I grew up in Bombay (now Mumbai), India. I did my undergraduate studies at IIT Bombay and came to Stanford as a PhD student. I spent a year in the research group at Google, and 14 years on the faculty at Princeton before coming back to Stanford in 2015. I study algorithms for situations where either the problem is too hard to solve exactly, or the data is too big to fit in memory and we have to cut corners somewhere. I’m looking forward to co-teaching CS 229 this quarter!
I grew up in small areas around the eastern part of Los Angeles (like Pasadena!), and I’ve always been a Raiders fan (yes, they’ve left me twice). I’m faculty in the AI lab, and I work on understanding how machine learning is changing the way we build software systems, how we get domain knowledge into modern deep learning systems, and the fun math/stats/optimization problems that pop out. CS229 is a really fun course to teach at a really exciting time for the field—and it’s a chance to meet so many smart students.
I was born in Seoul, South Korea and moved to Southern California. I did my undergraduate studies at UC Berkeley and my masters at Stanford University, School of Education. I am a course coordinator in the Computer Science department and help manage the larger CS courses. Looking forward to a great quarter with you all :)
I’m a first-year Master’s student in Theory/AI, and I just left industry after nine years to pursue my dream of teaching CS. At Google, I worked on the Code Jam programming contest and on Search; prior to that, I got degrees in chemistry and environmental science, and I taught an intro CS course (and TAed for many other courses) at Cal. I’ve played in and run puzzle hunts and trivia games for many years, and I also love history, Japanese literature, movies, probability/combinatorics, tabletop RPGs, and weightlifting. (SCPD/NDO students, I’ve been there, so feel free to reach out!)
I am a final year PhD student in CS working with Andrew Ng. My interests include ML and its applications to healthcare. I have been involved with CS229 for many offerings, and enjoy it every time!
I am a first year M.S. student in the CS department; I did my undergraduate degree at Stanford in CS as well. I am currently working on applying deep learning, specifically transformers, to the classification of MRI images. Looking forward to TAing 229 this quarter!
Hi! I am a MS student in the CS department, and did my undergrad in EE at Stanford as well. For the past few years, I have worked at the intersection of EE/CS/Radiology applying deep learning approaches (especially generative models) to MRI reconstruction. I also have some experience with NLP, having previously interned at Facebook on a natural language generation team for FB Assistant. Beyond school, I enjoy sports (especially basketball and tennis) and originally hail from Portland, Oregon. Looking forward to meeting everyone!
I am a second year Ph.D. student in the CS department, advised by Tengyu Ma. My research focuses on machine learning theory, unsupervised learning and transfer learning. In particular, I've been interested in understanding how optimization algorithms influence deep neural networks' generalization performance. Happy to chat with anyone!
II am a final year PhD student in EE, with interests in optimization, statistics, signal processing, ranging from more theoretical investigations to more practical algorithm design. I had fun TAing for CS229 in the past and excited for the quarter ahead!
Hi! I am a second year PhD student in AeroAstro, advised by Mykel Kochenderfer. My research focuses on probabilistic traffic modeling for the aircraft and automobiles. Within the scope of CS 229, my particular interest lies in unsupervised learning and reinforcement learning. Outside of school, I enjoy playing the piano, singing, and exploring new foods. Looking forward to TAing CS 229 this quarter!
I am a fifth year Ph.D. student in the CS department, advised by Emma Brunskill. Before that, I finished undergraduate study at Peking University in 2016. I am working on reinforcement learning (RL) for real-world applications where sample cost and safety would be huge challenges. I am also attracted by other problems about learning from interactions, including contextual bandits problem, imitation learning, and causal inference. Happy to chat if you have any questions or ideas for projects in related areas.
I am a second year MS CS student, did my undergrad at UCLA in Computer Science and Mathematics. My research work is in applications of deep learning to biomedical problems such as automated chest X-ray diagnosis and prognostic analysis of cancer, often in settings with limited supervision or lower-quality labels. Much of my work has involved applying techniques from NLP to biomedical text. I am a passionate believer in transformer models and believe that they should (and already are) be applied to vision tasks and can be as successful there as they are in NLP.
Hi, I am a MSCS student with double bachelor’s degrees in Computer Science and Cognitive Science (CS square!). I am interested in natural language processing and cognitive modeling in general, though my current on-going research project focuses on model compression. Same as many of you, I am trying to juggle school with research, work, and random hobbies (manga, literature, FFXIV, and more). CS229 is a challenging but definitely rewarding class. Share to me and your classmates about your struggle, and let’s pull through this together =)
Hi! I’m a Master’s student on the AI track. I spent some time at Facebook working on ML for imbalanced data, and on privacy attacks against neural networks. Lately, I've been really excited about algorithmic music generation. I also have some experience in computer vision, RL, and NLP. Feel free to reach out if you're interested in a project in any of these domains, or just want to chat :)
Hi, I’m a first year MSCS student with a focus in AI. My research work focuses on applying GANs for medical tasks, such as augmenting limited and often expensive medical datasets. I have prior experience in applying Deep Learning for Computer Vision tasks, such as monocular depth detection and pose estimation. CS229 is a very fun, exciting and rewarding class. I’m happy to chat if you have any questions or ideas about related projects. Looking forward to a great quarter!