PyData Eindhoven 2022

Andrei Alekseev

my name is Andrei. I've started working for ASML just a few months ago. I'm a Machine Learning Developer experienced in time series analysis and demand forecasting. I created open source time series forecasting library called ETNA.

  • Why does everyone need to develop a machine learning package?
Anjan Prasad Gantapara

Product Owner Predictive Maintenance

  • Predictive Maintenance at ASML
Bas Vlaming

Bas is a data scientist at Picnic Technologies. In his role, he functions as the Merchandising chapter lead, where he is responsible for AI projects that affect the Picnic app and what customers will see there, such as promotion forecasting, ranking & personalization, and recommendations. He has a background in physics, holding a Ph.D. from the University of Groningen and previously working at the Massachusetts Institute of Technology, MPI-PKS and Ocado Technology.

  • Everything in its Right Place: Optimising Ranking in Online Grocery
Emil Rijcken

PhD candidate at the Jheronimus Academy of Data Science/ Eindhoven University of Technology in Natural Language Processing for mental health care.

  • FuzzyTM: a Python package for fuzzy topic models
Greg Michaelson

Greg Michaelson is Cofounder and Chief Product Officer at Zerve, a young, stealthy startup that’s rethinking the data science development experience. Previously, Greg was an early joiner at DataRobot where he played many roles, including Chief Customer Officer. Prior to that, he worked as a data scientist in the financial sector after earning a PhD in Applied Statistics from the University of Alabama. In his spare time, Greg manufactures a line of flavored breakfast cereal toppings called Cerup. He lives in Spring Creek, Nevada with his wife, four children, and two Clumber Spaniels.

  • Significant Roadblocks to Usefulness for Jupyter Notebooks and a Recipe to Fix them
Hamideh Rostami
  • Predictive Maintenance at ASML
Harizo Rajaona

Harizo is the VP of Tech Content & Enablement at Dataiku, a company that offers a platform to build, deploy and run data science and machine learning projects at scale. He leads the Developer Advocacy team, which mission is to facilitate the adoption of the Dataiku platform by its most technical users.

Harizo started at Dataiku as a Data Scientist before moving to the Engineering team. Prior to that, he completed a PhD in mathematics on probabilistic simulations at scale for atmospheric physics.

  • A Tour of the Many DataFrame Frameworks
Jeroen Overschie

Jeroen is a Machine Learning Engineer at GoDataDriven, in The Netherlands. Jeroen has a background in Software Engineering and Data Science and helps companies take their Machine Learning solutions into production.
Besides his usual work, Jeroen has been active in the Open Source community. Jeroen published several PyPi modules, npm modules, and has contributed to several large open source projects (Hydra from Facebook and Emberfire from Google). Jeroen also authored two chrome extensions, which are published on the web store.

Hope to see you at PyData Eindhoven! 👋🏻

  • How to create a Devcontainer for your Python project 🐳
Judith van Stegeren

Judith van Stegeren is a machine learning engineer at Floryn, a Dutch fintech startup that finances small and medium businesses. She previously worked as a researcher at the University of Twente, and as a computer security specialist at the Dutch National Cyber Security Centre in the Hague.

Judith holds a PhD in computer science from the University of Twente. Her interests include the financial domain, data wrangling, natural language processing, procedural art and video games.

  • Practical code archaeology
Julien Hamerlinck

Data consultant GroupM Nexus

  • Thompson sampling for personalising a car brands advertisements
Lars Hanegraaf

Data Engineer and co-founder of Blenddata.

Helping clients to build data platforms in the cloud.

Enthousiastic about clean code, cloud, self-service solutions and music.

  • How to not pull your hair out while providing data to the business: unit testing for your data pipelines
Marc van Meel

Marc is AI & Ethics lead at KPMG, Managing Consultant, recovering Data Scientist, Public Speaker and host of the Beyond Data Science podcast.

  • AI Ethics in the Wild - Welcome to the Jungle
Marijn Markus

As a data scientist, Marijn finds data-drive solutions to problems.

As a social scientist, Marijn unveils the mechanisms behind people's behavior.

As a human being, Marijn discusses ethics and human rights.

Marijn combines technical expertise with a delivery of analysis, visuals and coaching, thanks to his experience and background in social science. As open source and sensor enthusiast, Marijn leverages his affection for open data and internet culture to deliver unique insights and solutions.

At Capgemini NL, Marijn has been leading the AI efforts for over 6 years.

From distinguishing science and fiction, creating friction and first introductions,
To research, development, team management and implementing AI in production.

Additionally, Marijn is a frequent speaker at events on AI and data science.

Most of all, Marijn seeks to improve people's lives using data.

  • AI for Good- Then and Now
Marysia Winkels

Marysia is a Data Scientist and Data Science Educator at GoDataDriven. In addition to this, she is also chair of the PyData Amsterdam committee.

  • Data Storytelling through Visualization
Max Knobbout

Currently employed as the lead data scientist in the central data science team at Just Eat I have a research background in AI (PhD., MSc.), and am very passionate about applying these techniques to solve complex real-world problems.

  • Causal inference and scenario generation within Just Eat
Nico van Engelenhoven


  • Thompson sampling for personalising a car brands advertisements
Pedro Holanda

COO of DuckDB Labs

  • DuckDB: Bringing analytical SQL directly to your Python shell.
Rob de Wit

Rob is a developer advocate at Iterative AI. He’s got a background in information sciences, and experience in data analytics and engineering. Right now he’s learning a whole lot about MLOps and exploring how people can adopt a collaborative, experiment-driven approach to ML projects.

  • Becoming a Pokémon Master with DVC: reproducible machine learning experiments
Ruben Mak

Lead data scientist at, building ML to make healthy food available by making greenhouses more efficient and sustainable.

  • Is it a predictive model? Is it causal inference? Well... It is running a greenhouse.
Sander Boelders

Data scientist and deep learning researcher and PhD student at the Elisabeth-Tweesteden hospital, Neurosurgery department and Tilbrurg University, department of cognitive sciences and AI.

  • Predicting Cognitive Impairment in Patients With a Primary Brain Tumor: A Machine Learning Perspective
Tosca van Meer

Bringing ingenuity to life using Applied AI

  • Using Deep Learning to Reduce Flight Delays at Schiphol Airport
Vincent Gosselin

Vincent has over 30 years of experience in Data Science, AI, and Decision Optimization.

He worked as Head of Data Science (Consulting) with organizations including Honeywell, ILOG, IBM. He has strong modeling skills in mathematical programming and machine learning.
Vincent's main objective is to help organizations identify and deploy analytics that maximizes ROI. He holds an M.S. in Data Science / AI from the University of Paris Saclay.

  • Turning your Data/AI algorithms into full web apps in no time with Taipy
Vincent Warmerdam

Vincent is a senior data professional who worked as an engineer, researcher, team lead, and educator in the past. He's especially interested in understanding algorithmic systems so that one may prevent failure. As such, he prefers simpler solutions that scale, as opposed to the latest and greatest from the hype cycle.

You may know him from his blog, his many open source projects, some of his PyData talks, or his project.

He's also known for giving helpful advice for free, so please feel free to talk to him if you have an interesting data problem.

  • Bulk Labelling Techniques
Wesley Boelrijk

I am the Lead Machine Learning Engineer at Xccelerated (part of Xebia). This means I teach and guide junior-to-medior ML Engineers in our one-year program. Besides that, I work on consultancy projects and have recently been at KLM, ProRail, and Port of Rotterdam. In my free time, I like to stay up-to-date in the ML ecosystem and play around with computer vision.

  • Lowering the barrier for ML monitoring
Yannic Suurmeijer
  • Come connect to the active Brainport community
santiago ruiz

Santiago has an educational background in industrial engineering, operations research, and data science. In the last years, he has been working extensively with computer vision to make real-time turnaround tasks related to detections with the final aim of reducing flight delays. Santiago's passion is to develop data-driven solutions to help to improve people’s life.

  • Using Deep Learning to Reduce Flight Delays at Schiphol Airport