Maithra Raghu
PhD Student @ Cornell CS and Google Brain
Welcome! I am a PhD student in Computer Science at Cornell University, where I am very fortunate to be advised by Jon Kleinberg. I am currently doing extended research with the Google Brain Team, where my mentors are Quoc Le and Samy Bengio. In the past, I’ve collaborated with Jascha Sohl-Dickstein and Surya Ganguli at Stanford.
Before Cornell, I was at the University of Cambridge (Trinity College) where I completed my Bachelors and Masters (Part III of the Tripos) in Mathematics. Prior to that I was very fortunate to spend my final years in high school competing in national and international mathematical Olympaids. The highlight was being part of the UK team at the China Girls Math Olympiad.
Research Interests
My research interests are broadly in machine learning, particularly deep learning. A specific research goal is to develop the Science of Deep Learning: understand and improve deep neural networks by combining systematic experiments with principled methods to provide robust conclusions. I am also interested in using these insights in healthcare applications.
news
| Sep 12, 2019 | Selected Talks Invited talks at O’Reilly’s AI Conference, Simons Institute Frontiers of Deep Learning, Stanford’s HealthAI Hackathon, WiML |
| Jun 9, 2019 | Selected Awards: Honored to be one of the Forbes 30 Under 30 in Science and named one of the MIT Rising Stars in EECS. |
- Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness of MAML
- Aniruddh Raghu*, Maithra Raghu*, Samy Bengio, Oriol Vinayls (*equal contribution)
- Preprint
- Transfusion: Understanding Transfer Learning with Applications to Medical Imaging
- Maithra Raghu*, Chiyuan Zhang*, Jon Kleinberg†, Samy Bengio† (*equal contribution) (†equal contribution)
- Neural Information Processing Systems (NeurIPS), 2019
- The Algorithmic Automation Problem: Prediction, Triage and Human Effort
- Maithra Raghu, Katy Blumer, Greg Corrado, Jon Kleinberg, Ziad Obermeyer, Sendhil Mullainathan
- Preprint
- Direct Uncertainty Prediction for Medical Second Opinions
- Maithra Raghu*, Katy Blumer*, Rory Sayres, Ziad Obermeyer, Sendhil Mullainathan, Jon Kleinberg (*equal contribution)
- International Conference on Machine Learning (ICML), 2019
- Insights on Representational Similarity in Neural Networks with Canonical Correlation
- Adversarial Spheres
- Justin Gilmer, Luke Metz, Fartash Faghri, Samuel S. Schoenholz, Maithra Raghu, Martin Wattenberg, Ian Goodfellow
- Preprint
- Appeared in International Conference on Learning Representations (ICLR) Workshop, 2018
- Can Deep Reinforcement Learning Solve Erdos-Selfridge-Spencer Games?
- Maithra Raghu, Alex Irpan, Jacob Andreas, Robert Kleinberg, Quoc V. Le, Jon Kleinberg
- International Conference on Machine Learning (ICML), 2018
- Also appeared in International Conference on Learning Representations (ICLR) Workshop, 2018
- Code
- SVCCA: Singular Vector Canonical Correlation Analysis for Deep Learning Dynamics and Interpretability
- Explaining the Learning Dynamics of Direct Feedback Alignment
- Justin Gilmer, Colin Raffel, Samuel S. Schoenholz, Maithra Raghu, Jascha Sohl-Dickstein
- Appeared in International Conference on Learning Representations (ICLR) Workshop, 2017
- On the Expressive Power of Deep Neural Networks
- Maithra Raghu, Ben Poole, Jon Kleinberg, Surya Ganguli, Jascha Sohl-Dickstein
- International Conference on Machine Learning (ICML), 2017
- Video
- Linear Additive Markov Processes
- Ravi Kumar, Maithra Raghu, Tamas Sarlos, Andrew Tomkins (alphabetical order)
- World Wide Web Conference (WWW), 2017
- Exponential expressivity in deep neural networks through transient chaos
- Ben Poole, Subhaneil Lahiri, Maithra Raghu, Jascha Sohl-Dickstein, Surya Ganguli
- Advances in Neural Information Processing Systems (NIPS) 2016
- Team Performance with Test Scores
- Jon Kleinberg, Maithra Raghu (alphabetical order)
- Economics and Computation (EC) 2015
- Invited to special issue of ACM Transactions on Economics and Computation, 2018