Avik Basu
Employers on the program
- 2026Intuit1 talk
Appearances by year
- PyData
- Data Council
- PyCon (national Python conferences)
- SciPy Conference (Scientific Computing with Python)
Talks
| Date | Event | Conference | Role | Title | Links |
|---|---|---|---|---|---|
| May 13, 2026 | PyCon US 2026 | PyCon (national Python conferences) | speaker | Upgrading Python CLIs: From Scripts to Interactive Tools Audience This talk is for Python developers at any level. We will use ML workflows as our running example, but the patterns apply to any CLI application. | Video |
| May 12, 2026 | AI Council 2026 | Data Council | talk | From Prediction to Uplift: Causal Modeling for Better Decisions Data science as Intuit | |
| Nov 7, 2025 | PyData Seattle 2025 | PyData | speaker | Beyond Just Prediction: Causal Thinking in Machine LearningMost ML models excel at prediction, answering questions like _"Who will buy our product?"_ or _"Which customers are likely to churn?"_. But when it comes to…Show lessMost ML models excel at prediction, answering questions like _"Who will buy our product?"_ or _"Which customers are likely to churn?"_. But when it comes to making actionable decisions, prediction alone can be misleading. | Video |
| Sep 1, 2025 | PyData Berlin 2025 | PyData | talk | Beyond the Black Box: Interpreting ML models with SHAPAs machine learning models become more accurate and complex, explainability remains essential. Explainability helps not just with trust and transparency but…Show lessAs machine learning models become more accurate and complex, explainability remains essential. Explainability helps not just with trust and transparency but also with generating actionable insights and guiding decision-making. | Video |
| Jul 7, 2025 | SciPy 2025 | SciPy Conference (Scientific Computing with Python) | bof | Open Code, Open Science: What’s Getting in Your Way?Collaborating on code and software is essential to open science—but it’s not always easy. Join this BoF for an interactive discussion on the real-world…Show lessCollaborating on code and software is essential to open science—but it’s not always easy. Join this BoF for an interactive discussion on the real-world challenges of open source collaboration. | |
| Nov 6, 2024 | PyData NYC 2024 | PyData | speaker | Reproducible work environments for data scientists using Nix | Video |
Frequent co-speakers
| Speaker | Shared events | Shared talks | Last together |
|---|---|---|---|
| Chang She | 3 | — | 2026 |
| Sarah Kaiser | 3 | — | 2026 |
| Carol Willing | 2 | — | 2026 |
| Catherine Nelson | 2 | — | 2026 |
| Vyas Ramasubramani | 2 | — | 2026 |
| Alexandre Andorra | 2 | — | 2025 |
| Allison Ding | 2 | — | 2025 |
| Allison Wang | 2 | — | 2025 |
| Andy Terrel | 2 | — | 2025 |
| Anjali Datta | 2 | — | 2025 |
| C.A.M. Gerlach | 2 | — | 2025 |
| Cainã Max Couto da Silva | 2 | — | 2025 |
| Carlos García Jurado Suarez | 2 | — | 2025 |
| Daniel Chen | 2 | — | 2025 |
| Deepyaman Datta | 2 | — | 2025 |
Speakers with the same name are merged into one entry, so this page may combine more than one person. Affiliations are shown as each conference listed them.