Hamel Husain
Machine Learning Engineer
Hamel Husain is currently an entrepreneur in residence at fast.ai, where
he builds tools for data scientists and machine learning engineers. Hamel
has previously worked at Airbnb, DataRobot, and GitHub where he built
a wide array of machine learning products and infrastructure. Hamel
has contributed to data and infrastructure tools in open source such
as Metaflow, Kubeflow, Jupyter, and Great Expectations. Hamel was also
a consultant for over 10 years, and used data science to improve business
outcomes in the restaurant, entertainment, telecommunications, and retail
industries.
Thomas Capelle
Machine Learning Engineer
Thomas Capelle is a Machine Learning Engineer at Weights & Biases working on the Growth Team. He’s a contributor to fastai library and a maintainer of wandb/examples repository. His focus is on MLOps, wandb applications in industry and fun deep learning in general. Previously he was using deep learning to solve short term forecasting for solar energy at SteadySun. He has a background in Urban Planning, Combinatorial Optimization, Transportation Economics and Applied Math.
Darek Kłeczek
Machine Learning Engineer
Darek Kłeczek is a Machine Learning Engineer at Weights & Biases, where he
leads the W&B education program. Previously, he applied machine learning
across supply chain, manufacturing, legal, and commercial use cases. He also
worked on operationalizing machine learning at P&G. Darek contributed the first
Polish versions of BERT and GPT language models and is a leader in the Polish
NLP community. He’s a Kaggle competition winner and 3x Kaggle Master.