Jordan | O'Reilly Artificial Intelligence Conference San Jose 2019 | keynote | On gradient-based methods for finding game-theoretic equilibria | — |
| Ken Goldberg | Amazon re:MARS 2019 | featured | — | — |
| Pieter Abbeel | ODSC East 2019 | keynote | — | — |
| Dawn Song | ScaledML 2019 | speaker | AI and Security: Lessons and Future Directions | — |
| Meredith Lee | WiDS Stanford Conference 2019 | speaker | WiDS Datathon Winners Announced | Video |
| Karthik Ram | rstudio::conf 2019 | speaker | A guide to modern reproducible data science with R | Slides · Video |
| Joseph M Hellerstein | CIDR 2019 | paper | Serverless Computing: One Step Forward, Two Steps Back | Paper |