Every year, we have a great set of SAIL graduates who are entering the job market soon (or already!) Each soon-to-be graduate has provided a brief description of their research; feel free to reach out if you have an opportunity.
Ajay Shanker Tripathi
Areas of Interest: Computational Education, Graph NN, Theoretical ML
Email: chausies7@gmail.com
Research Focus: Curve Fitting from Probabilistic Emissions and Applications to Dynamic Item Response Theory
Ali Mottaghi
Areas of Interest: Biomedicine and Health, Computer Vision, NLP
Email: mottaghi@stanford.edu
Research Focus: AI in Healthcare
Allan Zhou
Areas of Interest: Computer Vision, Robotics, Reinforcement Learning
Email: ayz@cs.stanford.edu
Research Focus: Invariance, data augmentation, and symmetries of deep neural networks.
Annie Xie
Areas of Interest: Robotics, Reinforcement Learning
Email: anniexie@stanford.edu
Research Focus: Deep reinforcement learning, foundation models for decision-making, generalizable robot learning
Archit Sharma
Areas of Interest: NLP, Robotics, Reinforcement Learning
Email: architsh@stanford.edu
Research Focus: Reinforcement learning for building autonomous robots that can learn from real world interaction
Bokui (William) Shen
Areas of Interest: Computer Vision, Human Centered and Creative AI, Robotics
Email: william.shen@apparate.ai
Research Focus: Generating Content for AI, and AI Generated Cotents: Synthetic Data For and From Machine Learning
Chris Cundy
Areas of Interest: Generative Models
Email: cundy@stanford.edu
Research Focus: Controlling generative models with variational methods
Dilip Arumugam
Areas of Interest: Reinforcement Learning
Email: dilip@cs.stanford.edu
Research Focus: My research relies on various statistical tools for navigating the full spectrum of reinforcement learning research, from the theoretical which offers provable guarantees on data-efficiency to the empirical which yields practical, scalable algorithms.
Eric Mitchell
Areas of Interest: NLP, Responsible AI
Email: em7@stanford.edu
Research Focus: My research makes language-based systems more trustworthy and reliable for end users.
George Halal
Areas of Interest: Computer Vision
Email: georgech@stanford.edu
Research Focus: Using AI to model the complex 3D geometry of magnetic fields in our Galaxy
Hancheng Cao
Areas of Interest: Human Centered and Creative AI, NLP, human AI interaction
Email: hanchcao@stanford.edu
Research Focus: I am a human centered AI researcher, and I am interested in developing methods , to understand, evaluate and design computing systems.
Haochen Zhang
Areas of Interest: NLP, Responsible AI, Theoretical ML
Email: jhaochen@stanford.edu
Research Focus: Advancing self-supervised learning algorithms through theory-driven approaches for interpretable and enhanced representation learning.
Honglin Chen
Areas of Interest: Computational Education, Computer Vision
Email: honglinc@stanford.edu
Research Focus: World modeling, self-supervisied learning from videos, physical scene understanding
Ieva Daukantas
Areas of Interest: Biomedicine and Health, Computational Neuro Science, Responsible AI
Email: ieva.daukantas@gmail.com
Research Focus: AI models robustness and correctness
Isabel Papadimitriou
Areas of Interest: NLP
Email: isabelvp@stanford.edu
Research Focus: I research how language models learn and represent language, and how this relates to human linguistic cognition
Jackie (Junrui) Yang
Areas of Interest: Human Centered and Creative AI
Email: jackiey@stanford.edu
Research Focus: I work on AI-based development framework (programming libraries, development environments, novel input devices) for multimodal interactions.
Jen Weng
Areas of Interest: Computer Vision
Email: zzweng@stanford.edu
Research Focus:3D computer vision and machine learning with a focus on 3D reconstruction and human pose understanding to enable improved perception and reasoning about 3D scenes.
John Hewitt
Areas of Interest: NLP
Email: johnhew@stanford.edu
Research Focus: Understanding and improving language models by discovery and design
Jonathan N. Lee
Areas of Interest: Reinforcement Learning, Theoretical ML
Email: jnl@stanford.edu
Research Focus: Foundation Models for Decision-Making, Reinforcement Learning
Kaidi Cao
Areas of Interest: Computer Vision, Graph NN, NLP
Email: kaidicao@cs.stanford.edu
Research Focus: Enhancing machine learning with data-efficient methods.
Katherine Tsai
Areas of Interest: Computational Neuro Science, Responsible AI, Theoretical ML
Email: tsaikl@stanford.edu
Research Focus: My research focuses on estimating networks from high-dimensional time-series with neuroscience applications.
Lingjiao Chen
Areas of Interest: Human Centered and Creative AI, NLP, General ML
Email: lingjiao@stanford.edu
Research Focus: How to Use AI/ML
Margalit Glagsow
Areas of Interest: Theoretical ML
Email: mglasgow@stanford.edu
Research Focus: I study deep learning theory: why, when, and how will gradient descent on neural networks find good solutions?
Mikaela Angelina Uy
Areas of Interest: Computer Vision, Graphics
Email: mikacuy@stanford.edu
Research Focus: I work on the intersection of 3D vision, geometry processing, graphics and machine learning, specifically, I am interested in diving into different representations of 3D objects and scenes for various downstream tasks such as deformation, reconstruction, controllable generation and variation synthesis.
Pratyusha Ria Kalluri
Areas of Interest: Human Centered and Creative AI, NLP, Responsible AI
Email: pkalluri@stanford.edu
Research Focus: Weaving humanistic and scientific inquiry, I reveal that AI technologies are currently contributing to larger, overwhelmingly power-centralizing projects; in parallel, I study sites of resistance.
Rachel Luo
Areas of Interest: Computer Vision, NLP, Robotics
Email: rsluo@cs.stanford.edu
Research Focus: I work on improving the reliability and safety of autonomous systems that operate in unstructured, uncertain, and dynamic real-world environments.
Robin Brown
Areas of Interest: Graph NN, Robotics, Theoretical ML
Email: rabrown1@stanford.edu
Research Focus: My research is focused on developing hybrid algorithms that utilize non-conventional computing architectures, with a goal to provide insights for co-designing “hardware primitives” and optimization algorithms, particularly in the context of neural network verification and other problems in robotics.
Rohan Taori
Areas of Interest: NLP
Email: rtaori@cs.stanford.edu
Research Focus: Ingredients for Accessible and Sustainable Language Models
Sanath Kuma Krishnamurthy
Areas of Interest: Human Centered and Creative AI, Reinforcement Learning, Theoretical ML
Email: sanathsk@stanford.edu
Research Focus: Developing uncertainty-aware personalized decision-making systems.
Sang Michael Xie
Areas of Interest: Human Centered and Creative AI, NLP, Responsible AI
Email: xie@cs.stanford.edu
Research Focus: Large-scale data-centric machine learning methods for language models.
Scott Fleming
Areas of Interest: Biomedicine and Health, NLP, Responsible AI
Email: scottyf@cs.stanford.edu
Research Focus: Large Language Models for Improving Clinical Decision Making
Serina Chang
Areas of Interest: Graph NN, Human Centered and Creative AI, NLP
Email: serinac@stanford.edu
Research Focus: I develop machine learning and network science methods to tackle complex societal challenges (e.g., pandemics, supply chains).
Shiori Sagawa
Areas of Interest: NLP, Responsible AI
Email: ssagawa@cs.stanford.edu
Research Focus: My research develops algorithms and evaluations for reliable machine learning.
Sydney Katz
Areas of Interest: Computer Vision, Responsible AI, Robotics
Email: smkatz@stanford.edu
Research Focus: My research is focused on the safe use of machine learning in high stakes settings.
Xinru Hua
Areas of Interest: Computer Vision, Statistical ML, Generative ML
Email: huaxinru@stanford.edu
Research Focus: My research focuses on efficient algorithms for robust learning, gradient flows, and diffusion generation of rare events.
Yifeng Jiang
Areas of Interest: Human Centered and Creative AI, Robotics, Human Movements, Physics Simulations
Email: yifengj@stanford.edu
Research Focus: Integrating deep learning and physics simulation methodologies for digital and real-world applications
Yusuf Roohani
Areas of Interest: Biomedicine and Health, Graph NN, NLP
Email: yroohani@stanford.edu
Research Focus: Foundation models for predicting cell behavior and identifying optimal interventions