Namid Stillman

Namid Stillman, PhD (https://x.com/nrstillman), is an applied research scientist focused on integrating AI methods into scientific research. As an active researcher who has worked on problems in nanoscience, drug discovery, cell biology, and complex systems, he has written more than 20 peer-reviewed articles in top academic journals, and has received generous funding support while conducting research at the University of Bristol, University College, London, and the Alan Turing Institute. He is currently the head of AI at Simudyne, where he helps develop complex models for industry. In his free time, he enjoys spending time in London or going for hikes outside the city. You can learn more at https://nrstillman.github.io.

books by Namid Stillman

Graph Neural Networks in Action
  • February 2025
  • ISBN 9781617299056
  • 392 pages
Included with a Manning Online subscription
  • printed in black & white

Graph Neural Networks in Action teaches you how to analyze and make predictions on data structured as graphs. You’ll work with graph convolutional networks, attention networks, and auto-encoders to take on tasks like node classification, link prediction, working with temporal data, and object classification. Along the way, you’ll learn the best methods for training and deploying GNNs at scale—all clearly illustrated with well-annotated Python code!