Of the Field

SciPy 2026

SciPy 2026 is the 25th annual Scientific Computing with Python conference, bringing together researchers, developers, and users of open-source scientific tools built in Python. The event features highlighted tracks in open-source collaboration, machine learning, and AI, as well as tutorials, conference sessions, sprints, and Birds-of-a-Feather sessions focus…

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42Speakers
25Sponsors
47On the bill · sessions
27Companies · in total
§I

Speakers

Programmed at SciPy, in alphabetical order.
Aarti Jha
Amber Case
Research Director at the Metagovernance Project and founder of The Calm Tech Institute · The Calm Tech Institute / Metagovernance Project
Benjamin Batorsky
Carson Sievert
Christopher Davis
Cynthia Ukawu
Daniel Chen
Dhavide Aruliah
Diego Kiedanski
Dr. Joseph H. Kennedy
Staff Scientist at the Alaska Satellite Facility · Alaska Satellite Facility, University of Alaska Fairbanks
Eniola Awowale
Eric Ma
Gil Forsyth
Ian Hunt-Isaak
Ian Spektor
Iason Krommydas
Jacob Tomlinson
James A. Bednar
Jaya Venkatesh
Jim Crist-Harif
Jim Pivarski
Jon Mease
§II

Sponsors

The houses behind the program. Tiers as disclosed.
MicrosoftPlatinum
NumFOCUSDiamond
NVIDIAPlatinum
PositPlatinum
Python Software FoundationPlatinum
Agnostiq (Covalent)Gold
AWSGold
CoiledGold
MetaGold
Posit SoftwareGold
PrefixGold
prefix.devGold
Thomson ReutersGold
ANSYSSilver
DatabricksSilver
KitwareSilver
SynopsysSilver
The U.S. Geological Survey (USGS)Silver
AnacondaGold/Social Event Sponsor
CurvenoteGold/Proceedings Sponsor
DevitJobsCommunity Partner
EnthoughtInstitutional Sponsor
QuansightSilver/Tutorial Sponsor
School of Engineering & Technology (SET), University of Washington TacomaSprints Sponsor
StreamlitGold/Social Event Sponsor
§III

Agenda

Selected from 47 sessions on the bill.
  • Monday, July 13, 1:30 PM

    Create custom image visualization and analysis tools with napari

    With everything from microscopes to telescopes to satellites, scientists produce image data in countless formats, shapes, sizes, and dimensions. Python provides a rich ecosystem of…

    Tutorials
  • Monday, July 13, 1:30 PM

    HighLoad Python: SIMD, GPU, TPU. Acceleration Patterns: Theory, Practice, Benchmarks. Looking into Silicon.

    You’ll learn a repeatable workflow to accelerate real numeric kernels using CPU SIMD, GPU arrays + custom kernels, and TPU/XLA compilation—all from Python. For each acceleration ti…

    Tutorials
  • Monday, July 13, 1:30 PM

    Introduction to Causal Inference

    This tutorial session is intended to give attendees a gentle introduction to applying causal thinking and inference using python. The tutorial will involve a combination of present…

    Tutorials
  • Monday, July 13, 1:30 PM

    Intro to Safe, Reliable, and Maintainable AI Apps in Python

    Large Language Models (LLMs) are transforming how we build applications, but the path from "cool demo" to "production-ready tool" is littered with challenges: hallucinations, verif…

    Tutorials
  • Monday, July 13, 1:30 PM

    Why oh why a CLI?

    The command line is the most powerful, composable, and underappreciated tool in a data scientist's arsenal. In this hands-on tutorial, attendees will go from "what is a terminal?" …

    Tutorials
  • Monday, July 13 1:30 PM, 4h

    Create custom image visualization and analysis tools with napari

    With everything from microscopes to telescopes to satellites, scientists produce image data in countless formats, shapes, sizes, and dimensions. Python provides a rich ecosystem of…

    Tutorials
  • Monday, July 13 1:30 PM, 4h

    HighLoad Python: SIMD, GPU, TPU. Acceleration Patterns: Theory, Practice, Benchmarks. Looking into Silicon.

    You’ll learn a repeatable workflow to accelerate real numeric kernels using CPU SIMD, GPU arrays + custom kernels, and TPU/XLA compilation—all from Python. For each acceleration ti…

    Tutorials
  • Monday, July 13 1:30 PM, 4h

    Introduction to Causal Inference

    This tutorial session is intended to give attendees a gentle introduction to applying causal thinking and inference using python. Causal data analysis is very common in many academ…

    Tutorials
  • Monday, July 13 1:30 PM, 4h

    Intro to Safe, Reliable, and Maintainable AI Apps in Python

    Large Language Models (LLMs) are transforming how we build applications, but the path from "cool demo" to "production-ready tool" is littered with challenges: hallucinations, verif…

    Tutorials
Intermission
Part the Second · For the Buyer

An audience of 27 companies, parsed from the program.

27 companies in attendance.

The numbers below are derived from the speakers, sponsors, and exhibitors on this page — cross-referenced into one ledger. They are the only thing here that 10times.com cannot tell you.

Who's in the room
0All threespeak · spons · exh
24Sponsoringsponsor only
3Companies Speakingspeaker only
Speakers by seniority

2% of the speakers carry senior titles — C-suite, Founder, VP, or Director-level.

  • Founder / Owner12%
  • Research / Science25%
  • Other roles3993%

Of 42 on the bill · classified by free-text title

Most-represented companies
  1. 01Agnostiq (Covalent)Sp·G
  2. 02AnacondaSp·G
  3. 03AnsysSp·S
  4. 04AWSSp·G
  5. 05CoiledSp·G
  6. 06CurvenoteSp·G
  7. 07DatabricksSp·S
  8. 08DevITJobs.ukSp·C
  9. 09EnthoughtSp·I
  10. 10KitwareSp·S
  11. 11MetaSp·G
  12. 12MicrosoftSp·P
  13. 13NumFOCUSSp·D
  14. 14NVIDIASp·P
Sponsors by tier
diamond1
4% of 25
platinum4
16% of 25
gold8
32% of 25
silver5
20% of 25
silver/tutorial sponsor1
4% of 25
community partner1
4% of 25
sprints sponsor1
4% of 25
gold/proceedings sponsor1
4% of 25
gold/social event sponsor2
8% of 25
institutional sponsor1
4% of 25
At peer events but not here

These companies sponsored two or more peer events recently, but aren't on this program. For an organizer, that's a list of warm prospects.

Related events · by shared sponsors