Columbia University
Also listed as 6 other names
Columbia Business School · Columbia Data Science Institute · Columbia University / The New York Times · Columbia University | Netflix · Columbia University | Statistics · Columbia Unviersity
Circuit mix
Where Columbia 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.
- Python & R data science46%15 events
- Research16%6 events
- Enterprise, analyst & AI expos14%5 events
- Alt data & financial information11%4 events
- AI engineering & MLOps5%2 events
- Postgres & open-source databases3%1 event
- Cloud providers3%1 event
- Geospatial & mapping3%1 event
The year around now
Conferences where Columbia 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
Distinct speakers
People from this company on a program that year, each counted once.
Sponsorships by tier
Sponsorship rows per year (one per event and listing), stacked by normalized tier.
- Silver
Where they've grown or pulled back
DownNothing recorded in 2026; sponsored 1 conference in 2023.
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.
Steady 1
Sponsored in most years of its span at the same tier.
- New York R Conference (now The New York Data Science & AI Conference)every year 2022–23, 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).
- MIT0.81
- New York University0.72
- Harvard University0.69
- University of Illinois Urbana-Champaign0.65
- Northeastern University0.64
- Yale University0.64
- JPMorgan Chase0.63
- University of Washington0.63
4 Cluster: PyData · PyCon 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 |
|---|---|---|
| Chapman & Hall/CRC, Taylor & Francis Group | 2 | 100% |
| Manning | 2 | 100% |
| Pearson | 2 | 100% |
| R Consortium | 2 | 100% |
| Springer Nature | 2 | 100% |
| No Starch Press | 1 | 50% |
| Posit | 1 | 50% |
| RStudio | 1 | 50% |
| Saturn Cloud | 1 | 50% |
| Spring Health | 1 | 50% |
| Sweet Francesca | 1 | 50% |
Neighborhood: companies with nearby conference footprints
Columbia 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 |
|---|---|---|---|---|
| New York R Conference 2023 | Jul 13–14, 2023 | New York, United States | Silver | Silver |
| New York R Conference 2022 | Jun 9–10, 2022 | New York, United States | Silver | Silver |
Speakers 42
| Speaker | Event | Role | Talk | Links |
|---|---|---|---|---|
| Tal Zussman | CIDR 2027 | paper | Reports of mmap()'s Death Are Greatly Exaggerated | — |
| Eric Siegel | DDAC 2026 | keynote | Predictive AI’s Big Moment: How It Makes Generative AI Reliable | — |
| Agostino Capponi | New York Summer Data Summit 2026 | speaker | The data arms race and disruptive agentic AI | — |
| Abby Tse | PyData London 2026 | tutorial | Learn to Unlock Document Intelligence with Open-Source AI | — |
| Charlie Summers | CIDR 2026 | paper | Please Don't Kill My Vibe: Empowering Agents with Data Flow Control | Paper |
| Cecilia Dones | CDAO Fall 2025 | speaker | — | — |
| Andrew Gelman | The New York Data Science & AI Conference 2025 | talk | What's Going On In There? Bayesian Tools for Understanding a Fitted Model | Video |
| Chris Wiggins | KDD 2025 (31st ACM SIGKDD Conference) | ADS invited talk | — | — |
| Marco Giometto | JuliaCon 2025 | lightning | Fast & flexible processing of lidar data with PointClouds.jl | — |
| Christos H. Papadimitriou | SIGMOD/PODS 2025 | keynote | How to Build a Brain? | — |
| Cecilia Dones | CDAO Fall 2024 | speaker | — | — |
| Cecilia Dones | 18th Annual CDOIQ Symposium | speaker | — | — |
| Michael Oliver Weinberg | New York Summer Data Summit 2024 | speaker | Fireside Chat: Data from an Asset Owners Perspective | — |
| Andrew Gelman | New York R Conference 2024 (10th anniversary) | talk | It's About Time | Video |
| Vikram Waradpande | PyCon US 2024 | speaker | You've got trust issues, we've got solutions: Differential Privacy | Video |
| Alexis Wichowski | Data Universe 2024 | keynote | How Data Is Pushing the Frontiers of Innovation | — |
| Tamer Eldeeb | CIDR 2024 | paper | Chablis: Fast and General Transactions in Geo-Distributed Systems | Paper |
| Zezhou Huang | CIDR 2024 | paper | The Fast and the Private: Task-based Dataset Search | Paper |
| Luca Carloni | STAC Summit New York, Fall 2023 | speaker | Building heterogeneous compute pipelines | — |
| Vikram Waradpande | PyCon DE & PyData Berlin 2023 | talk | You've got trust issues, we've got solutions: Differential Privacy | — |
| Sachin Kadyan | AWS re:Invent 2022 | chalk talk | The convergence of HPC and ML on AWS | Slides |
| Ben Lis | PGConf NYC 2022 | speaker | Optimal Data Loads | Slides |
| Charles Stern | FOSS4G 2022 | speaker | Pangeo Forge: Crowdsourcing Open Data in the Cloud | — |
| Ryan Abernathey | FOSS4G 2022 | speaker | Pangeo Forge: Crowdsourcing Open Data in the Cloud | — |
| Julius Busecke | SciPy 2022 | speaker | Cutting Edge Climate Science in the Cloud with Pangeo | — |
| Tom Nicholas | SciPy 2022 | tutorial | Xarray: Friendly, Interactive, and Scalable Scientific Data Analysis | — |
| Andrew Gelman | New York R Conference 2022 | talk | When You do Applied Statistics, You're Acting Like a Scientist. Why Does this matter? | Video |
| Andrew Gelman | New York R Conference 2021 | talk | Wrong Again! 30+ Years of Statistical Mistakes | Video |
| Kenneth A. Ross | SIGMOD/PODS 2021 | keynote | Utilizing (and Designing) Modern Hardware for Data-Intensive Computations: The Role of Abstraction | — |
| Oded Netzer | Neudata Summer Online Summit 2021 | speaker | — | — |
| Andrew Gelman | R Conference "New York" 2020 (virtual) | talk | Truly Open Science: From Design and Data Collection to Analysis and Decision Making | Video |
| Jonah Gabry | R Conference "New York" 2020 (virtual) | talk | A New Way to Interface with Stan from R | Video |
| Monica Thieu | R Conference "New York" 2020 (virtual) | talk | How to Prepare and Teach an R Lesson | Video |
| Thomas J Fan | PyData Austin 2019 | speaker | Do You Want To Build A Forest? | Video |
| Andreas Mueller | ODSC Europe 2019 | featured | — | — |
| Jared Lander | ODSC Europe 2019 | featured | — | — |
| Thomas J Fan | PyData New York City 2019 | speaker | What's now in NumFOCUS projects? (Part 2) | — |
| Thomas J Fan | PyData New York City 2019 | speaker | Deep Dive into scikit-learn's HistGradientBoosting Classifier and Regressor | Video |
| Thomas Fan | SciPy 2019 | speaker | Skorch - A Union of Scikit-learn and PyTorch | — |
| Andrew Gelman | New York R Conference 2019 | talk | Solve All Your Statistics Problems Using P-Values | Video |
| David Madigan | New York R Conference 2019 | talk | Towards systematic evidence generation from real-world healthcare data | Video |
| Tony Jebara | O'Reilly Artificial Intelligence Conference New York 2019 | keynote | Machine learning for personalization | — |