PyData London 2025 — the speakers, verified

London, United Kingdom · June 2025 · organized by PyData London / NumFOCUS

58 speakers below were extracted from the event's public agenda, and PyData London 2025 publishes its own site.

Who spoke, and about what

• Theodore Meynard — Data Science Manager at GetYourGuide
  • From Trees to Transformers: Our Journey Towards Deep Learning for Ranking source
• Mihail Douhaniaris — Senior Data Scientist at GetYourGuide
  • From Trees to Transformers: Our Journey Towards Deep Learning for Ranking source
• Marco Gorelli — Senior Software Engineer at Quansight Labs
  • Polars, DuckDB, PySpark, PyArrow, pandas, cuDF: how Narwhals has brought them all together! source
• Lex Avstreikh
  • Sovereign Data for AI with Python source
• Luca Baggi — ML Engineer @xtream
  • LLM Inference Arithmetics: the Theory behind Model Serving source
• Cheuk Ting Ho — After having a career in Data Scientist and Developer Relations, Cheuk dedicated her work to the ope
  • Is coding assistant as good as we thought in coding? source
• Lilinoe Harbottle
  • Git Commit, MedTech Transformed: Python’s Medical Robotics Breakthrough source
• Jacob Tomlinson — Jacob Tomlinson is a senior software engineer at NVIDIA. His work involves maintaining open source p
  • GPU Accelerated Python source
• Mridul Seth
  • NetworkX is Fast Now: Zero Code Change Acceleration source
• Anders Bogsnes
  • Hands-on with Apache Iceberg source
• Katrina Riehl — Dr. Katrina Riehl is a Principal Technical Product Manager at NVIDIA leading the CUDA Education prog
  • GPU Accelerated Python source
• Jeremy Tanner
  • GPU Accelerated Python source
• Lawrence Mitchell
  • GPU Accelerated Python source
• Chris Fonnesbeck — Chris is a Principal Quantitative Analyst at PyMC Labs and an Adjoint Associate Professor at the Van
  • PyMC Code Sprint source
  • Introduction to Bayesian Time Series Analysis with PyMC source
• Suyash Joshi
  • Forecasting Weather using Time Series ML source
• Jeroen Janssens — Jeroen Janssens, PhD, is a Senior Developer Relations Engineer at Posit, PBC. His expertise lies in visualizing data, im
  • Package Your Python Code as a CLI source
• Thijs Nieuwdorp — Thijs Nieuwdorp is the Lead Data Scientist at Xomnia in Amsterdam. His interest in the interaction between human and com
  • Package Your Python Code as a CLI source
• John Sandall — John Sandall is the CEO and Principal Data Scientist at Coefficient.
  • How To Measure And Mitigate Unfair Bias in Machine Learning Models source
• Andrea Melloncelli
  • Python Meets Quantum: Learn, Code, and Simulate source
• Sam Joseph — I am a Senior Software Engineer & AI Specialist at DRW, a proprietary trading firm. I was previous
  • Python Engineering Excellence Birds of a Feather source
  • Transformers Inside Out (Parts 1 & 2) source
• Ahmad Albarqawi
  • Graph Theory for Multi-Agent Integration: Showcase Clinical Use Cases source
• Tim Santos
  • Building your own vertical agent with AG2 AgentOS source
• Chi Wang
  • Building your own vertical agent with AG2 AgentOS source
• Ade Idowu
  • Hands-on workshop on developing Reinforcement Learning solutions with financial domain example use cases. source
• Leanne Fitzpatrick
  • Opening Notes & Keynote: Keep Calm and Data On: Being a data science practitioner in the era of AI proliferation source
• Callum Court
  • Multi-Task Learning for Fraud detection: From Trees to MLPs source
• Michał Szołucha
  • Parallel PyTorch Inference with Python Free-Threading source
• Alex Owens
  • Why you should stop pretending your sparse data is dense source
• Emeli Dral
  • AI agents testing: How to evaluate the unpredictable source
• Alex Jones
  • How we unified feature engineering across data and backend at Monzo source
• Olena Kutsenko
  • Bringing stories to life with AI, data streaming and generative agents source
• Joris Bekkers
  • Cutting Edge Football Analytics using Polars, Keras and Spektral source
• Radion Bikmukhamedov
  • Enhancing Fraud Detection with LLM-Generated Profiles: From Analyst Efficiency to Model Performance source
• Jay Alammar
  • Keynote- From Next Token Prediction to Reasoning and Beyond source
• Chris Laffra
  • PyScript - Python in the Browser source
• Theo van Kraay — Theo is passionate about NoSQL and distributed computing. He joined Microsoft in 2017 and has been i
  • Tackling Data Challenges for Scaling Multi-Agent GenAI Apps with Python source
• Ines Montani — Ines Montani is a developer specializing in tools for AI and NLP technology. She’s the co-founder and CEO of Explosion a
  • Conquering PDFs: document understanding beyond plain text source
  • Feminist AI Lounge source
• Adam Hill — Adam is the Interim Director of Data Science at ComplyAdvantage, where he leads a brilliant team tackling financial crim
  • Not Another LLM Talk… Practical Lessons from Building a Real-World Adverse Media Pipeline source
• John Carney
  • Platforms for valuable AI Products: Iteration, iteration, iteration source
• Natalia Ziemba‑Jankowska
  • Media Mix Modelling - how we can save company budget? source
• Ian Ozsvald
  • Leaders at PyData source
  • Successful Projects through a bit of Rebellion source
• Elizabeth Osanyinro
  • AI for Everyone - Building Inclusive Machine Learning Models source
• Onyekachukwu Ojumah
  • Automating Porosity Detection in Additive Manufacturing with Deep Learning source
• Isaac Chung
  • Reproducibility in Embedding Benchmarks source
• Tim Paine
  • One repo to rule them all, one repo to bind them...Control all of your projects with copier! source
• Lena Shakurova — Lena Shakurova is the founder of ParsLabs (https://parslabs.org), a Conversational AI agency, and Ch
  • Making LLMs reliable: A practical framework for production source
• Sofia Pinto — Sofia is a principal data scientist at Nesta, working with the sustainable future mission team on de
  • Analysing smart meter data to uncover energy consumption patterns source
• Andy Terrel
  • CUDA in Python: A New Era for GPU Acceleration source
• Tony Mears
  • Keynote- Innovation is Dead source
• Matt Squire
  • Diving into Transformer Model Internals source
• Jyoti Yadav
  • Agentic Cyber Defense with External Threat Intelligence source
• Hugh Evans
  • Humble Data Workshop source
• Matt Upson
  • Debugging Leadership: Six Errors when Moving From Code to Management source
• Samiul Huque
  • You Came to a Python Conference. Now, Go Do a PR Review! source
• Harrison Pim
  • Building a knowledge graph for climate policy source
• Fred O'Loughlin — Lead MLOps Engineer at Climate Policy Radar
  • Building a knowledge graph for climate policy source
• Salman Khan
  • Transfer Learning: Leveraging Pretrained Models with Limited Data source
• Tatiana Al-Chueyr
  • Scaling AI workloads with Ray & Airflow source

Questions about PyData London 2025

Who spoke at PyData London 2025?

58 speakers we hold a record for, listed below with the session each one gave. The list comes from the conference's own published agenda, so it is who actually appeared rather than who applied or who paid.

When and where was PyData London 2025?

June 2025, in London, run by PyData London / NumFOCUS. The agenda it was taken from is linked at the top of this page.

Are the talk titles real?

62 of the 62 records carry the session title exactly as the agenda printed it, so every one below is quoted.

Can I contact these speakers?

Not through us. We hold no contact details and no fees. Each entry links to the agenda page it came from, and that is the route.