ETH Zurich
Also listed as 2 other names
ETH · ETH Zürich
Circuit mix
Where ETH Zurich shows up, by circuit. Each event counts once: 2 if it sponsored, 1 if it only had speakers. Hover a segment for the conference.
- Research47%14 events
- Python & R data science37%11 events
- Streaming7%2 events
- Modern data stack & practitioner3%1 event
- Software engineering3%1 event
- Geospatial & mapping3%1 event
The year around now
Conferences where ETH Zurich 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.
Where they've grown or pulled back
ETH Zurich has never sponsored a tracked conference, so this follows where its speakers appear instead.
UpHad speakers at 5 conferences in 2026, up from 3 in 2023.
Counted per conference. 2026 is the latest year whose conferences have mostly happened. A conference counts as no longer seen only when later events published speaker lists.
New conferences spoken at 4
First speaker in 2025 or later.
- ACM SIGMOD/PODS (International Conference on Management of Data)first spoke 2026, 1 speaker
- DuckConfirst spoke 2026, 1 speaker
- ICML (International Conference on Machine Learning)first spoke 2025, 1 speaker
- QConfirst spoke 2026, 1 speaker
No longer seen 11
No speakers since 2024 or earlier, though the conference published speaker lists after that.
- ACML (Asian Conference on Machine Learning)last seen 2022; the conference ran again with speaker lists in 2023–25
- EuroPythonlast seen 2022; the conference ran again with speaker lists in 2023–26
- Flink Forwardlast seen 2021; the conference ran again with speaker lists in 2022–26
- FOSS4Glast seen 2022; the conference ran again with speaker lists in 2023–26
- JSM (Joint Statistical Meetings)last seen 2023; the conference ran again with speaker lists in 2024–26
- LDBC Technical User Community (TUC) Meetinglast seen 2023; the conference ran again with speaker lists in 2024–26
- NeurIPS (Conference on Neural Information Processing Systems)last seen 2021; the conference ran again with speaker lists in 2022–25
- PyCon (national Python conferences)last seen 2021; the conference ran again with speaker lists in 2022–26
Show 3 more
- PyDatalast seen 2024; the conference ran again with speaker lists in 2025–26
- SciPy Conference (Scientific Computing with Python)last seen 2022; the conference ran again with speaker lists in 2023–26
- useR! (The R User Conference)last seen 2024; the conference ran again with speaker lists in 2025–26
Regulars 3
Speakers in most years of the span.
- CIDR (Conference on Innovative Data Systems Research)speakers in 5 of 7 years, 2021–27
- IEEE ICDE (International Conference on Data Engineering)speakers in 2 of 2 years, 2024–25
- JuliaConspeakers in 3 of 4 years, 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).
- EPFL0.77
- University of Washington0.76
- New York University0.75
- Harvard University0.74
- Two Sigma0.74
- Pennsylvania State University0.73
- TU Dresden0.70
- CNRS0.70
14 Cluster: JSM · useR! circuit →
Often sponsors alongside
Companies that sponsored the same events, by number of shared events (out of 0 this company sponsored).
No co-sponsors: this company has no recorded sponsorships, or sponsored alone.
Neighborhood: companies with nearby conference footprints
ETH Zurich (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 0
No sponsorships recorded for ETH Zurich.
Speakers 40
| Speaker | Event | Role | Talk | Links |
|---|---|---|---|---|
| Jonas Dann | CIDR 2027 | paper | CODAs: Computational Data Paths for Lakehouses | — |
| Niklas Viebig | JuliaCon Global 2026 | speaker | Differentiable Climate Modeling: Calibrating SpeedyWeather with Enzyme | — |
| Niklas Viebig | JuliaCon Global 2026 | speaker | A learned surface roughness scheme for climate prediction in SpeedyWeather.jl | — |
| Niklas Viebig | JuliaCon Global 2026 | speaker | The GPU acceleration of SpeedyWeather.jl, the friendly and flexible climate model | — |
| Herminio Vazquez-Cano | DuckCon #7 | talk | Phages and DuckDB: The mighty duo against the giants | — |
| Gustavo Alonso | SIGMOD/PODS 2026 | keynote | A New Golden Era for Data Management | Slides |
| Thea Klaeboe Aarrestad | QCon London 2026 | speaker | Machine Learning at the Edge of Scale and Speed: Nanosecond Inference at the CERN Large Hadron Collider | — |
| Pinghe Li | CIDR 2026 | paper | End-to-End Declarative Data Analytics: Co-designing Engines, Interfaces, and Cloud Infrastructure | Slides · Paper |
| Andreas Krause | ICML 2025 | keynote | Closing the Loop: Machine Learning for Optimization and Discovery | — |
| Yongjun He | ICDE 2025 (41st IEEE International Conference on Data Engineering) | industry paper | MLKV: Efficiently Scaling up Large Embedding Model Training with Disk-based Key-Value Storage | — |
| Thea Klaeboe Aarrestad | CIDR 2025 | keynote | Pushing the limits of real-time ML: Nanosecond inference for Physics Discovery at the Large Hadron Collider | — |
| Francesc Martí Escofet | PyData Paris 2024 | talk | Catering Causal Inference: An Introduction to 'metalearners', a Flexible MetaLearner Library in Python | — |
| Giacomo Aloisi | JuliaCon 2024 | speaker | SeismicWaves.jl: a wave simulation package for FWI on multi-xPUs | Slides |
| Mauro Werder | JuliaCon 2024 | lightning | Subglacial water flow simulations on GPUs | — |
| Mauro Werder | JuliaCon 2024 | speaker | FastIce.jl: a massively parallel ice flow model running on GPUs | — |
| Matthias Bannert | useR! 2024 | poster | Open Time Series Initiative – Human-Friendly, Machine-Readable Time Series | — |
| Matthias Bannert | useR! 2024 | poster | Open Time Series Initiative – Human-Friendly, Machine-Readable Time Series | — |
| Dan Graur | ICDE 2024 (40th IEEE International Conference on Data Engineering) | industry paper | Addressing the Nested Data Processing Gap: JSONiq Queries on Snowflake through Snowpark | — |
| Gustavo Alonso | ICDE 2024 (40th IEEE International Conference on Data Engineering) | keynote | How serious are we about green computing? The impact of data intensive computing | — |
| Peter Bühlmann | JSM 2023 (Joint Statistical Meetings) | keynote | IMS: What Does It Stand For? What Could It Stand For? | — |
| Ludovic Räss | JuliaCon 2023 | workshop | Differentiable modelling on GPUs | — |
| Ludovic Räss | JuliaCon 2023 | speaker | Julia for High-Performance Computing | — |
| Ludovic Räss | JuliaCon 2023 | speaker | Massively parallel inverse modelling on GPUs with Enzyme | — |
| Ludovic Räss | JuliaCon 2023 | speaker | Scalable 3-D PDE Solvers Tackling Hardware Limit | — |
| Maciej Besta | Sixteenth LDBC TUC Meeting | speaker | Neural Graph Databases with Graph Neural Networks | Video |
| Andreas Krause | ACML 2022 | keynote | Safe and Efficient Exploration via Bayesian World Models | — |
| Michael Schmuki | FOSS4G 2022 | speaker | WebAssembly4G: Where we are, and where we're heading | — |
| Kevin Yamauchi | SciPy 2022 | tutorial | Interactive image analysis with napari | — |
| Michal Maciejewski | EuroPython 2022 | talk | When Models Query Models | Video |
| Dario Korolija | CIDR 2022 | paper | Farview: Disaggregated Memory with Operator Off-loading for Database Engines | Video · Paper |
| Alessio Figalli | NeurIPS 2021 | keynote | Optimal Transport: Past, Present, and Future | — |
| Tal Ben-Nun | PyCon Sweden 2021 | keynote | Keynote - Bridging Productivity, Portability, and Performance with Data-Centric Python | — |
| Vasiliki Kalavri | Flink Forward Global 2021 | keynote | KEYNOTE | Expert Panel: Current & Future State of the Art in Real-Time Data Infrastructure | — |
| Leonel Aguilar Melgar | CIDR 2021 | paper | Ease.ML: A Lifecycle Management System for Machine Learning | Video · Paper |
| Marloes Maathuis | NeurIPS 2020 | keynote | Causal Learning | Video |
| Matthew Brookes | Flink Forward Europe 2019 | speaker | Moving on from RocksDB to something FASTER | — |
| Vasiliki Kalavri | Flink Forward Europe 2019 | speaker | Self-managed and automatically reconfigurable stream processing | — |
| Dr Egor Kraev | PyData London 2019 | tutorial | Choosing the right neural generative model for your problem | — |
| Chandrasekhar Ramakrishnan | SciPy 2019 | tutorial | — | — |
| Mustafa Anil Tuncel | EuroPython 2019 | talk | Bioinformatics pipeline for revealing tumour heterogeneity | Slides · Video |