About Me

Eric Zelikman is a deep learning engineer with a keen interest in how algorithms can learn meaningful representations. A recent graduate of Stanford University's Symbolic Systems program, he focuses on developing efficient, robust, and disentangled representations within the field of machine learning. Zelikman believes that insights from machine learning can inform broader human challenges, aiming to leverage this technology to address significant global issues. He is currently engaged with DeepLearning.AI and has contributed to various research initiatives that explore the intersections of language models and reasoning.