Conferences / SciPy Conference (Scientific Computing with Python)
SciPy 2022
Jul 11–17, 2022 · AT&T Hotel & Conference Center, University of Texas, Austin, TX, United States
- Conference
- SciPy Conference (Scientific Computing with Python) Data science & ML
- Dates
- Jul 11, 2022 – Jul 17, 2022
- Venue
- AT&T Hotel & Conference Center, University of Texas
- Place
- Austin, TX, United States
- Format
- Hybrid
- Status
- Past
- Attendance
- —In-person Standard, Academic and Student tutorial and conference tickets all shown as SOLD OUT on the Attend page; no headcount published.
- Website
- scipy2022.scipy.org
- Recorded
- 21 sponsors · 143 speaker appearances
- Notes
- 21st annual SciPy; first in-person edition since 2019, with a virtual (livestream) option. Tutorials July 11-12, conference July 13-15, sprints July 16-17. Speakers from the official schedule (schedule2021.scipy.org/2022/); affiliations only where the site's speaker directory states one. In-person prices not recoverable (tables showed SOLD OUT). Videos on the Enthought YouTube channel.
Ticket prices
| Ticket | Price | Valid until | Notes | Source |
|---|---|---|---|---|
| Virtual (conference livestream) | $100 | — | In-person tiers shown as SOLD OUT | jim5090.wixsite.com |
Sponsors 21
Title / headline 1
- Enthought · Institutional Sponsor
Platinum 2
Community 1
- Packt · Community Sponsor
Other 2
- Chan Zuckerberg Initiative · Sprints Sponsor
- Kitware · Sprints Sponsor
Speakers and talks 143
| Speaker | Company | Role | Talk | Links |
|---|---|---|---|---|
| Ben Blaiszik | University of Chicago | Keynote | Software and Services to Fully Realize the Impact of AI, Machine Learning, Automation, and Community Engagement in Science | — |
| Enzo Ferrante | CONICET | Keynote | Fairness of Machine Learning in Medical Image Analysis | — |
| Megan Sosey | Space Telescope Science Institute | Keynote | Python’s Contribution to Astronomy and Major Space Telescope Missions | — |
| Peter Kalmus | NASA | Keynote | SciPy in Climate Science | — |
| Aaron Meurer | — | Speaker | SymPy | — |
| Adam Symington | Geollect | Tutorial | Creating Beautiful Geospatial Data Visualisations with Python | — |
| Alex Bozarth | IBM | Tutorial | Developing Extensions for JupyterLab | — |
| Alex Chabot-Leclerc | — | Bof | SciPy 2023 planning BoF | — |
| Alexander Kaszynski | Ansys | Tutorial | PyVista Tutorial | — |
| Alexy Khrabrov | — | Speaker | Accelerating Science with the Generative Toolkit for Scientific Discovery (GT4SD) | — |
| Allan Campopiano | Deepnote | Speaker | The Myth of the Normal Curve and What to Do About It | — |
| Anderson Banihirwe | CarbonPlan | Tutorial | Xarray: Friendly, Interactive, and Scalable Scientific Data Analysis | — |
| Anna Haensch | — | Speaker | Python for Global Applications: teaching scientific Python in context to law and diplomacy students | — |
| Antonio Cuni | — | Speaker | HPy: Where next? | — |
| Axel Donath | — | Speaker | Pylira: deconvolution of images in the presence of Poisson noise | — |
| Bane Sullivan | — | Tutorial | PyVista Tutorial | — |
| Bhupendra Raut | — | Speaker | Tobac: a flexible framework for detection, tracking and lagrangian analysis in atmospheric and oceanic data | — |
| Brad Rees | — | Speaker | GPU Accelerated Graph Analysis in Python using cuGraph | — |
| Chanel Richardson | — | Speaker | Using Python to protect voting rights | — |
| Charles Blackmon-Luca | — | Speaker | Accelerating ETL/SQL workloads with RAPIDS-Dask + Dask-SQL | — |
| Chris Sewell | — | Speaker | AiiDA common workflows for computing material properties using different quantum engines | — |
| Cliff Kerr | Bill and Melinda Gates Foundation | Speaker | Python vs. the pandemic: a case study in high-stakes software development | — |
| David Nicholson | — | Speaker | (Re)Introducing the US Research Software Engineers Association to SciPy | — |
| David Nicholson | — | Speaker | Virtual vs In-person Settings and their Impact on Diversity and Inclusion | — |
| Davina Zamanzadeh | UCLA | Speaker | pyampute: a Python library for data amputation | — |
| Deepak Cherian | National Center for Atmospheric Research (NCAR) | Tutorial | Xarray: Friendly, Interactive, and Scalable Scientific Data Analysis | — |
| Draga Doncila Pop | Monash University | Tutorial | Interactive image analysis with napari | — |
| Eduardo Blancas | Ploomber | Tutorial | Ploomber: Developing Maintainable and Reproducible Data Pipelines Interactively From Jupyter, VSCode, and PyCharm | — |
| Elijah Knaap | Center for Geospatial Sciences @ UC-Riverside | Tutorial | Spatial and Urban Data Science with PySAL | — |
| Emma Marshall | — | Tutorial | Xarray: Friendly, Interactive, and Scalable Scientific Data Analysis | — |
| Eric Ma | — | Tutorial | Bayesian Data Science by Simulation | — |
| Eric Ma | — | Tutorial | Network Analysis Made Simple | — |
| Gabe Schoenbach | — | Speaker | Using Python to protect voting rights | — |
| Haw-Minn Lu | West Health Institute | Tutorial | Understanding Missing Data and How to Deal with it | — |
| Henry Schreiner | — | Speaker | Awkward Packaging: building Scikit-HEP | — |
| Hugo Bowne-Anderson | Outerbounds | Tutorial | Bayesian Data Science by Simulation | — |
| Hugo Bowne-Anderson | Outerbounds | Tutorial | Full-stack Machine Learning for Data Scientists | — |
| Ian Hunt-Isaak | — | Tutorial | The Jupyter Interactive Widget Ecosystem | — |
| Ido Michael | Ploomber | Tutorial | Ploomber: Developing Maintainable and Reproducible Data Pipelines Interactively From Jupyter, VSCode, and PyCharm | — |
| Itay Dafna | Bloomberg | Tutorial | The Jupyter Interactive Widget Ecosystem | — |
| Jackson Morgan | — | Speaker | Analysis of Python Development Schemes for Monte Carlo Neutronics on High Performance Computing | — |
| Jacob Tomlinson | NVIDIA | Tutorial | GPU development with Python 101 | — |
| Jacob Tomlinson | NVIDIA | Tutorial | Dask Tutorial: Scaling the PyData Ecosystem | — |
| James A. Bednar | — | Speaker | Python Data Visualization, 2022 | — |
| James Bednar | Anaconda | Tutorial | hvPlot and HoloViz: Visualize all your data easily, from notebooks to dashboards | — |
| James Lamb | SpotHero | Speaker | Does that CSV need to be on PyPI? Probably not. | — |
| Jan Janssen | — | Speaker | pyiron – an integrated development environment (IDE) for scientific workflows | — |
| Janos Gabler | University of Bonn | Tutorial | Practical numerical optimization with scipy, estimagic and jaxopt | — |
| Jarrod Millman | — | Speaker | Scientific Python Community Outreach | — |
| Jarrod Millman | — | Speaker | Scientific Python Ecosystem Coordination | — |
| Jason Chambless | KBI Biopharma | Tutorial | Sharing your scientific tools: from a script to a desktop application | — |
| Jean-Luc Stevens | — | Tutorial | hvPlot and HoloViz: Visualize all your data easily, from notebooks to dashboards | — |
| Jennifer Glick | IBM | Tutorial | Introduction to the Qiskit Runtime, A Platform for Efficient Quantum-Classical Computation | — |
| Jessica Scheick | University of New Hampshire | Tutorial | Xarray: Friendly, Interactive, and Scalable Scientific Data Analysis | — |
| Jessie Yu | — | Tutorial | Introduction to the Qiskit Runtime, A Platform for Efficient Quantum-Classical Computation | — |
| Jim Crist-Harif | — | Speaker | Dask User's Round-table | — |
| Jim Pivarski | Princeton University | Tutorial | Loopy and unloopy programming techniques | — |
| Jinzhe Zeng | — | Speaker | DeePMD-kit: A powerful, efficient, user-friendly, flexible, and free platform for Deep Potential models | — |
| Jon Guyer | — | Bof | SciPy 2023 planning BoF | — |
| Jonathan Rocher | KBI Biopharma | Tutorial | Sharing your scientific tools: from a script to a desktop application | — |
| Juan Luis Cano Rodríguez | poliastro | Speaker | Per Python ad astra: interactive Astrodynamics with poliastro | — |
| Juanita Gomez | Scientific Python | Speaker | Scientific Python Community Outreach | — |
| Juanita Gomez | Scientific Python | Speaker | Scientific Python—From GitHub to TikTok | — |
| Julia Signell | Saturn Cloud | Tutorial | Dask Tutorial: Scaling the PyData Ecosystem | — |
| Julius Busecke | Columbia University | Speaker | Cutting Edge Climate Science in the Cloud with Pangeo | — |
| Julius Busecke (he/him) | — | Speaker | Enabling petabyte-scale ocean data analytics on staggered grids through the grid ufunc protocol in xGCM | — |
| Jun | — | Speaker | An Introduction to Distributed Hybrid Hyperparameter Optimization | — |
| Karin Knudson | — | Speaker | Using Python to protect voting rights | — |
| Karin Knudson | — | Speaker | Python for Global Applications: teaching scientific Python in context to law and diplomacy students | — |
| Kate Hertweck | — | Speaker | Building belonging in open source and open science | — |
| Kate Huddleston | — | Speaker | ANI-AIM: The Use of Machine Learning in Computational Chemistry | — |
| Kevin Kho | Prefect | Speaker | Introduction to Workflow Orchestration with Prefect | — |
| Kevin Lacaille | Planet | Tutorial | Eroding Coastlines: A Geospatial & Computer Vision Analysis | — |
| Kevin Tyle | — | Speaker | Project Pythia: A Community-built Training Resource for the Geoscientific Python Software Ecosystem | — |
| Kevin Yamauchi | ETH Zurich | Tutorial | Interactive image analysis with napari | — |
| Kim Pevey | — | Panelist | Pragmatic Panel: Build and Deploy Complex Data-Driven WebApps | — |
| Logan Thomas | Enthought | Tutorial | Introduction to Numerical Computing With NumPy | — |
| Luigi F. Cruz | — | Speaker | Real-Time Digital Signal Processing with SciPy Signal: Simultaneous Demodulation of Multiple FM Stations | — |
| Mansi Shah | Planet | Tutorial | Eroding Coastlines: A Geospatial & Computer Vision Analysis | — |
| Mariana Meireles | NumFOCUS | Tutorial | The Jupyter Interactive Widget Ecosystem | — |
| Martha Cryan | IBM | Tutorial | Developing Extensions for JupyterLab | — |
| Mason Egger | — | Speaker | An Introduction to Synthetic Data | — |
| Matt McCormick | — | Tutorial | Pythonic 3D visualization | — |
| Matt Thompson | — | Speaker | Infrastructure at Open Force Field: Creating a software stack for end-to-end force field development | — |
| Matthew Craig | Minnesota State University Moorhead | Tutorial | The Jupyter Interactive Widget Ecosystem | — |
| Matthew Petroff | — | Speaker | Development of Accessible, Aesthetically-Pleasing Color Sequences | — |
| Matthias Bussonnier | — | Speaker | Papyri: Better Documentation for the Scientific Ecosystem in Jupyter | — |
| Max Jones | — | Speaker | Geospatial analysis and visualization with PyGMT | — |
| Maxime Liquet | — | Tutorial | hvPlot and HoloViz: Visualize all your data easily, from notebooks to dashboards | — |
| May Ireland | — | Speaker | Communicating effectively online | — |
| Melissa Mendonça | — | Speaker | DEI: beyond the basics | — |
| Michael Zargham | — | Speaker | Scientific Computing and Web3 | — |
| Miranda Mundt | — | Speaker | (Re)Introducing the US Research Software Engineers Association to SciPy | — |
| Mridul Seth | — | Tutorial | Network Analysis Made Simple | — |
| Nadia Dencheva | — | Tutorial | Using the Advanced Science Data Format (ASDF) in Python | — |
| Natalia Clementi | — | Tutorial | Dask Tutorial: Scaling the PyData Ecosystem | — |
| Naty Clementi | Coiled | Speaker | Dask User's Round-table | — |
| Niels Bantilan | Union.ai | Speaker | Reliable, Reproducible, Recoverable, and Auditable Machine Learning for Production Workloads with Flyte | — |
| niklas nolte | — | Speaker | PyConf: A Framework for Reliable and Efficient Configuration of Complex Workflows | — |
| Orhan Eroglu | National Center for Atmospheric Research (NCAR) | Speaker | The Geoscience Community Analysis Toolkit: An Open Development, Community Driven Toolkit in the Scientific Python Ecosystem | — |
| Paige Martin | — | Speaker | Pangeo Community Gathering | — |
| Pamphile Roy | Quansight | Speaker | Scientific Python Ecosystem Coordination | — |
| Pamphile Roy | Quansight | Speaker | Improving random sampling in Python: scipy.stats.sampling and scipy.stats.qmc | — |
| Paul Anzel | — | Speaker | How do you test data workflows | — |
| Paul Anzel | — | Speaker | To PhD or not to PhD | — |
| Perry Greenfield | STScI | Speaker | The Advanced Scientific Data Format (ASDF): An Update | — |
| Perry Greenfield | STScI | Tutorial | Using the Advanced Science Data Format (ASDF) in Python | — |
| Philipp Rudiger | — | Tutorial | hvPlot and HoloViz: Visualize all your data easily, from notebooks to dashboards | — |
| Philipp Schiele | Ludwig Maximilian University of Munich | Tutorial | Convex optimization using CVXPY | — |
| Piyush Jain | — | Tutorial | Developing Extensions for JupyterLab | — |
| Prabhu Ramachandran | Indian Institute of Technology Bombay | Tutorial | Pythonic 3D visualization | — |
| Prabhu Ramachandran | Indian Institute of Technology Bombay | Tutorial | Sharing your scientific tools: from a script to a desktop application | — |
| Prabhu Ramchandran | — | Speaker | The (surprising) road to reproducibility: automation! | — |
| Qiming Sun | — | Speaker | PySCF: the Python-based Simulations of Chemistry Framework | — |
| Riley Murray | CVXPY | Tutorial | Convex optimization using CVXPY | — |
| Robert Jackson | — | Speaker | Tobac: a flexible framework for detection, tracking and lagrangian analysis in atmospheric and oceanic data | — |
| Roni Kobrosly | DrFirst | Tutorial | Introduction to Causal Modeling | — |
| Ryan Abernathey | — | Speaker | Pangeo Forge: Crowdsourcing Open Data in the Cloud | — |
| Ryan Abernathey | — | Speaker | Pangeo Community Gathering | — |
| Savin Goyal | Outerbounds | Tutorial | Full-stack Machine Learning for Data Scientists | — |
| Savin Goyal | Outerbounds | Speaker | Human-Friendly, Production-Ready Data Science with Metaflow | — |
| Scott Henderson | University of Washington | Tutorial | Xarray: Friendly, Interactive, and Scalable Scientific Data Analysis | — |
| Scott Shambaugh | Capella Space | Speaker | Monaco: Quantify Uncertainty and Sensitivities in Your Computational Models with a Monte Carlo library | — |
| Sebastian Bichelmaier | TU Vienna | Speaker | Efficient parametrizations of potential energy surfaces in Python | — |
| Sebastian Raschka | — | Speaker | Using Deep Learning When Class Labels Have A Natural Order -- Predicting Ratings and Rankings using PyTorch Lightning | — |
| Shaswat Shah | Lyft | Speaker | Comparing the Different Ways to Scale Python and Pandas Code | — |
| Siddhant Wahal | Enthought | Tutorial | Sharing your scientific tools: from a script to a desktop application | — |
| Simon Cross | RIKEN | Speaker | HPy: Where next? | — |
| Simon Cross | RIKEN | Tutorial | Exploring open quantum systems with QuTiP | — |
| Sophia Vargas | — | Speaker | Measuring open source project health | — |
| Steven Diamond | Gridmatic | Tutorial | Convex optimization using CVXPY | — |
| Tanya Akumu | IBM | Speaker | Searching for Anomalous Subsets? All You Need is Scanning | — |
| Tetsuo Koyama | PyVista developers team | Tutorial | PyVista Tutorial | — |
| Thomas Caswell | — | Speaker | Python Data Visualization, 2022 | — |
| Thomas J. Fan | — | Speaker | Counting on Poisson Regression with Scikit-learn | — |
| Thomas Nicholas | — | Speaker | Enabling petabyte-scale ocean data analytics on staggered grids through the grid ufunc protocol in xGCM | — |
| Tim Mensinger | University of Bonn | Tutorial | Practical numerical optimization with scipy, estimagic and jaxopt | — |
| Tom Nicholas | Columbia University | Tutorial | Xarray: Friendly, Interactive, and Scalable Scientific Data Analysis | — |
| Travis Oliphant | — | Speaker | Scientific Computing and Web3 | — |
| Wenduo Zhou | — | Speaker | Automatic Structural Refinement Platform | — |
| William Jamieson | — | Tutorial | Using the Advanced Science Data Format (ASDF) in Python | — |
| Youness Bennani | Bloomberg | Tutorial | The Jupyter Interactive Widget Ecosystem | — |
| Zac Hatfield-Dodds | Anthropic | Tutorial | Introduction to Property-Based Testing | — |