Of the Field

SciPy 2026

S

ciPy 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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39Voices
15Underwriters
0Exhibitors
47On the bill · sessions
15Companies · in total
§I

The Voices

Programmed at SciPy, in alphabetical order.
Aarti Jha
Benjamin Batorsky
Carson Sievert
Christopher Davis
Cynthia Ukawu
Daniel Chen
Dhavide Aruliah
Diego Kiedanski
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
Karthik Venkataramani
Katrina Riehl

— and 17 more, by name unsung —

§II

Underwritten By

The houses behind the program. Tiers as disclosed.
MicrosoftPlatinum
NVIDIAPlatinum
Agnostiq (Covalent)Gold
AWSGold
CoiledGold
Posit SoftwareGold
prefix.devGold
DatabricksSilver
The U.S. Geological Survey (USGS)Silver
AnacondaGold/Social Event Sponsor
CurvenoteGold/Proceedings Sponsor
EnthoughtInstitutional Sponsor
QuansightSilver/Tutorial Sponsor
School of Engineering & Technology (SET), University of Washington TacomaSprints Sponsor
StreamlitGold/Social Event Sponsor
§III

The Programme

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 15 companies, parsed from the program.

Fifteen 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.

01Fig. 01 — Composition of the House
0All threespeak · spons · exh
15Sponsoringsponsor only
0Exhibitingexhibitor only
0Companies Speakingspeaker only
02Fig. 02 — The Voices, by Seniority
  • Other roles39100%

Of 39 on the bill · classified by free-text title

03Fig. 03 — The Heaviest in the Room
  1. 01Agnostiq (Covalent)Sp·G
  2. 02AnacondaSp·G
  3. 03AWSSp·G
  4. 04CoiledSp·G
  5. 05CurvenoteSp·G
  6. 06DatabricksSp·S
  7. 07EnthoughtSp·I
  8. 08MicrosoftSp·P
  9. 09NVIDIASp·P
  10. 10Posit SoftwareSp·G
  11. 11prefix.devSp·G
  12. 12QuansightSp·S
  13. 13School of Engineering & Technology (SET), University of Washington TacomaSp·S
  14. 14StreamlitSp·G
04Fig. 04 — By Tier
platinum2
13% of 15
gold5
33% of 15
silver2
13% of 15
gold/social event sponsor2
13% of 15
institutional sponsor1
7% of 15
gold/proceedings sponsor1
7% of 15
silver/tutorial sponsor1
7% of 15
sprints sponsor1
7% of 15
05Fig. 05 — The Missing · who's 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.

06Fig. 06 — Adjacent Convocations · by shared underwriters