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<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN">
<html>
<head>
<link rel="stylesheet" type="text/css" href="style/style.css">
</style>
<link rel="icon" type="image/png" href="img/jhu.png">
<title>Enayat Ullah</title>
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<body>
<table width="800" border="0" align="center" cellspacing="0" cellpadding="0">
<tr>
<td>
<table width="100%" align="center" border="0" cellspacing="0" cellpadding="20">
<tr>
<td width="67%" valign="middle">
<p align="center">
<name>Enayat Ullah</name> </br>
</font>
<em>    [email protected]</em></a>
<font id="covermail"><font id="email" style="display:inline;">
<noscript><i>Please enable Javascript to view.</i></noscript>
</font></font>
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<p align>I am a Research Scientist at <a href = "http://meta.com"> Meta</a>. I am interested in various theoretical and practical aspects of Machine Learning, Optimization and Differential Privacy. </p>
<p align> Previously, I was a
Ph.D. student in the department of Computer Science at the <a href="htts://www.jhu.edu"> Johns Hopkins University</a>, advised by <a href="https://www.cs.jhu.edu/~raman/Home.html"> Raman Arora</a>. Before that,
<!-- </p> -->
<!-- <p align> -->
I graduated from the <a href="https://www.iitk.ac.in/">Indian Intitute of Technology Kanpur</a> with a Bachelors and Masters degree in Mathematics and Computing, with minors in Computer Science and English Literature.
At IIT Kanpur, I worked with <a href = "http://www.cse.iitk.ac.in/users/purushot/">Purushottam Kar</a>, <a href="http://home.iitk.ac.in/~kundu/kundu.html">Debasis Kundu</a> and <a href = "http://prateekjain.org">Prateek Jain.</a> </p>
I have undertaken internships and visits at <a href = "https://research.google/"> Google Research</a>, with <a href = "https://kairouzp.github.io/"> Peter Kairouz </a>, <a href="https://homes.cs.washington.edu/~sewoong/">Sewoong Oh</a> and <a href="https://www.christopherchoquette.com/">Christopher Choquette-Choo</a>; <a href = "https://research.adobe.com/"> Adobe Research</a>, with <a href="https://sites.google.com/site/anupraob/">Anup Rao</a>, <a href = "https://sites.google.com/view/tungtmai/">Tung Mai</a>, and <a href="http://ryanrossi.com/">Ryan Rossi</a>; the <a href="https://www.ias.edu/">Institute for Advanced Study, Princeton</a>, in the <a href="https://www.ias.edu/math/sp/Optimization_Statistics_and_Theoretical_Machine_Learning#:~:text=Theoretical%20Machine%20Learning-,Special%20Year%20on%20Optimization%2C%20Statistics%2C%20and%20Theoretical%20Machine%20Learning,2020%20(Distinguished%20Visiting%20Professor)">Special Year on Optimization, Statistics, and Theoretical Machine Learning</a> program and the <a href="https://simons.berkeley.edu/">Simons Institute for the Theory of Computing</a> in the <a href="https://simons.berkeley.edu/programs/games2022">Learning and Games</a> program.
<br>
<p align=center>
</p>
</td>
<td width="33%"><img class="image-cropper" src="img/photo.jpg"></td>
</tr>
</table>
<table width="100%" align="center" border="0" cellspacing="0" cellpadding="20">
<table width="100%" align="center" border="0" cellspacing="0" cellpadding="20">
<tr>
<td>
<heading>Publications/Preprints</heading>
</td>
</tr>
<tr >
<td valign="top" width="100%">
<p><a href='https://arxiv.org/pdf/2403.03856.pdf'>
<papertitle>Public-data Assisted Private Stochastic Optimization: Power and Limitations</papertitle></a>
<br> with Michael Menart, Raef Bassily, Cristóbal Guzmán, Raman Arora <br>
<em> (Under Submission)</em>
</td>
</tr>
<tr >
<td valign="top" width="100%">
<p><a href='https://arxiv.org/pdf/2311.13447.pdf'>
<papertitle>Differentially Private Non-Convex Optimization under the KL Condition with Optimal Rates</papertitle></a>
<br> with Michael Menart, Raman Arora, Raef Bassily, Cristóbal Guzmán<br>
<em>Algorithmic Learning Theory (ALT), 2024</em>
</td>
</tr>
<tr >
<td valign="top" width="100%">
<p><a href='https://openreview.net/pdf?id=gQ4h6WvME0' onclick="return false;">
<papertitle>Optimistic rates for Multi-task Representation Learning</papertitle></a>
<br> with Austin Watkins, Thanh Nguyen-Tang, Raman Arora<br>
<em>Neural Information Processing Systems (NeurIPS), 2023</em>
</td>
</tr>
<tr >
<td valign="top" width="100%">
<p><a href='https://arxiv.org/pdf/2307.10999.pdf'>
<papertitle>Private Federated Learning with Autotuned Compression</papertitle></a>
<br> with Christopher A. Choquette-Choo, Peter Kairouz, Sewoong Oh<br>
<em>International Confernce on Machine Leraning (ICML), 2023</em>
</td>
</tr>
<tr >
<td valign="top" width="100%">
<p><a href='https://arxiv.org/pdf/2307.11228.pdf'>
<papertitle>From Adaptive Query Release to Machine Unlearning</papertitle></a>
<br> with Raman Arora<br>
<em>International Confernce on Machine Leraning (ICML), 2023</em>
<br><em>Workshop on Updatable Machine Leraning, 2022</em></br>
</td>
</tr>
<tr >
<td valign="top" width="100%">
<p><a href="https://arxiv.org/abs/2206.00846">
<papertitle>Faster Rates of Convergence to Stationary Points in Differentially Private Optimization</papertitle></a>
<br> with Raman Arora, Raef Bassily, Tomás González, Cristóbal Guzmán, Michael Menart <br>
<em>International Confernce on Machine Leraning (ICML), 2023</em>
</td>
</tr>
<tr >
<td valign="top" width="100%">
<p><a href="https://arxiv.org/abs/2205.03014">
<papertitle>Differentially Private Generalized Linear Models Revisited</papertitle></a>
<br> with Raman Arora, Raef Bassily, Cristóbal Guzmán, Michael Menart <br>
<em>Neural Information Processing Systems (NeurIPS), 2022</em>
<br><em>Theory and Practice of Differential Privacy (TPDP), 2022 </em><br>
</td>
</tr>
<tr >
<td valign="top" width="100%">
<p><a href="https://arxiv.org/abs/2207.00411">
<papertitle>Adversarial Robustness is at odds with Lazy Training</papertitle></a>
<br> with Yunjuan Wang, Poorya Mianjy, Raman Arora<br>
<em>Neural Information Processing Systems (NeurIPS), 2022</em>
</td>
</tr>
<tr >
<td valign="top" width="100%">
<p><a href="https://openreview.net/pdf?id=TzRXyO3CzX">
<papertitle>Clustering with Approximate Nearest Neighbour Oracles</papertitle></a>
<br>with Harry Lang, Raman Arora, Vladimir Braverman<br>
<em>Transactions of Machine Lerning (TMLR), 2022</em>
</td>
</tr>
<tr >
<td valign="top" width="100%">
<p><a href="https://openreview.net/pdf?id=KwWKB9Bqam">
<papertitle>Generalization Bounds for Kernel Canonical Correlation Analysis</papertitle></a>
<br>with Raman Arora<br>
<em>Transactions of Machine Leraning (TMLR), 2022</em>
</td>
</tr>
<tr >
<td valign="top" width="100%">
<p><a href="https://arxiv.org/abs/2102.13179">
<papertitle>Machine Unlearning via Algorithmic Stability</papertitle></a>
<br> with Tung Mai, Anup Rao, Ryan Rossi, Raman Arora<br>
<em>Conference on Leraning Theory (COLT), 2021,
<br><em> Foundations of Responsible Computing (FORC), 2021</em></br>
</td>
</tr>
<tr >
<td valign="top" width="100%">
<p><a href="https://arxiv.org/abs/2007.07682">
<papertitle>FetchSGD: Communication-efficient Federated learning with Sketching</papertitle></a>
<br> with Daniel Rothchild, Ashwinee Panda, Nikita Ivkin, Vladimir Braverman, Joseph Gonzalez, Ion Stoica, Raman Arora<br>
<em>International Confernce on Machine Leraning (ICML), 2020</em>
</td>
</tr>
<tr >
<td valign="top" width="100%">
<p><a href="https://arxiv.org/abs/1808.00934">
<papertitle>Communication-efficient Distributed SGD with Sketching</papertitle></a>
<br>with Nikita Ivkin, Daniel Rothchild, Vladimir Braverman, Ion Stoica, Raman Arora<br>
<em>Neural Information Processing Systems (NeurIPS), 2019</em>
</td>
</tr>
<tr >
<td valign="top" width="100%">
<p><a href="https://arxiv.org/abs/1808.00934">
<papertitle>Improved Algorithms for Time-Decay Streams</papertitle></a>
<br>with Vladimir Braverman, Harry Lang, Samson Zhou <em>
</em> <br>
<em>International Conference on Approximation Algorithms for Combinatorial Optimization Problems (APPROX), 2019</em>
</td>
</tr>
<tr>
<td valign="top" width="100%">
<p><a href="https://arxiv.org/abs/1808.00934">
<papertitle>Streaming Kernel PCA with \(\tilde O(\sqrt{n})\) Random Features</papertitle></a>
<br>with Poorya Mianjy, Teodor V Marinov, Raman Arora<br>
<em>Neural Information Processing Systems (NeurIPS), 2018</em>
</td>
</tr>
<!-- <tr >
<td valign="top" width="100%">
<p><a href="">
<papertitle>Convergence Guarantees for ADAM and RMSProp in Non-Convex Optimization ..</papertitle></a>
<br><em>(\( \alpha\)-\(\beta\) order)</em> Amitabh Basu, Soham De, Anirbit Mukherjee, <b>Enayat Ullah</b><br>
<em>(Under Submission)</em>
<br> <a href = "https://arxiv.org/abs/1807.06766v1">arXiv</a> <br>
</td>
</tr> -->
</tabble>
<table width="100%" align="center" border="0" cellspacing="0" cellpadding="20">
<tr>
<td>
<heading>Service</heading>
</td>
</tr>
<tr >
<td valign="top" width="100%">
Program Committe
<br> <a href="https://tpdp24.cs.uchicago.edu/"> Theory and Practice of Differetial Privacy (TPDP), 2024</a></br>
<a href ="https://upml2022.github.io/"> Workshop on Updatable Machine Learning, 2022 </a>
<br>Reviewer</br>
ICML, NeurIPS, ICLR, AISTATS
</td>
</tr>
</table>
<table width="100%" align="center" border="0" cellspacing="0" cellpadding="2">
<tr >
<br>
<p align="right"><font size="2">
<a href="http://www.cs.berkeley.edu/~barron/">website</a>
<a href="http://i-am-karan-singh.github.io/"> credits</a>
</font>
</p>
</td>
</tr>
</table>
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