Conferences / SciPy Conference (Scientific Computing with Python)
SciPy 2025
Jul 7–13, 2025 · Tacoma Convention Center, Tacoma, WA, United States
- Conference
- SciPy Conference (Scientific Computing with Python) Data science & ML
- Dates
- Jul 7, 2025 – Jul 13, 2025
- Venue
- Tacoma Convention Center
- Place
- Tacoma, WA, United States
- Format
- Hybrid
- Status
- Past
- Attendance
- —
- Website
- scipy2025.scipy.org
- Recorded
- 19 sponsors · 176 speaker appearances
- Notes
- 24th annual SciPy. Virtual conference passes available. Tutorials July 7-8, conference July 9-11, sprints July 12-13. Speakers: all confirmed talks, tutorials, keynotes and BoFs from the pretalx schedule; affiliations from pretalx bios (keynote affiliations from the home page) only where stated. Regular pricing from May 1: combined passes +$100, single passes +$50. Sponsor logos identified from image files where alt text was empty; tier captions under logos taken as stated.
Ticket prices
| Ticket | Price | Valid until | Notes | Source |
|---|---|---|---|---|
| Student conference only (early bird) | $235 | Apr 30, 2025 | 3.9% processing fee included in final price | web.archive.org |
| Student tutorials only (early bird) | $235 | Apr 30, 2025 | 3.9% processing fee included in final price | web.archive.org |
| Academic conference only (early bird) | $400 | Apr 30, 2025 | 3.9% processing fee included in final price | web.archive.org |
| Academic tutorials only (early bird) | $450 | Apr 30, 2025 | 3.9% processing fee included in final price | web.archive.org |
| Student conference & tutorials (early bird) | $470 | Apr 30, 2025 | 3.9% processing fee included in final price | web.archive.org |
| Standard conference only (early bird) | $500 | Apr 30, 2025 | 3.9% processing fee included in final price | web.archive.org |
| Standard tutorials only (early bird) | $550 | Apr 30, 2025 | 3.9% processing fee included in final price | web.archive.org |
| Academic conference & tutorials (early bird) | $850 | Apr 30, 2025 | 3.9% processing fee included in final price | web.archive.org |
| Standard conference & tutorials (early bird) | $1,050 | Apr 30, 2025 | 3.9% processing fee included in final price | web.archive.org |
| Virtual conference only | $100 | — | web.archive.org |
Sponsors 19
Title / headline 1
- Enthought · Institutional Sponsor
Platinum 1
Gold 7
- Amazon Web Services
- Anaconda
- Curvenote · Gold / Proceedings Sponsor
- MotherDuck · Gold / Poster Sponsor
- Posit
- prefix.dev
- Wherobots
Silver 4
- Open OnDemand
- OpenTeams · Silver / Teen Track Sponsor
- Quansight · Silver / Tutorial Infrastructure Sponsor
Community 4
- CodeDay · Community Partner
- PyData Seattle · Community Partner
- Seattle Spark + AI Meetup · Community Partner
- Women Techmakers Seattle · Community Partner
Other 2
- Earthmover · Attendee Social Host
- University of Washington · Sprints Host
Speakers and talks 176
| Speaker | Company | Role | Talk | Links |
|---|---|---|---|---|
| Charles R Harris | — | Keynote | My Dinner with Numeric, Numpy, and Scipy: A Retrospective from 2001 to 2025 with Comments and Anecdotes | — |
| Christopher Lamb | NVIDIA | Keynote | Python at the Speed of Light: Accelerating Science with CUDA Python | — |
| Kathryn D. Huff | University of Illinois Urbana-Champaign | Keynote | What We Maintain, We Defend | — |
| Malvika Sharan | Open Life Science (OLS) | Keynote | The Myth of Artificial: Spotlighting Community Intelligence for Responsible Science | — |
| Yusra AlSayyad | Vera C. Rubin Observatory | Keynote | Rubin Observatory: What will you discover when you’re always watching | — |
| Adam Symington | Synmax | Tutorial | Geospatial data visualisation in Python | — |
| Adam Thompson | — | Speaker | AI as a Detector: Lessons in Real Time Pulsar Discovery | — |
| Akshay Agrawal | marimo | Speaker | marimo: an open-source reactive Python notebook | — |
| Albert Steppi | Quansight | Speaker | SciPy’s New Infrastructure for Probability Distributions and Random Variables | — |
| Alessio Buccino | — | Speaker | SpikeInterface: Streamlining End-to-End Spike Sorting Workflows | — |
| Alex Monahan | MotherDuck | Tutorial | All the SQL a Pythonista needs to know: an introduction to SQL and DataFrames with DuckDB | — |
| Alexander Kaszynski | — | Tutorial | 3D Visualization with PyVista | — |
| Alexander Kmoch | — | Speaker | Using Discrete Global Grid Systems in the Pangeo ecosystem | — |
| Allison Ding | NVIDIA | Speaker | Unlocking AI Performance with NeMo Curator: Scalable Data Processing for LLMs | — |
| Allison Ding | NVIDIA | Tutorial | Scaling Clustering for Big Data: Leveraging RAPIDS cuML | — |
| Ana Comesana | Lawrence Berkeley National Laboratory | Speaker | Advanced Machine Learning Techniques for Predicting Properties of Synthetic Aviation Fuels using Python | — |
| Anant Mittal | eScience Institute | Bof | AI for Scientific Discovery | — |
| Angus Hollands | 2i2c | Speaker | Jupyter Book 2.0 – A Next-Generation tool for sharing for Computational Content | — |
| Anil Sharma | — | Bof | Agentic-Ai and latency implications | — |
| Anjali Datta | Vista | Tutorial | Building machine learning pipelines that scale: a case study using Ibis and IbisML | — |
| Anne Fouilloux | — | Speaker | Using Discrete Global Grid Systems in the Pangeo ecosystem | — |
| Antoni Liria Sala | — | Tutorial | Retrieval Augmented Generation (RAG) for LLMs | — |
| Archit Datar | Celanese International | Tutorial | Show your work: Tutorial on building and hosting web applications | — |
| Avik Basu | — | Bof | Open Code, Open Science: What’s Getting in Your Way? | — |
| Axel Sirota | — | Speaker | Polyglot RAG: Building a Multimodal, Multilingual, and Agentic AI Assistant | — |
| Bane Sullivan | — | Tutorial | 3D Visualization with PyVista | — |
| Ben Miller | — | Speaker | RydIQule: A Package for Modelling Quantum Sensors | — |
| Benoît Bovy | — | Speaker | Using Discrete Global Grid Systems in the Pangeo ecosystem | — |
| Benoît Bovy | — | Speaker | The brave new world of slicing and dicing Xarray objects. | — |
| Brigitta Sipőcz | — | Bof | Reliable executable tutorials -- CI/CD challenges | — |
| Brodie Vidrine | NOAA | Speaker | Breaking Out of the Loop: Refactoring Legacy Software with Polars | — |
| Bryce Adelstein Lelbach | NVIDIA | Speaker | cuTile, the New/Old Kid on the Block: Python Programming Models for GPUs | — |
| C.A.M. Gerlach | — | Speaker | Remote development for students and indie researchers with Spyder | — |
| Cainã Max Couto da Silva | — | Tutorial | Building an AI Agent for Natural Language to SQL Query Execution on Live Databases | — |
| Carlos Cordoba | — | Speaker | Remote development for students and indie researchers with Spyder | — |
| Carlos García Jurado Suarez | UW Scientific Software Engineering Center (SSEC) | Bof | AI for Scientific Discovery | — |
| Carol Willing | — | Tutorial | Create Your First Python Package: Make Your Python Code Easier to Share and Use | — |
| Charles Turner | ACCESS-NRI | Speaker | Python for Climate Science: Using Intake to provide easy access to Climate Model data | — |
| Charlie Becker | NSF | Speaker | Physical XAI - Going Beyond Traditional XAI Methods in Earth System Science | — |
| Charlotte Wickham | Posit | Speaker | From One Notebook to Many Reports: Automating with Quarto | — |
| Chirag Shah | — | Speaker | Accelerating scientific data releases: Automated metadata generation with LLM agents | — |
| Chris Holdgraf | 2i2c | Speaker | Jupyter Book 2.0 – A Next-Generation tool for sharing for Computational Content | — |
| Cordero Core | University of Washington | Bof | AI for Scientific Discovery | — |
| Daniel Chen | Posit | Tutorial | Shiny for Python: Building Production-Ready Dashboards in Python | — |
| Debarshi Datta | Florida Atlantic University | Tutorial | A Hands-on Tutorial towards building Explainable Machine Learning using SHAP, GINI, LIME, and Permutation Importance | — |
| Deepak Cherian | Earthmover | Tutorial | Hierarchical Data Analysis with Xarray DataTree & Zarr | — |
| Deepak Cherian | Earthmover | Speaker | The brave new world of slicing and dicing Xarray objects. | — |
| Deepyaman Datta | — | Speaker | Python is all you need: an overview of the composable, Python-native data stack | — |
| Deepyaman Datta | — | Tutorial | Building machine learning pipelines that scale: a case study using Ibis and IbisML | — |
| Denis Leshchev | NVIDIA | Speaker | Edge processing of X-ray ptychography: enabling real-time feedback for high-speed data acquisition | — |
| Draga Doncila Pop | — | Tutorial | Create custom image visualization and analysis tools with napari | — |
| Dylan Wootton | — | Tutorial | Vega-Altair: A Structured Way to Build Interactive Charts | — |
| Elise Chavez | University of Washington | Speaker | Enabling Innovative Analysis on Heterogeneous Clusters through HTCdaskgateway | — |
| Elliot Marx | Chalk | Speaker | Real-time ML: Accelerating Python for inference (< 10ms) at scale | — |
| Emily Dorne | DrivenData | Speaker | Zamba: Computer vision for wildlife conservation | — |
| Eniola Awowale | NASA | Tutorial | Hierarchical Data Analysis with Xarray DataTree & Zarr | — |
| Enrique Molina Giménez | Universitat Rovira i Virgili | Speaker | Processing Cloud-optimized data in Python (Dataplug) | — |
| Enrique Molina Giménez | Universitat Rovira i Virgili | Tutorial | Processing Cloud-optimized data in Python with Serverless Functions (Lithops, Dataplug) | — |
| Eric Ma | Moderna | Tutorial | Network Analysis Made Simple | — |
| Eric Ma | Moderna | Tutorial | Building with LLMs Made Simple | — |
| Erik Welch | NVIDIA | Speaker | Lessons Learned from Adding Backend Dispatching to NetworkX and scikit-image | — |
| Fernando Cervantes Sanchez | The Jackson Laboratory | Tutorial | Scaling-up deep learning inference to large-scale bioimage data | — |
| Fernando Cervantes Sanchez | The Jackson Laboratory | Speaker | An Active Learning plugin in Napari to fine tune models for large-scale bioimage analysis | — |
| Filippo Balzaretti | Stanford University | Speaker | Can Scientific Python Tools Unlock the Secrets of Materials? The Electrons That Machine-Learning Can't Handle | — |
| Frank Strug | University of Illinois Chicago | Speaker | KvikUproot - Reading and Deserializing High Energy Physics Data with KvikIO and CuPy | — |
| Franklin Koch | Curvenote | Speaker | Jupyter Book 2.0 – A Next-Generation tool for sharing for Computational Content | — |
| Guen Prawiroatmodjo | MotherDuck | Tutorial | All the SQL a Pythonista needs to know: an introduction to SQL and DataFrames with DuckDB | — |
| Heberto Mayorquin | — | Speaker | SpikeInterface: Streamlining End-to-End Spike Sorting Workflows | — |
| Henry Fredrick Schreiner III | Princeton University | Speaker | Packaging a Scientific Python Project | — |
| hugo bowne-anderson | — | Speaker | Escaping Proof-of-Concept Purgatory: Building Robust LLM-Powered Applications | — |
| hugo bowne-anderson | — | Tutorial | Building LLM-Powered Applications for Data Scientists and Software Engineers | — |
| Ian Hunt-Isaak | — | Speaker | Xarray across biology. Where are we and where are we going? | — |
| Ian Hunt-Isaak | — | Tutorial | Hierarchical Data Analysis with Xarray DataTree & Zarr | — |
| Inessa Pawson | — | Bof | Open Code, Open Science: What’s Getting in Your Way? | — |
| Inessa Pawson | — | Tutorial | Create Your First Python Package: Make Your Python Code Easier to Share and Use | — |
| Inessa Pawson | — | Bof | AI for Scientific Discovery | — |
| Irina Demeshko | NVIDIA | Speaker | Scaling NumPy for Large-Scale Science: The cuPyNumeric Approach | — |
| Jacob Matson | — | Tutorial | All the SQL a Pythonista needs to know: an introduction to SQL and DataFrames with DuckDB | — |
| Jacob Tomlinson | NVIDIA | Speaker | EffVer: Versioning code by the effort required to upgrade | — |
| Jacob Tomlinson | NVIDIA | Speaker | Teaching Python with GPUs: Empowering educators to share knowledge that uses GPUs | — |
| Jay Qi | DrivenData | Speaker | Zamba: Computer vision for wildlife conservation | — |
| Jean-Marc Delouis | CNRS | Speaker | Using Discrete Global Grid Systems in the Pangeo ecosystem | — |
| Jeremiah Paige | — | Tutorial | Create Your First Python Package: Make Your Python Code Easier to Share and Use | — |
| Jeremiah Paige | — | Bof | Open Code, Open Science: What’s Getting in Your Way? | — |
| Jim Kitchen | Anaconda | Tutorial | Develop Pythonic spreadsheets running Python in and out of the grid | — |
| Jim Pivarski | — | Tutorial | Thinking in arrays | — |
| Joe Cheng | Posit | Speaker | Keeping LLMs in Their Lane: Focused AI for Data Science and Research | — |
| Joe Hamman | Earthmover | Tutorial | Hierarchical Data Analysis with Xarray DataTree & Zarr | — |
| John Kirkham | — | Tutorial | Reproducible Machine Learning Workflows for Scientists with pixi | — |
| Jon Mease | — | Tutorial | Vega-Altair: A Structured Way to Build Interactive Charts | — |
| Jonas Eschle | CERN | Speaker | zfit: scalable pythonic likelihood fitting | Slides |
| Jonathan Starr | — | Bof | AI for Scientific Discovery | — |
| Juanita Gomez | UC Santa Cruz | Bof | Towards Robust Security in Scientific Open Source Projects | — |
| Julie Barnum | LASP | Bof | Open-source science-specific Research Software Engineer Communities: benefits and lessons learned | — |
| Julie Hollek | — | Bof | Organizing Conferences in These Times | — |
| Julie Hollek | — | Bof | SciPy 2026 | — |
| Justus Magin | Laboratoire de l'Oceanographie Physique et Spatiale (LOPS) | Tutorial | Hierarchical Data Analysis with Xarray DataTree & Zarr | — |
| Justus Magin | Laboratoire de l'Oceanographie Physique et Spatiale (LOPS) | Speaker | Using Discrete Global Grid Systems in the Pangeo ecosystem | — |
| Justus Magin | Laboratoire de l'Oceanographie Physique et Spatiale (LOPS) | Speaker | The brave new world of slicing and dicing Xarray objects. | — |
| Katrina Riehl | NVIDIA | Bof | GPU Accelerated Python | — |
| Katrina Riehl | NVIDIA | Tutorial | The Accelerated Python Developer's Toolbox | — |
| Kedar Dabhadkar | Lam Research | Tutorial | Show your work: Tutorial on building and hosting web applications | — |
| Kevin Lee | NVIDIA | Tutorial | Bring Accelerated Computing to Data Science in Python | — |
| Kevin Lin | — | Bof | Generative AI in Education | — |
| Kyle Sunden | Matplotlib | Speaker | Dynamic Data with Matplotlib | — |
| Leah Wasser | pyOpenSci | Tutorial | Create Your First Python Package: Make Your Python Code Easier to Share and Use | — |
| Leah Wasser | pyOpenSci | Bof | Open Code, Open Science: What’s Getting in Your Way? | — |
| Leland McInnes | Tutte Institute for Mathematics and Computing | Speaker | DataMapPlot: Rich Tools for UMAP Visualizations | — |
| Leo Fang | NVIDIA | Speaker | CuPy: My Journey toward GPU-Accelerated Computing in Python | — |
| Lorena Barba | The George Washington University | Speaker | Embracing GenAI in Engineering Education: Lessons from the Trenches | — |
| Luigi Cruz | SETI Institute | Speaker | AI as a Detector: Lessons in Real Time Pulsar Discovery | — |
| Madicken | — | Bof | SciPy 2026 | — |
| Mark Wolfman | — | Speaker | Probing the Hidden World of Battery Chemistry With X-rays | — |
| Matt Haberland | Cal Poly | Speaker | SciPy’s New Infrastructure for Probability Distributions and Random Variables | — |
| Matthew Feickert | University of Washington | Tutorial | Reproducible Machine Learning Workflows for Scientists with pixi | — |
| Michael Chow | Posit | Speaker | User guides: engaging new users, delighting old ones | — |
| Michael Horrell | AlixPartners | Speaker | GBNet: Gradient Boosting packages integrated into PyTorch | — |
| Mihai Maruseac | Speaker | From Model to Trust: Building upon tamper-proof ML metadata records | — | |
| nate stemen | Unitary Foundation | Speaker | Noise-Resilient Quantum Computing with Python | — |
| Naty Clementi | NVIDIA | Speaker | Teaching Python with GPUs: Empowering educators to share knowledge that uses GPUs | — |
| Negin Sobhani | National Center for Atmospheric Research (NCAR) | Speaker | Scaling AI/ML Workflows on HPC for Geoscientific Applications. | — |
| Negin Sobhani | National Center for Atmospheric Research (NCAR) | Tutorial | Hierarchical Data Analysis with Xarray DataTree & Zarr | — |
| Nezar Abdennur | UMass Chan Medical School | Speaker | Accelerating Genomic Data Science and AI/ML with Composability | — |
| Noor Aftab | Amazon Web Services | Speaker | Unlocking the Missing 78%: Inclusive Communities for the Future of Scientific Python | — |
| Oleksandr Yardas | University of Illinois Urbana-Champaign | Speaker | Burning fuel for cheap! Transport-independent depletion in OpenMC | — |
| Pedro Garcia Lopez | Universitat Rovira i Virgili | Tutorial | Processing Cloud-optimized data in Python with Serverless Functions (Lithops, Dataplug) | — |
| Pedro Garcia Lopez | Universitat Rovira i Virgili | Speaker | Processing Cloud-optimized data in Python (Dataplug) | — |
| Peter Fackeldey | — | Tutorial | Thinking in arrays | — |
| Peter Sobolewski | The Jackson Laboratory | Tutorial | Scaling-up deep learning inference to large-scale bioimage data | — |
| Peter Sobolewski | The Jackson Laboratory | Tutorial | Create custom image visualization and analysis tools with napari | — |
| Quynh L. Nguyen | — | Speaker | Scaling NumPy for Large-Scale Science: The cuPyNumeric Approach | — |
| Raymond Hawkins | — | Speaker | ReSCU-Nets: recurrent U-Nets for segmentation of multidimensional microscopy data | — |
| Rodrigo Fernandez-Gonzalez | — | Speaker | ReSCU-Nets: recurrent U-Nets for segmentation of multidimensional microscopy data | — |
| Rowan Cockett | Curvenote | Speaker | Jupyter Book 2.0 – A Next-Generation tool for sharing for Computational Content | — |
| Rowan Cockett | Curvenote | Speaker | SciPy Proceedings: An Exemplar for Publishing Computational Open Science | — |
| Ruben Arts | — | Speaker | Reproducible Science Made Easy: Package Management with Pixi | — |
| Ruben Arts | — | Tutorial | Reproducible Machine Learning Workflows for Scientists with pixi | — |
| Ryan C Cooper | University of Connecticut | Speaker | Generative AI in Engineering Education: A Tool for Learning, Not a Replacement for Skills | — |
| Sanjiban Sengupta | CERN | Speaker | Challenges and Implementations for ML Inference in High-energy Physics | Slides |
| Sanket Verma | — | Speaker | Learning the art of fostering open-source communities | — |
| Sarah Kaiser | — | Speaker | Getting all your snakes in a grid: collaborating and teaching with Python in Excel and the Anaconda Toolbox | — |
| Sarah Kaiser | — | Tutorial | Develop Pythonic spreadsheets running Python in and out of the grid | — |
| Sarah Purpura | — | Speaker | From Legacy to Leading-Edge: Revamping NCEI Software for the Cloud Era | — |
| Scott Henderson | University of Washington | Speaker | The brave new world of slicing and dicing Xarray objects. | — |
| Scott Henderson | University of Washington | Tutorial | Hierarchical Data Analysis with Xarray DataTree & Zarr | — |
| Sean W. Freeman | University of Alabama in Huntsville | Speaker | tobac: Tracking Atmospheric Phenomena on Multiscale, Multivariate Diverse Datasets | — |
| Seher Karakuzu | Brookhaven National Laboratory | Speaker | Edge processing of X-ray ptychography: enabling real-time feedback for high-speed data acquisition | — |
| Shaurya Agarwal | PwC | Tutorial | The-Silmaril: Practice #ontology engineering with Python (and other languages). | — |
| Simon Adorf | — | Speaker | GPUs & ML – Beyond Deep Learning | — |
| Siu Kwan Lam | — | Speaker | Numba v2: Towards a SuperOptimizing Python Compiler | — |
| Siyu Qian | Capital One | Tutorial | Retrieval Augmented Generation (RAG) for LLMs | — |
| Stacy Irwin | Pacific Northwest National Laboratory | Speaker | Keeping Python Fun: Using Robotics Competitions to Teach Data Analysis and Application Development | — |
| Stefan Krawczyk | — | Tutorial | Building LLM-Powered Applications for Data Scientists and Software Engineers | — |
| Stefanie Molin | Bloomberg | Tutorial | (Pre-)Commit to Better Code | — |
| Stefanie Molin | Bloomberg | Tutorial | Introduction to Data Analysis Using Pandas | — |
| Steve Purves | — | Speaker | Jupyter Book 2.0 – A Next-Generation tool for sharing for Computational Content | — |
| Steve Van Tuyl | — | Bof | Real-world Impacts of Generative AI in the Research Software Engineer and Data Scientist Workplace | — |
| Subhosit Ray | Florida Atlantic University | Tutorial | A Hands-on Tutorial towards building Explainable Machine Learning using SHAP, GINI, LIME, and Permutation Importance | — |
| Sukhada Kulkarni | Capital One | Tutorial | Retrieval Augmented Generation (RAG) for LLMs | — |
| Tetsuo Koyama | — | Tutorial | Create Your First Python Package: Make Your Python Code Easier to Share and Use | — |
| Tetsuo Koyama | — | Bof | Open Code, Open Science: What’s Getting in Your Way? | — |
| Tetsuo Koyama | — | Tutorial | 3D Visualization with PyVista | — |
| Thomas J. Fan | Modal | Speaker | Dive into Flytekit's Internals: A Python SDK to Quickly Bring your Code Into Production | — |
| Tim Monko | University of Washington | Speaker | From the outside, in: How the napari community supports users and empowers transition to contribution | — |
| Tim Monko | University of Washington | Tutorial | Create custom image visualization and analysis tools with napari | — |
| Tina Odaka | Ifremer | Speaker | Using Discrete Global Grid Systems in the Pangeo ecosystem | — |
| Tom Nicholas | — | Speaker | Cubed: Scalable array processing with bounded-memory in Python | — |
| Tom Nicholas | — | Speaker | VirtualiZarr and Icechunk: How to build a cloud-optimised datacube of archival files in 3 lines of xarray | — |
| Tom Nicholas | — | Tutorial | Hierarchical Data Analysis with Xarray DataTree & Zarr | — |
| Tom White | — | Speaker | Cubed: Scalable array processing with bounded-memory in Python | — |
| Trevor Manz | — | Speaker | Accelerating Genomic Data Science and AI/ML with Composability | — |
| Tudor Garbulet | Oak Ridge National Laboratory | Speaker | Accelerating scientific data releases: Automated metadata generation with LLM agents | — |
| Vyas Ramasubramani | — | Speaker | Accelerated DataFrames for all: Bringing GPU acceleration to pandas and Polars | — |
| Wolf Vollprecht | — | Speaker | Reproducible Science Made Easy: Package Management with Pixi | — |
| Xinling Luo | Capital One | Tutorial | Retrieval Augmented Generation (RAG) for LLMs | — |
| Yuvi | — | Speaker | Towards a more sustainable and reliable mybinder.org | — |