New York University
Circuit mix
Where New York 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.
- Research45%14 events
- Python & R data science39%12 events
- Modern data stack & practitioner6%2 events
- Vendor flagships & roadshows3%1 event
- AI engineering & MLOps3%1 event
- Software engineering & trading tech3%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
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.
- Title
- Other / unlabeled
Where they've grown or pulled back
DownNothing recorded in 2026; sponsored 1 conference in 2022.
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.
Pulled out 1
Not sponsored since 2024 or earlier, though a later event published a complete sponsor list without them.
- EMNLP (Conference on Empirical Methods in Natural Language Processing)last sponsored 2022; the conference ran again in 2023–26
Once or on and off 1
No clear direction, or a gap we can’t confirm because later sponsor lists are incomplete.
- New York R Conference (now The New York Data Science & AI Conference)once, 2024, unranked tier
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).
- ETH Zurich0.82
- Two Sigma0.76
- Meta0.75
- University of Michigan0.75
- UC Santa Cruz0.75
- DuckDB Labs0.72
- Twitter0.71
- Harvard University0.71
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 |
|---|---|---|
| Abu Dhabi Convention and Exhibition Bureau | 1 | 50% |
| Adobe | 1 | 50% |
| aiXplain | 1 | 50% |
| Amazon Web Services | 1 | 50% |
| Apple | 1 | 50% |
| Babelscape | 1 | 50% |
| Baidu | 1 | 50% |
| Beyond Limits | 1 | 50% |
| Bloomberg | 1 | 50% |
| ByteDance | 1 | 50% |
| CAIR | 1 | 50% |
| Chapman & Hall/CRC, Taylor & Francis Group | 1 | 50% |
| Cohere | 1 | 50% |
| Duolingo | 1 | 50% |
| 1 | 50% |
Neighborhood: companies with nearby conference footprints
New York 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 2024 (10th anniversary) | May 16–17, 2024 | New York, United States | Premium | Other |
| EMNLP 2022 | Dec 7–11, 2022 | Abu Dhabi, United Arab Emirates | Diamond | Title |
Speakers 31
| Speaker | Event | Role | Talk | Links |
|---|---|---|---|---|
| Anh Mai | CIDR 2027 | paper | DeciDB: In-Database Processing of Decision Queries | — |
| Sanchit Sahay | PyCon US 2026 | speaker | Asleep at the Wheel: Getting your SBOMs to pay attention to Python Builds | Video |
| Kushal Kolar | PyData Boston 2025 | speaker | fastplotlib: driving scientific discovery through data visualization | Video |
| Kyunghyun Cho | NeurIPS 2025 (San Diego) | keynote | From Benchmarks to Problems - A Perspective on Problem Finding in AI | Video |
| Juliana Freire | VLDB 2025 (51st) | keynote | Bridging Disciplines in Data Management Research to Solve Complex Data Problems | — |
| Palak Bansal | DataConnect Conference 2024 | speaker | GANs for Causal Inference: Harnessing Conditional Independence | — |
| Lukas Pühringer | EuroPython 2024 | talk | It’s happening: TUF joins PyPI (Warehouse) | Video |
| Hilke Schellmann | ODSC East 2024 | keynote / track keynote | — | — |
| Kyunghyun Cho | ACML 2023 | keynote | Beyond Test Accuracies for Studying Deep Neural Networks | — |
| George Perrett | New York R Conference 2023 | talk | Bayesian Boosting | Slides · Video |
| Yuanqing Wang | SciPy 2023 | speaker | From Espaloma to SAKE: To brew, distill, and mix force fields with balanced briskness, smoothness, and intricacy. | — |
| Marina Moore | QCon New York 2023 | speaker | Securing the Software Supply Chain: How in-toto and TUF Work Together to Combat Supply Chain Attacks | — |
| Paul Romer | JupyterCon 2023 | keynote | Paul Romer Keynote | — |
| Sumana Harihareswara | PyCon US 2023 | speaker | Argument Clinic: What Healthy Professional Conflict Looks Like | Video |
| Juliana Freire | EDBT/ICDT 2023 | keynote | Dataset Search for Data Discovery, Augmentation, and Explanation | — |
| Gary Marcus | EMNLP 2022 | keynote | Towards a Foundation for AGI | Video |
| David Chalmers | NeurIPS 2022 | keynote | Could a Large Language Model be Conscious? | — |
| Paul Romer | PyData NYC 2022 | keynote | — | — |
| Maria Sahakyan | PyData Yerevan 2022 | talk | Explainable AI as a Conventional Data Analysis Tool | — |
| Lukas Pühringer | EuroPython 2022 | talk | Work in Progress: Implementing PEP 458 to Secure PyPI downloads | — |
| Jennifer Hill | New York R Conference 2022 | talk | Deep Down, Everyone Wants to be Causal | Video |
| Julia Stoyanovich | ISWC 2021 | keynote | — | — |
| Jonathan Haidt | Modern Data Stack Conference 2021 | keynote | — | — |
| Julia Stoyanovich | KDD 2021 (virtual, Singapore) | ADS invited talk | TransFAT: Translating Fairness, Accountability, and Transparency into Data Science Practice | — |
| Julia Stoyanovich | EDBT/ICDT 2021 | keynote | Comparing Apples and Oranges: Fairness and Diversity in Ranking | — |
| Julia Stoyanovich | VLDB 2020 (46th) | keynote | Responsible Data Management | — |
| Sebastian Schelter | CIDR 2020 | paper | "Amnesia" - Machine Learning Models That Can Forget User Data Very Fast | Paper |
| Joshua Loftus | Data Council New York City 2019 | talk | Valid Inference after Model Selection and the selectiveInference Package | — |
| Juliana Freire | Data Council New York City 2019 | talk | Reproducibility in Data Science | — |
| Kyunghyun Cho | EMNLP-IJCNLP 2019 | keynote | Curiosity-driven Journey into Neural Sequence Models | — |
| Juliana Freire | ICDE 2019 (35th IEEE International Conference on Data Engineering) | keynote | Towards Usability, Transparency, and Trust in Data-Driven Exploration | Slides |