Caltech
Circuit mix
Where Caltech shows up, by circuit. Each event counts once: 2 if it sponsored, 1 if it only had speakers. Hover a segment for the conference.
- Modern data stack & practitioner63%4 events
- Python & R data science25%2 events
- Vendor flagships & roadshows13%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
| Conference | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 | 2025 | 2026 | 2027 | 2028 |
|---|---|---|---|---|---|---|---|---|---|---|
| Data Con LA | ||||||||||
| SciPy Conference (Scientific Computing with Python) | ||||||||||
| Data + AI Summit | ||||||||||
| PyData |
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.
- Silver
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.
- Data Con LAlast sponsored 2022; the conference ran again in 2023–26
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).
- UCLA0.83
- Arizona State University0.79
- StarRocks0.71
- QuantStack0.69
- Rice University0.67
- Posit0.66
- prefix.dev0.62
- University of Virginia0.61
8 Cluster: PyData · posit::conf circuit →
Often sponsors alongside
Companies that sponsored the same events, by number of shared events (out of 1 this company sponsored).
| Company | Shared events | Share |
|---|---|---|
| Amazon Web Services | 1 | 100% |
| Archangel Technology Consultants | 1 | 100% |
| Boomi | 1 | 100% |
| CloudTrakr | 1 | 100% |
| Data 4 Good | 1 | 100% |
| Data Analysis Journal | 1 | 100% |
| Instaclustr | 1 | 100% |
| LOPSA | 1 | 100% |
| MongoDB | 1 | 100% |
| MountainTop Data | 1 | 100% |
| openSUSE | 1 | 100% |
| RMDS Lab | 1 | 100% |
| StarRocks | 1 | 100% |
| USC | 1 | 100% |
Neighborhood: companies with nearby conference footprints
Caltech (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 1
| Event | Date | Place | Tier as listed | Normalized tier |
|---|---|---|---|---|
| Data Con LA 2022 | Aug 13, 2022 | Los Angeles, United States | Silver | Silver |
Speakers 9
| Speaker | Event | Role | Talk | Links |
|---|---|---|---|---|
| Joshua Cook | Data Con LA 2026 | speaker | Extraction Trees: Reliable Structured Data from Messy Text | Video |
| Brigitta Sipőcz | SciPy 2023 | speaker | [BoF Room 103] SciPy 2023 Sprint Prep BoF | — |
| Brigitta Sipőcz | SciPy 2023 | speaker | Open Source Sprints [Kickoff in Room 204] | — |
| Brigitta Sipőcz | SciPy 2023 | speaker | Open Source Sprints [Kickoff in Room 204] | — |
| Ash Pahwa | Data Con LA 2022 | speaker | Transformers for NLP | — |
| Ash Pahwa | Data Con LA 2021 | speaker | The Future of Language Models | — |
| Manu Flores | PyData Los Angeles 2019 | speaker | Analyzing genetic networks using neural networks | Video |
| Katie Bouman | Spark + AI Summit Europe 2019 | keynote | — | — |
| Ash Pahwa | Data Con LA 2019 | speaker | Optimization Algorithms for Deep Learning | — |