Office: DC 3124
Cell: 657-c0mpsci (657-206-7724)
Email: ?@csail.mit.edu, but replace ? with the first letter of my first name
Links to: CV (as of August 2022);
My group is The Salon.
Feel free to send me comments anonymously here. Note that, by design, I won't be able to respond -- if you need me to, it's better handled via email, or leaving some way for me to reply.
I am unable to respond to requests for internships or graduate admission applications from outside the university.
If you do feel compelled to contact me in this way, I am far more likely to remember you if you demonstrate that you have genuinely engaged with my work.
Instead, I recommend that you apply for graduate studies through the standard channels.
I am an Assistant Professor at the University of Waterloo's Cheriton School of Computer Science, and a faculty affiliate at the Vector Institute.
I run The Salon.
I'm interested in reliable and trustworthy statistics and machine learning, including considerations such as data privacy and robustness.
I was a Microsoft Research Fellow at the Simons Institute for the Theory of Computing for the Fall 2018 semester program on Foundations of Data Science and the Spring 2019 semester program on Data Privacy: Foundations and Applications.
Before that, I completed my Ph.D. at MIT, affiliated with the Theory of Computing group in CSAIL.
I was very fortunate to be advised by Costis Daskalakis.
Before MIT, I spent four wonderful years at Cornell University, graduating in May 2012 with a degree in Computer Science and Electrical and Computer Engineering.
At Cornell, I was incredibly lucky to have the opportunity to work with Bobby Kleinberg.
- (8/17/22) New paper on arXiv: Private Estimation with Public Data.
- (8/15/22) I will be a reviewer for ICBINB 2022.
- (8/11/22) I will be an AC for ICLR 2023.
- (8/9/22) I was on Nathan Harms' PhD thesis committee.
- (7/19/22) I'm an ethical reviewer for NeurIPS 2022.
- (7/11/22) I'm giving a few talks in the upcoming weeks, at an operations research summer school (7/21, virtual), our Fields workshop on privacy (7/29, in Toronto), at Facebook (8/3, virtual), at University of Victoria (8/25, Victoria), and UBC (8/29, Vancouver).
- (6/28/22) I am serving on the PhD thesis commitees of Bailey Kacsmar and Tim Dockhorn.
- (6/27/22) I will be giving an invited talk at ICORS on robust estimation for random graphs.
- (6/27/22) I will be on the Master's thesis committees of Haolin Yu and Emily Lepert.
- (6/24/22) I gave a talk at Google on private fine-tuning of large language models.
- (6/6/22) New paper on arXiv: Per-Instance Privacy Accounting for Differentially Private Stochastic Gradient Descent.
- (5/25/22) I will be on the program committee of FOCS 2023.
- (5/17/22) New paper on arXiv: New Lower Bounds for Private Estimation and a Generalized Fingerprinting Lemma.
- (5/15/22) One paper accepted to ICML 2022 with a long talk.
- (5/14/22) Three papers (1, 2, 3) accepted to COLT 2022.
- (5/11/22) I gave an invited tutorial at IWCIT 2022 on differential privacy. Slides are available here.
- (4/22/22) Calibration with Privacy in Peer Review accepted to ISIT 2022.
- (4/21/22) New paper on arXiv: Indiscriminate Data Poisoning Attacks on Neural Networks.
- (4/20/22) I will be on the program committee of SaTML 2023.
- (4/1/22) I will be a reader of Xinda Li's Master's thesis, and on Kelly Ramsay's PhD thesis committee.
- (3/31/22) One paper accepted to FORC 2022, non-archival track.
- (3/30/22) I will be an area chair for NeurIPS 2022.
- (3/28/22) I'm giving talks at Waterloo's Probability seminar and University of Washington's theory seminar.
- (3/18/22) Organizing two workshops at ICML 2022: TPDP 2022 and UpML 2022.
- (3/15/22) I gave a talk at the Simons Data Privacy Reunion.
- (3/1/22) I will give a (virtual) talk at Huawei Montreal on March 11.
- (2/28/22) I will attending a Apple workshop on differential privacy on April 5 and 6.
- (2/24/22) I gave a (virtual) talk at UMass Amherst's ML and Friends Lunch.
- (2/3/22) Efficient Mean Estimation with Pure Differential Privacy via a Sum-of-Squares Exponential Mechanism accepted to STOC 2022.
- (1/27/22) New paper on arXiv: Calibration with Privacy in Peer Review.
- (1/20/22) Differentially Private Fine-tuning of Language Models accepted to ICLR 2022.
Most authorships are in alphabetical order, as is common in areas of computer science.
Papers with contribution-order authorship are indicated, and equal contributions are marked with * or ^.
Generally, these will put the students as first-author, with equal contribution amongst the senior authors.
ⓡ is used for randomized author order.
Selected Papers (Show all)
- Differentially Private Fine-tuning of Language Models.
Da Yu, Saurabh Naik, Arturs Backurs*, Sivakanth Gopi*, Huseyin A. Inan*, Gautam Kamath*, Janardhan Kulkarni*, Yin Tat Lee*, Andre Manoel*, Lukas Wutschitz*, Sergey Yekhanin*, Huishuai Zhang*. (Contribution order)
Proceedings of the 10th International Conference on Learning Representations (ICLR 2022).
Selected Workshop Papers (Show)
- Calibration with Privacy in Peer Review.
Wenxin Ding, Gautam Kamath ⓡ Weina Wang ⓡ Nihar B. Shah.
AAAI 2022 Workshop on Privacy-Preserving Artificial Intelligence (PPAI 2022). Oral Presentation.
- Private Hypothesis Selection.
Mark Bun, Gautam Kamath, Thomas Steinke, Zhiwei Steven Wu.
CCS 2019 Workshop on Theory and Practice of Differential Privacy (TPDP 2019). Oral Presentation.
Sever: A Robust Meta-Algorithm for Stochastic Optimization.
Ilias Diakonikolas, Gautam Kamath, Daniel M. Kane, Jerry Li, Jacob Steinhardt, Alistair Stewart.
NeurIPS 2018 Workshop on Security in Machine Learning (SECML 2018). Oral Presentation.
Priv'IT: Private and Sample Efficient Identity Testing.
Bryan Cai, Constantinos Daskalakis, Gautam Kamath.
ICML 2017 Workshop on Private and Secure Machine Learning 2017 (PSML 2017). Oral Presentation.
Here are some videos of talks I've given.
My (74) co-authors include:
Clément L. Canonne,
Samuel B. Hopkins,
Huseyin A. Inan,
Daniel M. Kane,
Yin Tat Lee,
Nihar B. Shah,
Ananda Theertha Suresh,
Zhiwei Steven Wu,
They originate from a number of countries, including Argentina, Australia, Austria, Brazil, Bulgaria, Canada, China, France, Greece, India, Iran, Israel, Latvia, New Zealand, Russia, Turkey, United Kingdom, United States of America.
- I have been (or will be) a general chair for the following conferences: STOC 2020.
- I have been (or will be) program chair for the following workshops: TPDP 2021, TPDP 2022, UpML 2022.
- I have been (or will be) on the core program committee or an area chair for the following conferences: SODA 2020, ICML 2020, ICALP 2020, Random 2020,ALT 2021, ICLR 2021, FORC 2021, COLT 2021, CCS 2021, ESA 2021, NeurIPS 2021, SODA 2022, ICLR 2022, ALT 2022, AAAI 2022, COLT 2022, NeurIPS 2022, SaTML 2023, FOCS 2023, ICLR 2023.
- I have been (or will be) on the program committee (i.e., a reviewer) of the following machine learning conferences: NIPS 2016, ICML 2018, NeurIPS 2018, AISTATS 2019, ICML 2019, NeurIPS 2019, AAAI 2020, AISTATS 2020, FAccT 2021.
- For completeness, conferences I have reviewed for include: AAAI, AISTATS, ALT, COLT, FAccT, FOCS, ICALP, ICML, ISAAC, ISIT, ITCS, NeurIPS, RANDOM, SODA, STACS, STOC.
- I have (or will be) on the program committee of the following workshops: TPDP 2019, PriML 2019, TPDP 2020, PPML 2020, PriML 2021, ICBINB 2021, ICBINB 2022.
- I am a maintainer of the CS Theory Blog Aggregator, along with Arnab Bhattacharyya and Suresh Venkatasubramanian.
- Clément Canonne and I organized a workshop called "A TCS Quiver" at FOCS 2019.
- Clément Canonne and I organized a workshop on distribution testing at FOCS 2017.
- Clément Canonne and I organized a workshop on orthogonal polynomials at FOCS 2016.
- I'm an editor for the MIT Theory of Computation Student Blog and Property Testing Review.
- I'm one of the organizers of TCS+, an online seminar series in theoretical computer science, accessible to the widest possible audience, and ensuring a carbon-free dissemination of ideas across the globe.
- I organized the second Sublinear Day, which was on April 10, 2015 at MIT.
- I was the head organizer for the Second Annual Danny Lewin MIT Theory Student Retreat, which took place in October 2013.
Aloni and Themis wrote a bit about this retreat here.
- From Fall 2012 to Fall 2013, I was in charge of the Theory Group lunch, which was the current incarnation of Great Ideas in Theoretical Computer Science at CSAIL.
The website for the current offering is here.
I'm very lucky to work with a number of great students -- check out their profiles on my group's People page.
Here is a collection of collections of talk videos.
- TCS+: An series of online seminars in theoretical computer science.
- Simons Institute Videos: Videos from workshops hosted at the Simons Institute for the Theory of Computing.
- BIRS Videos: Videos from workshops hosted at the Banff International Research Station.
- Institute for Advanced Studies Videos: Videos from the IAS. Note that many are related to other fields besides computer science.
- Microsoft Research Talks: Talks at Microsoft Research, including a variety of topics beyond theory.
- Shannon Channel: A series of online seminars in information theory.
- Princeton TCS Videos: Videos from theory lunch and workshops within Princeton's theory group.
- Videolectures.net: Lecture videos from a number of conferences and workshops, seems to be primarily focused on machine learning events.
- I used to go by the name "G", though I now prefer Gautam. Also, my name is not Guatam Kamath, though it is commonly misspelled as such.
- My friends Aviv Adler, Greg Bodwin, and primarily Jennifer Tang, made a small puzzle hunt for my graduation. You can check out the puzzles here: 1, 2, 3, 4, 5, 6. Warning that they can be incredibly unfair if you are not me, but oh well. Try them out!