QuantumBlack
Also listed as 2 other names
QuantumBlack, AI by McKinsey · Quantumblack
Circuit mix
Where QuantumBlack shows up, by circuit. Each event counts once: 2 if it sponsored, 1 if it only had speakers. Hover a segment for the conference.
- Research44%7 events
- Python & R data science41%12 events
- Vendor flagships & roadshows6%1 event
- AI engineering & MLOps6%2 events
- Modern data stack & practitioner3%1 event
The year around now
Conferences where QuantumBlack 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.
- Platinum
- Gold
- Silver
- Bronze
Where they've grown or pulled back
DownNothing recorded in 2026; sponsored 2 conferences 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.
Moved down 1
Best tier fell between the first and latest year with a ranked tier.
- NeurIPS (Conference on Neural Information Processing Systems)Platinum 2019 → Silver 2022
Pulled out 3
Not sponsored since 2024 or earlier, though a later event published a complete sponsor list without them.
- ACML (Asian Conference on Machine Learning)last sponsored 2019; the conference ran again in 2021–25
- ICML (International Conference on Machine Learning)last sponsored 2022; the conference ran again in 2023–26
- MLSys (Conference on Machine Learning and Systems)last sponsored 2019; the conference ran again in 2020 and 2022–26
Once or on and off 2
No clear direction, or a gap we can’t confirm because later sponsor lists are incomplete.
- Data + AI Summitonce, 2019, Bronze
- PyDataonce, 2019, Gold
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).
- IMC0.86
- Abridge0.82
- Optiver0.81
- Ollama0.80
- G-Research0.80
- DatologyAI0.80
- Point72 / Cubist Systematic Strategies0.79
- Cartesia AI0.78
8 Cluster: NeurIPS · ICML circuit →
Often sponsors alongside
Companies that sponsored the same events, by number of shared events (out of 9 this company sponsored).
| Company | Shared events | Share |
|---|---|---|
| Bloomberg | 7 | 78% |
| 7 | 78% | |
| Microsoft | 7 | 78% |
| Apple | 6 | 67% |
| DeepMind | 6 | 67% |
| IBM | 6 | 67% |
| Meta | 6 | 67% |
| Amazon Web Services | 5 | 56% |
| Bosch | 5 | 56% |
| The D. E. Shaw Group | 5 | 56% |
| Hudson River Trading | 5 | 56% |
| Netflix | 5 | 56% |
| Point72 / Cubist Systematic Strategies | 5 | 56% |
| Squarepoint Capital | 5 | 56% |
| Two Sigma | 5 | 56% |
Neighborhood: companies with nearby conference footprints
QuantumBlack (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 9
| Event | Date | Place | Tier as listed | Normalized tier |
|---|---|---|---|---|
| NeurIPS 2022 | Nov 28, 2022 – Dec 9, 2022 | New Orleans, United States | Silver | Silver |
| ICML 2022 | Jul 17–23, 2022 | Baltimore, United States | Silver | Silver |
| NeurIPS 2020 | Dec 6–12, 2020 | — | Gold | Gold |
| NeurIPS 2019 | Dec 8–14, 2019 | Vancouver, Canada | Platinum | Platinum |
| ACML 2019 | Nov 17–19, 2019 | Nagoya, Japan | Gold sponsors | Gold |
| PyData London 2019 | Jul 12–14, 2019 | London, United Kingdom | Gold | Gold |
| ICML 2019 | Jun 9–15, 2019 | Long Beach, United States | Silver | Silver |
| Spark + AI Summit 2019 | Apr 23–25, 2019 | San Francisco, United States | Bronze | Bronze |
| SysML 2019 | Mar 31, 2019 – Apr 2, 2019 | Stanford, United States | Silver | Silver |
Speakers 17
| Speaker | Event | Role | Talk | Links |
|---|---|---|---|---|
| Imad Touil | AI Engineer World's Fair 2026 | speaker | AI-Native Organisations runs on Skills: How to Extract, Structure, evaluate and Scale Them | Video |
| Dmitry Sorokin | PyCon Ireland 2025 | talk | Turning ML and Data Pipelines into AI Agents with Kedro and LangGraph | — |
| Dmitry Sorokin | PyCon Ireland 2024 | talk | End-to-end Machine Learning with open-source | — |
| Juan Luis Cano Rodríguez | PyData London 2024 | tutorial | Analytics engineering without dbt? Building the composable Python data stack with Kedro and Ibis | — |
| Juan Luis Cano Rodríguez | PyCon Lithuania 2023 | workshop | Analyze your data at the speed of light with Polars and Kedro | — |
| Lim H. | EuroPython 2021 Online | talk | Reproducible and Deployable Data Science with Open-Source Python | Slides · Video |
| Yetunde Dada | PyCon US 2021 (Online) | speaker | Reproducible and maintainable data science code with Kedro | Video |
| Ivan Torroledo | PyCon Colombia 2020 | talk | Taking machine learning models to production level | — |
| Tom Goldenberg | PyData Los Angeles 2019 | speaker | Kedro + MLflow – Reproducible and versioned data pipelines at scale | Video |
| Guillaume Baquiast | PyData Cambridge 2019 | talk | GA2M: combining accuracy and explainability | — |
| Ivan Danov | PyData Cambridge 2019 | talk | A Kedro Mindset for Data Scientists | — |
| Deepyaman Datta | PyData New York City 2019 | speaker | New and Upcoming | — |
| Ian Whalen | PyData New York City 2019 | speaker | Implementing Lightweight Random Indexing for Polylingual Text Classification | Video |
| Philip Pilgerstorfer | O'Reilly Artificial Intelligence Conference London 2019 | speaker | — | — |
| Tim Daines | O'Reilly Artificial Intelligence Conference London 2019 | speaker | — | — |
| Yetunde Dada | PyCon DE & PyData Berlin 2019 | talk | Production-level data pipelines that make everyone happy using Kedro | — |
| Paul Beaumont | Data Council Singapore 2019 | talk | Causal Inference: Making the Right Intervention | — |