Summary
Tom G is an Engineer II in London with a PhD in Machine Learning and Software Security and a decade of hands-on experience building secure, production-ready ML systems. He has blended research and engineering across roles at Amazon, SAP, Volkswagen and startups, delivering Agentic AI for automated pentesting, TLS parsers in Rust, and Transformer- and VAE-based anomaly detection. His research background spans GNNs, causal inference, privacy-preserving and explainable ML, and he has practical experience implementing differentially private and federated learning in TensorFlow. Tom also teaches compiler engineering and regularly presents on software security, reflecting a strong aptitude for communicating complex technical ideas. Comfortable across languages and stacks, he uniquely bridges deep academic rigor with applied DevSecOps and tool-building for enterprise security.
10 years of coding experience
9 years of employment as a software developer
Bachelor of Science - BS, Applied Computer Science, 3.7/4.0 GPA, Bachelor of Science - BS, Applied Computer Science, 3.7/4.0 GPA at Baden-Wuerttemberg Cooperative State University (DHBW)
Doctor of Philosophy - PhD (Dr. rer. nat.), Machine Learning and Software Security, Magna cum laude, Doctor of Philosophy - PhD (Dr. rer. nat.), Machine Learning and Software Security, Magna cum laude at Technische Universität Berlin
Master of Science - MS, Computer Science, 3.7/4.0 GPA, Master of Science - MS, Computer Science, 3.7/4.0 GPA at Karlsruhe University of Applied Sciences