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Afshine Amidi is currently teaching the Transformers & Large Language Models workshop at Stanford and is also leading LLM efforts at Netflix. Previously, he worked on the Gemini team at Google and used NLP techniques to solve complex queries. Before that, he worked at Uber Eats to improve the quality of the search and recommendation systems. On the side, Afshine published a few papers at the intersection of deep learning and computational biology. He holds a Bachelor’s and a Master’s Degree from École Centrale Paris and a Master’s Degree from MIT.

Shervine Amidi is currently teaching the Transformers & Large Language Models workshop at Stanford and is also working on the Gemini team at Google to leverage LLMs for action-based queries. Previously, he worked on applied machine learning problems for recommender systems at Uber Eats where he focused on representation learning to better surface dish recommendations. On the side, Shervine published a few papers at the intersection of deep learning and computational biology. He holds a Bachelor’s and a Master’s Degree from École Centrale Paris and a Master’s Degree from Stanford University.

Amir is a machine learning engineer at Meta focusing on video ad systems. Previously, he built scalable content understanding, generation, and ranking systems at Netflix.