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Hashem Elezabi Hello! I'm currently an M.S. student in Computer Science (AI track) at Stanford. I also did my undergrad at Stanford, majoring in Electrical Engineering with a minor in Mathematics. I'm primarily interested in large language models, vision-language models, and their real-world applications. My interests extend to several adjacent areas, including machine learning, reinforcement learning, optimization, and deep generative models. I'm also very excited about developing tools to make human-AI interaction more effective! Previously, I was mainly interested in the intersection between machine learning and systems, and did an internship at Apple working on SoC performance architecture and an internship at NVIDIA working on deep learning library performance. I was selected for an Apple-Stanford M.S. scholarship for 2022-23 and a School of Engineering Dean's Coterminal Fellowship for 2021-22. Before that, I interned at conversational AI startup Gridspace, building deep generative models for enhancing the quality of call center recordings. As an undergraduate researcher, I worked with Professors Kexin Rong and Peter Bailis on FAST, a state-of-the-art unsupervised earthquake detection system that led to the discovery of thousands of new earthquakes. |
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