Daniel Biś
Applied Scientist at Amazon
Seattle, Washington, United States
Summary
👤
Senior🎓
Top SchoolDaniel Biś is an Applied Scientist at Amazon AI with a decade of experience at the intersection of deep learning, NLP, graph representation learning, and scalable distributed systems. He holds a Ph.D. from Florida State University where his research probed the learning dynamics of deep neural networks for NLP and LLMs and produced state-of-the-art solutions for biomedical word sense disambiguation and improved clinical mortality prediction. At Amazon he has built graph neural networks for query rewriting in intelligent assistants and repeatedly bridges research prototypes to production-quality ML systems. Comfortable across PyTorch, TensorFlow, and large-scale engineering stacks, he blends theoretical rigor with hands-on engineering to optimize model performance and serving. Based in Seattle, he brings both academic depth and practical delivery experience, often focusing on representation learning and model interpretability in real-world settings.
10 years of coding experience
4 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Florida State University
Polish, English
Github Skills (9)
face7
natural-language-processing5
nlp5
machine-learning4
summarization4
deep-learning4
text-summarization4
tensorflow4
roberta2
Programming languages (2)
Github contributions (5)
danielbis/danielbis.github.io
Oct 2017 - Jun 2022
Contributions:21 pushes, 1 branch in 4 years 8 months
danielbis/MStream
Nov 2019 - Dec 2019
Contributions:28 commits, 6 pushes in 24 days
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