Conferences / PyData
PyData Seattle 2025
Nov 7–9, 2025 · Bellevue College, Bellevue, WA, United States
- Conference
- PyData Data science & ML
- Dates
- Nov 7, 2025 – Nov 9, 2025
- Venue
- Bellevue College
- Place
- Bellevue, WA, United States
- Format
- In person
- Status
- Past
- Attendance
- —
- Website
- pydata.org
- Recorded
- 0 sponsors · 66 speaker appearances
- Notes
- Held at Bellevue College, 3000 Landerholm Cir SE, Bellevue, WA (Seattle area). pydata.org/seattle2025 has expired and the Wayback Machine was unreachable during research, so sponsors are not recorded (LanceDB was billed as a community partner on its own Luma page). Speakers: all talks/tutorials/panels/keynotes from pretalx; affiliations only where the pretalx bio states one.
Ticket prices
| Ticket | Price | Valid until | Notes | Source |
|---|---|---|---|---|
| Student Tutorial Pass | $100 | — | Final price incl. processing fees; early bird ($50 off 3-day, $25 off tutorial/talk, non-student) through 2025-09-22 | ti.to |
| Individual Tutorial Pass | $150 | — | Final price incl. processing fees; early bird ($50 off 3-day, $25 off tutorial/talk, non-student) through 2025-09-22 | ti.to |
| Corporate Tutorial Pass | $200 | — | Final price incl. processing fees; early bird ($50 off 3-day, $25 off tutorial/talk, non-student) through 2025-09-22 | ti.to |
| Startup Tutorial Pass | $200 | — | Final price incl. processing fees; early bird ($50 off 3-day, $25 off tutorial/talk, non-student) through 2025-09-22 | ti.to |
| Student Talk Pass | $200 | — | Final price incl. processing fees; early bird ($50 off 3-day, $25 off tutorial/talk, non-student) through 2025-09-22 | ti.to |
| Individual Talk Pass | $250 | — | Final price incl. processing fees; early bird ($50 off 3-day, $25 off tutorial/talk, non-student) through 2025-09-22 | ti.to |
| Student 3-Day Pass | $300 | — | Final price incl. processing fees; early bird ($50 off 3-day, $25 off tutorial/talk, non-student) through 2025-09-22 | ti.to |
| Startup Talk Pass | $300 | — | Final price incl. processing fees; early bird ($50 off 3-day, $25 off tutorial/talk, non-student) through 2025-09-22 | ti.to |
| Individual 3-Day Pass | $400 | — | Final price incl. processing fees; early bird ($50 off 3-day, $25 off tutorial/talk, non-student) through 2025-09-22 | ti.to |
| Corporate Talk Pass | $400 | — | Final price incl. processing fees; early bird ($50 off 3-day, $25 off tutorial/talk, non-student) through 2025-09-22 | ti.to |
| Startup 3-Day Pass | $500 | — | Final price incl. processing fees; early bird ($50 off 3-day, $25 off tutorial/talk, non-student) through 2025-09-22 | ti.to |
| Corporate 3-Day Pass | $600 | — | Final price incl. processing fees; early bird ($50 off 3-day, $25 off tutorial/talk, non-student) through 2025-09-22 | ti.to |
Sponsors 0
No sponsors recorded
Speakers and talks 66
| Speaker | Company | Role | Talk | Links |
|---|---|---|---|---|
| Chang She | LanceDB | Keynote | Keynote: Chang She - Never Send a Human to do an Agent's Search | Video |
| Josh Starmer | — | Keynote | Keynote: Josh Starmer - Communicating Concepts, Clearly Explained!!! (Or, why I don’t worry about AI taking my job and sense of purpose away from me.) | Video |
| Zaheera Valani | Databricks | Keynote | Keynote: Zaheera Valani- Driving Data Democratization with the Databricks Data Intelligence Platform | Video |
| Allison Ding | NVIDIA | Tutorial | Scaling Large-Scale Interactive Data Visualization with Accelerated Computing | — |
| Allison Wang | Databricks | Speaker | Polars on Spark: Unlocking Performance with Arrow Python UDFs | Video |
| Andy Terrel | — | Speaker | Building Inference Workflows with Tile Languages | Video |
| Andy Terrel | — | Tutorial | GPU Accelerated Python | — |
| Anquida Adams | — | Panelist | Diversity Panel: Data for All: Empowering Underrepresented Voices in Data Science and Analytics | — |
| Avik Basu | — | Speaker | Beyond Just Prediction: Causal Thinking in Machine Learning | Video |
| Aziza Mirsaidova | Oracle | Speaker | Prompt Variation as a Diagnostic Tool: Exposing Contamination, Memorization, and True Capability in LLMs | Video |
| Bernardo Dionisi | — | Speaker | Know Your Data(Frame) with Paguro: Declarative and Composable Validation and Metadata using Polars | Video |
| Bill Engels | PyMC Labs | Speaker | Actually using GPs in practice with PyMC Data science | Video |
| C.A.M. Gerlach | — | Speaker | Democratizing (Py)Data: Remote computing for all | Video |
| C.A.M. Gerlach | — | Tutorial | Newcomer Sprint! | — |
| Carl Kadie | — | Speaker | How to Optimize your Python Program for Slowness: Inspired by New Turing Machine Results | Video |
| Carl Kadie | — | Speaker | Explore Solvable and Unsolvable Equations with SymPy | Video |
| Carlos Garcia Jurado Suarez | CodePointers | Speaker | Wrangling Internet-scale Image Datasets | Video |
| Catherine Nelson | — | Tutorial | Going From Notebooks to Production Code | — |
| Daniel Chen | Posit | Tutorial | LLMs, Chatbots, and Dashboards: Visualize and Analyze Your Data with Natural Language | — |
| David Aronchick | Expanso | Speaker | Taming the Data Tsunami: An Open-Source Playbook to Get Ready for ML | Video |
| Denny Lee | Databricks | Speaker | Building Agents with Agent Bricks and MCP | Video |
| Devin Petersohn | Snowflake | Speaker | We don't dataframe shame: A love letter to dataframes | Video |
| Eloisa Elias T | — | Panelist | Panel: Building Data-Driven Startups with User-Centric Design | Video |
| Eloisa Elias T | — | Panelist | Diversity Panel: Data for All: Empowering Underrepresented Voices in Data Science and Analytics | — |
| Eloisa Elias T | — | Tutorial | Newcomer Sprint! | — |
| Esteban Ginez | Q-CTRL | Tutorial | Subgraph Isomorphism at Scale with data science tools | — |
| Everett Kleven | Daft | Speaker | Why Models Break Your Pipelines (and How to Make Them First-Class Citizens) | Video |
| Fangchen Li | — | Tutorial | Newcomer Sprint! | — |
| FTC 18225 High Definition | — | Tutorial | Building Intelligent DIY Robots: From Hardware to Vision Systems | — |
| Heejoon Ahn | Northwell Health | Panelist | Diversity Panel: Data for All: Empowering Underrepresented Voices in Data Science and Analytics | — |
| Ivan Perez Avellaneda | Monaghan Medical Corporation | Tutorial | The Problem of Address Matching: a Journey through NLP and AI | — |
| Jack Ye | LanceDB | Speaker | Supercharging Multimodal Feature Engineering with Lance and Ray | Video |
| Jake Stevens-Haas | — | Tutorial | Newcomer Sprint! | — |
| Jim Dowling | Hopsworks | Speaker | Real-TIme Context Engineering for Agents | Video |
| Jiten Oswal | — | Tutorial | Building Bazel Packages for AI/ML: SciPy, PyTorch, and Beyond | — |
| John Carney | — | Speaker | Building valuable Deterministic products in a Probabilistic world | Video |
| John Tigue | Connoiter | Tutorial | How to make datamap web-apps of embedding vectors via open source tooling | — |
| Joseph Holsten | — | Tutorial | Newcomer Sprint! | — |
| Joshua Ahmed | RealEngineers | Panelist | Panel: Building Data-Driven Startups with User-Centric Design | Video |
| Justin Castilla | Redis | Speaker | There and back again... by ferry or I-5? | Video |
| Jyotinder Singh | Speaker | Practical Quantization in Keras: Running Large Models on Small Devices | Video | |
| Khuyen Tran | CodeCut | Speaker | Multi-Series Forecasting at Scale with StatsForecast | SlidesVideo |
| Micheleen Harris | — | Panelist | Diversity Panel: Data for All: Empowering Underrepresented Voices in Data Science and Analytics | — |
| Nicholas Merchant | — | Speaker | Wrangling Internet-scale Image Datasets | Video |
| nidhin pattaniyil | Walmart | Tutorial | Building a Deep Research Agentic Workflow | — |
| Noor Aftab | Amazon Web Services | Speaker | The Missing 78%: What We Learned When Our Community Doubled Overnight | Video |
| Ojas Ankurbhai Ramwala | University of Washington | Speaker | Explainable AI for Biomedical Image Processing | Video |
| Oli Dinov | AI By The Bay | Panelist | Diversity Panel: Data for All: Empowering Underrepresented Voices in Data Science and Analytics | — |
| Pedro Albuquerque | AppOrchid | Speaker | Generalized Additive Models: Explainability Strikes Back | Video |
| Pedro Luraschi | Hal9 | Panelist | Panel: Building Data-Driven Startups with User-Centric Design | Video |
| Rachel Wagner-Kaiser | KPMG | Tutorial | Newcomer Sprint! | — |
| Rajesh | Jenius Bank | Speaker | Securing Retrieval-Augmented Generation: How to Defend Vector Databases Against 2025 Threats | Video |
| Ramesh Oswal | Aurora | Tutorial | Building Bazel Packages for AI/ML: SciPy, PyTorch, and Beyond | — |
| Ravi Kumar Yadav | Walmart | Tutorial | Building a Deep Research Agentic Workflow | — |
| Robert Masson | Atlassian | Tutorial | Going From Notebooks to Production Code | — |
| Roman Lutz | Microsoft | Speaker | Red Teaming AI: Getting Started with PyRIT for Safer Generative AI Systems | Video |
| Sarah Kaiser | Microsoft | Tutorial | There's no place like home: using AI agents in Jupyter notebooks | — |
| Saurabh Garg | Outerbounds | Speaker | Optimizing AI/ML Workloads: Resource Management and Cost Attribution | Video |
| Sebastian Duerr | Cerebras | Speaker | Evaluation is all you need | Video |
| Shujing Yang | Databricks | Speaker | Polars on Spark: Unlocking Performance with Arrow Python UDFs | Video |
| Stephen Cheng | Parakeet Health | Speaker | Scaling Background Noise Filtration for AI Voice Agents | Video |
| Trent Nelson | NVIDIA | Speaker | Unlocking Parallel PyTorch Inference (and More!) with Python Free-Threading | Video |
| Weston Pace | LanceDB | Speaker | Data Loading for Data Engineers | Video |
| Yibei Hu | — | Speaker | Multi-Series Forecasting at Scale with StatsForecast | SlidesVideo |
| Yinhan Liu | FlickBloom | Panelist | Panel: Building Data-Driven Startups with User-Centric Design | Video |
| Yujian Tang | OSS4AI | Panelist | Panel: Building Data-Driven Startups with User-Centric Design | Video |