Summary
Beliz Gunel is a Senior Research Scientist at Google DeepMind with a decade of experience building and deploying large language models, following a PhD in machine learning from Stanford and an EECS BS from Berkeley. Her work spans representation learning, ML systems, and data-efficient models, with practical impact across Google Brain, Facebook AI, Microsoft, and Amazon Lab126. She has co-advised PhD students on AI in healthcare and helped ship components used in Google Cloud Document AI, reflecting a focus on robust, real-world ML. Known for blending theoretical insight with production mindset, she emphasizes architectures whose embeddings resonate with input structure to improve resilience to distribution shifts. Based in Mountain View, she also explores entrepreneurship through Stanford GSB’s Ignite program, signaling a strong interest in translating research into products.
10 years of coding experience
2 years of employment as a software developer
Ignite Entrepreneurship and Innovation, Ignite Entrepreneurship and Innovation at Stanford University Graduate School of Business
Bachelor of Science (B.S.) Electrical Engineering and Computer Science, Bachelor of Science (B.S.) Electrical Engineering and Computer Science at University of California, Berkeley
High School Math/Science Track, High School Math/Science Track at Izmir Fen Lisesi
Doctor of Philosophy - PhD Machine Learning, Doctor of Philosophy - PhD Machine Learning at Stanford University
English, Turkish