Conferences / SciPy Conference (Scientific Computing with Python)
SciPy 2024
Jul 8–14, 2024 · Greater Tacoma Convention Center, Tacoma, WA, United States
- Conference
- SciPy Conference (Scientific Computing with Python) Data science & ML
- Dates
- Jul 8, 2024 – Jul 14, 2024
- Venue
- Greater Tacoma Convention Center
- Place
- Tacoma, WA, United States
- Format
- Hybrid
- Status
- Past
- Attendance
- —
- Website
- scipy2024.scipy.org
- Recorded
- 15 sponsors · 198 speaker appearances
- Notes
- 23rd annual SciPy; first edition in Tacoma. Virtual conference tickets offered. Tutorials July 8-9, conference July 10-12, sprints July 13-14 (University of Washington Tacoma). Speakers: all confirmed talks, tutorials and BoFs from the pretalx schedule; keynotes from the home page. Affiliations from pretalx bios only where stated. Final ti.to prices include a 3.9% processing fee.
Ticket prices
| Ticket | Price | Valid until | Notes | Source |
|---|---|---|---|---|
| Student tutorials only (early bird) | $300 | Apr 30, 2024 | Listed under 'Conference Tiers (Early Bird Pricing)'; 3.9% processing fee included in final price | web.archive.org |
| Student conference only (early bird) | $300 | Apr 30, 2024 | Listed under 'Conference Tiers (Early Bird Pricing)'; 3.9% processing fee included in final price | web.archive.org |
| Academic conference only (early bird) | $425 | Apr 30, 2024 | Listed under 'Conference Tiers (Early Bird Pricing)'; 3.9% processing fee included in final price | web.archive.org |
| Academic tutorials only (early bird) | $475 | Apr 30, 2024 | Listed under 'Conference Tiers (Early Bird Pricing)'; 3.9% processing fee included in final price | web.archive.org |
| Standard conference only (early bird) | $525 | Apr 30, 2024 | Listed under 'Conference Tiers (Early Bird Pricing)'; 3.9% processing fee included in final price | web.archive.org |
| Standard tutorials only (early bird) | $575 | Apr 30, 2024 | Listed under 'Conference Tiers (Early Bird Pricing)'; 3.9% processing fee included in final price | web.archive.org |
| Student conference & tutorials (early bird) | $600 | Apr 30, 2024 | Listed under 'Conference Tiers (Early Bird Pricing)'; 3.9% processing fee included in final price | web.archive.org |
| Academic conference & tutorials (early bird) | $900 | Apr 30, 2024 | Listed under 'Conference Tiers (Early Bird Pricing)'; 3.9% processing fee included in final price | web.archive.org |
| Standard conference & tutorials (early bird) | $1,100 | Apr 30, 2024 | Listed under 'Conference Tiers (Early Bird Pricing)'; 3.9% processing fee included in final price | web.archive.org |
| Teen Track (early bird) | $50 | — | scipy2024.scipy.org | |
| Teen Track (regular) | $75 | — | scipy2024.scipy.org | |
| Virtual conference only | $100 | — | Listed under 'Conference Tiers (Early Bird Pricing)'; 3.9% processing fee included in final price | web.archive.org |
Sponsors 15
Title / headline 1
- Enthought · Institutional Sponsor
Platinum 1
Gold 6
- Amazon Web Services
- Coiled
- Curvenote · Gold/Proceedings Sponsor
- Posit
- prefix.dev
- Streamlit · Gold/Social Event Sponsor
Silver 4
- Covalent · Silver/Tutorial Sponsor
- Databricks
- Quansight · Silver/Tutorial Sponsor
- USGS
Other 3
- Anaconda · Social Event Sponsor
- Microsoft · Social Event Sponsor
- University of Washington · Sprints Sponsor
Speakers and talks 198
| Speaker | Company | Role | Talk | Links |
|---|---|---|---|---|
| Elizabeth (Libby) Barnes | Colorado State University | Keynote | — | — |
| Julia Silge | Posit | Keynote | — | — |
| Kyle Cranmer | University of Washington | Keynote | — | — |
| Aakash Varambhia | Johnson Matthey | Speaker | Delivering state of the art imaging data science to aid research and development at Johnson Matthey | — |
| Adam Thompson | NVIDIA | Bof | Accelerated Python (Python on GPU) | — |
| Adam Thompson | NVIDIA | Speaker | Coming Online: Enabling Real-Time and AI-Ready Scientific Discovery | — |
| Akshay Gupta | Capital One | Speaker | Picking your battles: when is a compiled language like Rust beneficial for Data Scientists? | — |
| Alan Chalker | — | Bof | Open OnDemand: Providing easy access to scientific computing resources | — |
| Alex Monahan | MotherDuck | Speaker | How to bootstrap a Data Warehouse with DuckDB | — |
| Alex Monahan | MotherDuck | Tutorial | All the SQL a Pythonista needs to know: an introduction to SQL and DataFrames with DuckDB | — |
| Alexandre Chabot-Leclerc | — | Bof | SciPy 2025 | — |
| Ali Martz | Oregon State University | Speaker | Python for early-stage design of sustainable aviation fuels | — |
| Ana Comesana | — | Speaker | Python for early-stage design of sustainable aviation fuels | — |
| Anant Mittal | University of Washington | Tutorial | Generative AI Copilot for Scientific Software – a RAG-Based Approach using OLMo | — |
| Andrew Huang | — | Tutorial | From RAGs to riches: Build an AI document inquiry web-app | — |
| Andy Terrel | — | Bof | Accelerated Python (Python on GPU) | — |
| Anita Sarma | — | Speaker | [Diversity Keynote Luncheon] Empowering Open Source: Effective Mentoring Strategies for an Inclusive Community | — |
| Ankur Ankan | Radboud University | Speaker | Introduction to Causal Inference using pgmpy | — |
| Anshul Tambay | eScience Institute | Tutorial | Generative AI Copilot for Scientific Software – a RAG-Based Approach using OLMo | — |
| Anuj Sinha | University of Washington | Tutorial | Generative AI Copilot for Scientific Software – a RAG-Based Approach using OLMo | — |
| Bane Sullivan | — | Tutorial | 3D Visualization with PyVista | — |
| Beibin Li | Microsoft | Speaker | Building Multi-Agent Generative-AI Applications with AutoGen | — |
| Benoit Hamelin | — | Speaker | Vector space embeddings and data maps for cyber defense | — |
| Bill Little | UK Met Office | Tutorial | 3D Visualization with PyVista | — |
| Biola Adeyemi | — | Tutorial | Image analysis and visualization in Python with scikit-image, napari, and friends | — |
| Brandyn Lucca | Applied Physics Laboratory, University of Washington | Speaker | Echostack: A flexible and scalable open-source software suite for echosounder data processing | — |
| Braxton Cuneo | Seattle University | Speaker | Dante’s Externo: Injecting Python Functions into a Template-Driven CUDA C++ Framework | — |
| Brigitta Sipőcz | — | Bof | Community Feedback on the NumPy 2.0 Release | — |
| Brigitta Sipőcz | — | Bof | SciPy 2024 Sprint Prep BoF | — |
| Bryan Van de Ven | NVIDIA | Tutorial | Interactive data visualizations with Bokeh (in 2024) | — |
| C.A.M. Gerlach | — | Bof | What would you like to see in your scientific IDE? | — |
| C.A.M. Gerlach | — | Bof | Towards Robust Security in Scientific Open Source Projects | — |
| CaesarTuguinay | — | Speaker | Echostack: A flexible and scalable open-source software suite for echosounder data processing | — |
| Chi Wang | Microsoft | Speaker | Building Multi-Agent Generative-AI Applications with AutoGen | — |
| Christine Smit | NASA | Speaker | Free, public, standardized Zarr stores of geospatial data in the cloud for all! Now in Beta. | — |
| Christopher Davis | University of California, Irvine | Tutorial | Data Visualization with Vega-Altair | — |
| Cliff Kerr | Institute for Disease Modeling, Bill & Melinda Gates Foundation | Speaker | Starsim: A flexible framework for agent-based modeling of health and disease | — |
| Connor Stone | Université de Montréal | Speaker | Development of AstroPhot: Fitting Everything Everywhere all at Once in Astronomical Images | — |
| Cordero Core | — | Tutorial | Generative AI Copilot for Scientific Software – a RAG-Based Approach using OLMo | — |
| Dan Schult | Colgate University | Speaker | Sparse arrays in scipy.sparse | — |
| Darren Vengroff | — | Speaker | An Introduction to Impact Charts | — |
| Darren Vengroff | — | Tutorial | Working with U.S. Census Data in Python: Discovery, Analysis, and Visualization | — |
| Dewey Dunnington | Voltron Data | Speaker | Introducing nanoarrow: the world's tiniest Arrow Implementation | — |
| Dharhas Pothina | Quansight | Tutorial | Data of an Unusual Size (2024 edition): A practical guide to analysis and interactive visualization of massive datasets | — |
| Dharhas Pothina | Quansight | Tutorial | From RAGs to riches: Build an AI document inquiry web-app | — |
| Dhavide Aruliah | — | Tutorial | Determining Climate Risks with NASA Earthdata Cloud | — |
| Diego Kiedanski | — | Tutorial | A hands-on forecasting guide: from theory to practice | — |
| Dingrui Lei | — | Speaker | Echostack: A flexible and scalable open-source software suite for echosounder data processing | — |
| Don Setiawan | University of Washington | Speaker | Echostack: A flexible and scalable open-source software suite for echosounder data processing | — |
| Don Setiawan | University of Washington | Tutorial | Xarray: Friendly, Interactive, and Scalable Scientific Data Analysis | — |
| Don Setiawan | University of Washington | Tutorial | Generative AI Copilot for Scientific Software – a RAG-Based Approach using OLMo | — |
| Doris Lee | Snowflake | Speaker | Scaling your data science workflows with Modin | — |
| Elena Felder | MotherDuck | Tutorial | All the SQL a Pythonista needs to know: an introduction to SQL and DataFrames with DuckDB | — |
| eli knaap | San Diego State University | Speaker | geosnap: The Geospatial Neighborhood Analysis Package | — |
| Elizabeth Barnes | Colorado State University | Speaker | Keynote: Explainable AI for Climate Science: Opening the black box to reveal planet earth | — |
| Emily Dorne | DrivenData | Speaker | Using Satellite Imagery to Identify Harmful Algal Blooms and Protect Public Health | — |
| Eniola Awowale | NASA | Speaker | Simplifying analysis of hierarchical HDF5 and NetCDF4 files with xarray-datatree | — |
| Eric Heiden | NVIDIA | Bof | Accelerated Python (Python on GPU) | — |
| Eric Heiden | NVIDIA | Speaker | Warp: Advancing Simulation AI with Differentiable GPU Computing in Python | — |
| Eric Ma | Moderna | Speaker | LlamaBot: a Pythonic interface to Large Language Models | — |
| Eric Ma | Moderna | Speaker | How to foster an open source culture within your data science team | — |
| Erick Martins Ratamero | The Jackson Laboratory | Tutorial | Image analysis and visualization in Python with scikit-image, napari, and friends | — |
| Erick Martins Ratamero | The Jackson Laboratory | Speaker | Expanding the OME ecosystem for imaging data management | — |
| Franz Kiraly | — | Tutorial | Enhancing Predictive Analytics with tsbootstrap and sktime | — |
| Fritz Lekschas | Ozette Technologies | Tutorial | Bring your __repr__’s to life with anywidget | — |
| Gil Forsyth | Voltron Data | Speaker | Ibis: because SQL is everywhere and so is Python | — |
| Gil Forsyth | Voltron Data | Tutorial | Intro to Ibis: blazing fast analytics with DuckDB, Polars, Snowflake, and more, from the comfort of your Python repl. | — |
| Giordon Stark | — | Speaker | How the Scientific Python ecosystem helps answering fundamental questions of the Universe | — |
| Gordon Watts | University of Washington | Tutorial | Thinking In Arrays | — |
| Gordon Watts | University of Washington | Speaker | How the Scientific Python ecosystem helps answering fundamental questions of the Universe | — |
| Guen Prawiroatmodjo | MotherDuck | Speaker | How to bootstrap a Data Warehouse with DuckDB | — |
| Guen Prawiroatmodjo | MotherDuck | Tutorial | All the SQL a Pythonista needs to know: an introduction to SQL and DataFrames with DuckDB | — |
| Hajime Takeda | MIKI HOUSE Americas | Speaker | Introduction to Causal Inference with Machine Learning | — |
| Heinrich Peters | — | Speaker | Model Share AI: An Integrated Toolkit for Collaborative Machine Learning Model Development, Provenance Tracking, and Deployment in Python | — |
| Henry Fredrick Schreiner III | — | Speaker | Scikit-build-core: A modern build-backend for CPython C/C++/Fortran/Cython extensions. | — |
| Ian Spektor | Tryolabs | Tutorial | A hands-on forecasting guide: from theory to practice | — |
| Ian Spektor | Tryolabs | Speaker | Safe, fast, and easy time series preprocessing with Temporian | — |
| Irfan Alibay | Open Free Energy | Speaker | Towards MDAnalysis 3.0: a fast, interoperable, and extensible community-driven ecosystem for handling molecular simulation data | — |
| Isabel Zimmerman | Posit | Tutorial | Create Your First Pure Python Package: Make Your Python Code Easier to Share and Use | — |
| Isabel Zimmerman | Posit | Speaker | From Code to Clarity: Using Quarto for Python Documentation | — |
| Ishika Khandelwal | University of Washington | Tutorial | Generative AI Copilot for Scientific Software – a RAG-Based Approach using OLMo | — |
| Jacob Smith | Oak Ridge National Laboratory | Speaker | Supporting Greater Interactivity in the IPython Visualization Ecosystem | — |
| James A. Bednar | Anaconda | Tutorial | hvPlot and Panel: Easy data visualization, data exploration, and data apps | — |
| James Bourbeau | Coiled | Speaker | Pandas + Dask DataFrame 2.0 - Comparison to Spark, DuckDB and Polars | — |
| James Lamb | — | Bof | SciPy 2024 Sprint Prep BoF | — |
| Jaswant Panchumarti | Kitware | Tutorial | 3D Visualization with PyVista | — |
| Jay Chia | Eventual | Speaker | Building Daft: Python + Rust = a better distributed query engine | — |
| Jean-Christophe Fillion-Robin | Kitware | Speaker | Scikit-build-core: A modern build-backend for CPython C/C++/Fortran/Cython extensions. | — |
| Jean-Christophe Fillion-Robin | Kitware | Speaker | ITK-Wasm: Universal spatial analysis and visualization | — |
| Jeremiah Paige | — | Tutorial | Create Your First Pure Python Package: Make Your Python Code Easier to Share and Use | — |
| Jeremy Tanner | — | Bof | Accelerated Python (Python on GPU) | — |
| Jessica Scheick | — | Tutorial | Xarray: Friendly, Interactive, and Scalable Scientific Data Analysis | — |
| Jim Crist-Harif | — | Tutorial | Intro to Ibis: blazing fast analytics with DuckDB, Polars, Snowflake, and more, from the comfort of your Python repl. | — |
| Joanna Piper Morgan | Oregon State University | Speaker | Monte Carlo/Dynamic Code: Performant and Portable High-Performance Computing at Scale via Python and Numba | — |
| Jon Mease | — | Tutorial | Data Visualization with Vega-Altair | — |
| Jonathan Starr | — | Bof | Defining Valuable Data for Mapping Open Source Science | — |
| Jordão Bragantini | — | Tutorial | Image analysis and visualization in Python with scikit-image, napari, and friends | — |
| Jordão Bragantini | — | Speaker | ultrack: large-scale versatile cell tracking in Python under segmentation uncertainty | — |
| Jorge Paz Soldan Palma | University of South Carolina | Speaker | Uncertainty quantification and propagation of the NaCl-KCl-MgCl2 pseudoternary system for molten salt application | — |
| Josh Borrow | University of Washington | Speaker | Making Research Data Flow with Python | — |
| Joshua Taillon | NIST | Speaker | HyperSpy – Your Multidimensional Data Analysis Toolbox | — |
| Juan Cabanela | — | Tutorial | Building Complex Web Apps with Jupyter Widgets | — |
| Juanita Gomez | — | Bof | Scientific Python Ecosystem Coordination | — |
| Juanita Gomez | — | Bof | Towards Robust Security in Scientific Open Source Projects | — |
| Julia Silge | Posit | Speaker | Keynote: The Right Tool for the Job | — |
| Julie Hollek | — | Bof | SciPy 2025 | — |
| Justin Braaten | Speaker | Bridging the gap between Earth Engine and the Scientific Python Ecosystem | — | |
| Karthik Venkataramani | University of Washington | Tutorial | Determining Climate Risks with NASA Earthdata Cloud | — |
| Katrina Riehl | — | Bof | Accelerated Python (Python on GPU) | — |
| Kevin Lacaille | Spexi Geospatial | Tutorial | Hobby Drones, Urban Forests: A Geospatial Journey to Greener Cities | — |
| Kevin Lin | — | Bof | Generative AI in Education | — |
| Kyle Barron | Development Seed | Speaker | Lonboard: Fast, interactive geospatial vector data visualization in Jupyter | — |
| Kyle Cranmer | University of Washington | Speaker | Keynote: Particles, People, and Pull Requests | — |
| Kyle Niemeyer | — | Speaker | Monte Carlo/Dynamic Code: Performant and Portable High-Performance Computing at Scale via Python and Numba | — |
| Kyle Niemeyer | — | Speaker | Python for early-stage design of sustainable aviation fuels | — |
| Lars Grüter | — | Tutorial | Image analysis and visualization in Python with scikit-image, napari, and friends | — |
| Leah Wasser | pyOpenSci | Speaker | The power of community in solving scientific Python’s most challenging problems | — |
| Leah Wasser | pyOpenSci | Tutorial | Create Your First Pure Python Package: Make Your Python Code Easier to Share and Use | — |
| Leo Fang | NVIDIA | Bof | Accelerated Python (Python on GPU) | — |
| Lucas Sterzinger | — | Speaker | Simplifying analysis of hierarchical HDF5 and NetCDF4 files with xarray-datatree | — |
| Luigi Cruz | SETI Institute | Speaker | Coming Online: Enabling Real-Time and AI-Ready Scientific Discovery | — |
| Luis Lopez | National Snow and Ice Data Center (NSIDC) | Tutorial | Xarray: Friendly, Interactive, and Scalable Scientific Data Analysis | — |
| Maarten Breddels | Widgetti | Tutorial | Building Complex Web Apps with Jupyter Widgets | — |
| Madhav Kashyap | University of Washington | Tutorial | Generative AI Copilot for Scientific Software – a RAG-Based Approach using OLMo | — |
| Madicken | — | Bof | Supporting free-threaded Python | — |
| Mathieu Guillame-Bert | Tutorial | A hands-on forecasting guide: from theory to practice | — | |
| Mathieu Guillame-Bert | Speaker | Safe, fast, and easy time series preprocessing with Temporian | — | |
| Matt Craig | — | Tutorial | Building Complex Web Apps with Jupyter Widgets | — |
| Matt McCormick | Kitware | Speaker | ITK-Wasm: Universal spatial analysis and visualization | — |
| Matthew Feickert | University of Washington | Speaker | How the Scientific Python ecosystem helps answering fundamental questions of the Universe | — |
| Matthew Rocklin | — | Speaker | Dask in Production | — |
| Max Jones | — | Tutorial | Xarray: Friendly, Interactive, and Scalable Scientific Data Analysis | — |
| Mehdi Ouazza | — | Tutorial | All the SQL a Pythonista needs to know: an introduction to SQL and DataFrames with DuckDB | — |
| Mine Çetinkaya-Rundel | Duke University | Tutorial | Unlocking Dynamic Reproducible Documents: A Quarto Tutorial for Scientific Communication | — |
| Nathan Goldbaum | Quansight | Bof | Supporting free-threaded Python | — |
| Nathan Goldbaum | Quansight | Speaker | My NumPy year: From no CPython C API experience to shipping a new DType in NumPy 2.0 | — |
| Nathan Goldbaum | Quansight | Bof | Community Feedback on the NumPy 2.0 Release | — |
| Nathan Martindale | Oak Ridge National Laboratory | Speaker | Supporting Greater Interactivity in the IPython Visualization Ecosystem | — |
| Naty Clementi | Voltron Data | Speaker | Ibis + DuckDB geospatial: a match made on Earth | — |
| Naty Clementi | Voltron Data | Tutorial | Intro to Ibis: blazing fast analytics with DuckDB, Polars, Snowflake, and more, from the comfort of your Python repl. | — |
| Negin Sobhani | — | Tutorial | Xarray: Friendly, Interactive, and Scalable Scientific Data Analysis | — |
| Nezar Abdennur | UMass Chan Medical School | Tutorial | Bring your __repr__’s to life with anywidget | — |
| Nicholas Ursa | MotherDuck | Speaker | How to bootstrap a Data Warehouse with DuckDB | — |
| Nick Lenssen | — | Speaker | Simplifying analysis of hierarchical HDF5 and NetCDF4 files with xarray-datatree | — |
| Nick Terrel | University of Washington | Speaker | Atomistic uncertainty driven data generation in ANI neural network potentials | — |
| Nicole Brewer | Arizona State University | Tutorial | Building Complex Web Apps with Jupyter Widgets | — |
| Niki Burggraf | eScience Institute | Tutorial | Generative AI Copilot for Scientific Software – a RAG-Based Approach using OLMo | — |
| Ondřej Čertík | Microsoft | Speaker | LPython: Novel, Fast, Retargetable Python Compiler | — |
| Pamela Fox | — | Bof | Scientific Computing in the Cloud | — |
| Patricia A. Loto | Metadocencia | Tutorial | Determining Climate Risks with NASA Earthdata Cloud | — |
| Pavithra Eswaramoorthy | Quansight | Tutorial | From RAGs to riches: Build an AI document inquiry web-app | — |
| Pavithra Eswaramoorthy | Quansight | Tutorial | Interactive data visualizations with Bokeh (in 2024) | — |
| Pavithra Eswaramoorthy | Quansight | Tutorial | Data of an Unusual Size (2024 edition): A practical guide to analysis and interactive visualization of massive datasets | — |
| Pawan Negi | Illinois Institute of Technology | Tutorial | Automate your research with automan | — |
| Peter Sun | Cornell University | Speaker | mrfmsim: a modular simulation platform for magnetic resonance force microscopy experiments | — |
| Phillip Cloud | Voltron Data | Tutorial | Intro to Ibis: blazing fast analytics with DuckDB, Polars, Snowflake, and more, from the comfort of your Python repl. | — |
| Pierre Raybaut | — | Speaker | From Spyder to DataLab: 15 years of scientific software crafting in Python | — |
| Prabhu Ramachandran | IIT Bombay | Tutorial | Automate your research with automan | — |
| Pryce Turner | Union.ai | Speaker | Orchestrating Bioinformatics Workflows Across a Heterogeneous Toolset with Flyte | — |
| Qiusheng Wu | University of Tennessee, Knoxville | Speaker | SAMGeo: Automated Segmentation of Remote Sensing Imagery with the Segment Anything Model | — |
| Qiusheng Wu | University of Tennessee, Knoxville | Speaker | Bridging the gap between Earth Engine and the Scientific Python Ecosystem | — |
| Quinn Brencher | University of Washington | Tutorial | Github Actions for Scientific Data Workflows | — |
| Reka Horvath | — | Tutorial | Cookiecutter: Project Templates and Much More | — |
| Richard Iannone | — | Speaker | Great Tables for Everyone | — |
| Rick Ratzel | — | Speaker | No-Code-Change GPU Acceleration for Your Pandas and NetworkX Workflows | — |
| Rohit Ganguly | — | Bof | Scientific Computing in the Cloud | — |
| Ryan C Cooper | University of Connecticut | Speaker | Teaching and Learning Scientific Computing in the age of ChatGPT | — |
| Samapriya Roy | Maxar | Speaker | Bridging the gap between Earth Engine and the Scientific Python Ecosystem | — |
| Sankalp Gilda | — | Tutorial | Enhancing Predictive Analytics with tsbootstrap and sktime | — |
| Santiago Soler | UBC | Speaker | Pooch: a friend to fetch your data files | — |
| Sarah Kaiser | — | Bof | Scientific Computing in the Cloud | — |
| Scott Henderson | University of Washington | Tutorial | Xarray: Friendly, Interactive, and Scalable Scientific Data Analysis | — |
| Sean Law | — | Speaker | STUMPY: Modern Time Series Analysis with Matrix Profiles | — |
| Sebastian Benthall | Econ-ARK | Speaker | New Developments in Open Source Computational Economics | — |
| Sebastian Raschka | — | Tutorial | Pretraining and Finetuning LLMs from the Ground Up | — |
| Soham Kishor Butala | University of Washington | Speaker | Echostack: A flexible and scalable open-source software suite for echosounder data processing | — |
| Stanley Seibert | Anaconda | Speaker | PIXIE: Blending Just-in-time and Ahead-of-time compilation in scientific Python applications | — |
| Stéfan van der Walt | — | Tutorial | Image analysis and visualization in Python with scikit-image, napari, and friends | — |
| Stéfan van der Walt | — | Bof | Scientific Python Ecosystem Coordination | — |
| Stuart Archibald | — | Speaker | PIXIE: Blending Just-in-time and Ahead-of-time compilation in scientific Python applications | — |
| Tetsuo Koyama | — | Tutorial | 3D Visualization with PyVista | — |
| Tim Diller | — | Tutorial | A Practical Introduction to NumPy | — |
| Timo Metzger | makepath | Tutorial | Interactive data visualizations with Bokeh (in 2024) | — |
| Tom Nicholas | [C]Worthy | Speaker | Simplifying analysis of hierarchical HDF5 and NetCDF4 files with xarray-datatree | — |
| Tom Nicholas | [C]Worthy | Tutorial | Xarray: Friendly, Interactive, and Scalable Scientific Data Analysis | — |
| Tom Vo | LLNL | Speaker | xCDAT (Xarray Climate Data Analysis Tools): A Python package for simple climate data analysis on structured grids | — |
| Trevor Manz | Harvard University | Speaker | anywidget: custom Jupyter Widgets made easy | — |
| Trevor Manz | Harvard University | Tutorial | Bring your __repr__’s to life with anywidget | — |
| Valentina Staneva | eScience Institute | Speaker | Echostack: A flexible and scalable open-source software suite for echosounder data processing | — |
| Valentina Staneva | eScience Institute | Tutorial | Github Actions for Scientific Data Workflows | — |
| Vangelis Kourlitis | Technical University of Munich | Speaker | How the Scientific Python ecosystem helps answering fundamental questions of the Universe | — |
| Vangelis Kourlitis | Technical University of Munich | Tutorial | Thinking In Arrays | — |
| Vani Mandava | eScience Institute | Tutorial | Generative AI Copilot for Scientific Software – a RAG-Based Approach using OLMo | — |
| Vi Rapp | — | Speaker | Python for early-stage design of sustainable aviation fuels | — |
| Vyas Ramasubramani | — | Speaker | No-Code-Change GPU Acceleration for Your Pandas and NetworkX Workflows | — |
| Wietze Suijker | Space Intelligence | Tutorial | Xarray: Friendly, Interactive, and Scalable Scientific Data Analysis | — |
| Wu-Jung Lee | Applied Physics Laboratory, University of Washington | Speaker | Echostack: A flexible and scalable open-source software suite for echosounder data processing | — |
| Zac Hatfield-Dodds | Anthropic | Tutorial | Introduction to Property-Based Testing | — |