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<!DOCTYPE HTML>
<!--
Dimension by HTML5 UP
html5up.net | @ajlkn
Free for personal and commercial use under the CCA 3.0 license (html5up.net/license)
-->
<html>
<head>
<title>Lucio Mwinmaarong Dery</title>
<meta charset="utf-8" />
<meta name="viewport" content="width=device-width, initial-scale=1, user-scalable=no" />
<link rel="stylesheet" href="assets/css/main.css" />
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<div id="wrapper">
<!-- Header -->
<header id="header">
<div class="logo">
<span class="icon fa-laptop"></span>
</div>
<div class="content">
<div class="inner">
<h1>Dery Lucio</h1>
<p>
Computer Science PhD Student @
<a href="https://www.cs.cmu.edu/">Carnegie Mellon University</a>
<br></br>
</p>
</div>
</div>
<nav>
<ul>
<li><a href="#intro">Intro</a></li>
<li><a href="#work">Work</a></li>
<li><a href="#contact">Contact</a></li>
<li><a href="#blog">Art</a></li>
</ul>
</nav>
<div>
<ul class="icons">
<li><a href="https://twitter.com/derylucio" class="icon fa-twitter"><span class="label">Twitter</span></a></li>
<li><a href="https://www.facebook.com/lucio.dery" class="icon fa-facebook"><span class="label">Facebook</span></a></li>
<li><a href="https://github.com/ldery" class="icon fa-github"><span class="label">GitHub</span></a></li>
<li><a href="https://medium.com/@luciodery" class="icon fa-medium"><span class="label">Medium</span></a></li>
</ul>
</div>
</header>
<!-- Main -->
<div id="main">
<article id="intro">
<h2 class="major">Intro</h2>
<p><span class="image main"><img src="images/me_eating.jpg" alt="" /></span></p>
<p>
I am a Research Scientist at Google Deepmind working in the Fundamental Research Org. Before this, I was a PhD student in the Computer Science Department at Carnegie Mellon University co-advised by Ameet Talwalkar and Graham Neubig. Before starting my PhD, I was a Research Engineer at Facebook AI Research (FAIR) in Seattle. My current research interests broadly cover all things related to learning from multiple tasks: transfer learning, meta-learning, multi-tasking and auxiliary learning. I primarily explore these fields in the context of Natural Language Processing but the tools I develop are domain agnostic.
I have previously worked in Computer Vision (CV) - specifically CV algorithms for High Energy Physics (HEP) and Video Understanding. I did my undergrad (Physics) and Masters (Computer Science) at Stanford University.
Outside of A.I, I am very passionate about Reading, Music, Art, Neuroscience, Philosophy and Food !!.
<br>
</p>
<h3 class="major">2025 Book List</h3>
<ul>
<li>Men without women - Haruki Murakami</li>
<li>Kokoro - Natsume Soseki </li>
<li>Knife of Dreams: Wheel of Time Series - Robert Jordan </li>
<li>The Gathering Storm: Wheel of Time Series - Robert Jordan </li>
<li>Towers of Midnight: Wheel of Time Series - Robert Jordan </li>
<li>Exhalation - Ted Chiang </li>
<li>Determined - Robert Sapolsky </li>
<li>Zero to One - Peter Thiel </li>
</ul>
<h4 class="major"> In Progress </h3>
<ul>
<li>The Fall - Albert Camus </li>
<li>Special Relativity andd Classical Field Theory - Leonard Susskind and Art Friedman </li>
<li>The Sandman (Book 3) - Neil Gaiman </li>
<li>I Will Teach You To Be Rich - Ramit Sethi </li>
<li>Collected Fictions of Jorge Luis Borges </li>
</ul>
<h3 class="major">2024 Book List</h3>
<ul>
<li>How not to be wrong - Jordan Ellenberg</li>
<li>The ones who walk away from omelas - Ursula K. Le Guin </li>
<li>Algorithms to live by - Brian Christian, Thomas L. Griffiths</li>
<li>Winter's Heart: Wheel of Time Series - Robert Jordan </li>
<li>Crossroads of Twilight: Wheel of Time Series - Robert Jordan </li>
<li>The Dark Forest (Three Body Problem - Book II) - Liu Cixin</li>
<li>Death's End (Three Body Problem - Book III) - Liu Cixin</li>
<li>Parable of the Sower - Octavia Butler</li>
</ul>
<h3 class="major">2023 Book List</h3>
<ul>
<li>The Alchemist - Paulo Coelho</li>
<li>Ikigai - Hector Garcia and Francesc Miralles </li>
<li>Thinking Fast and Slow - Daniel Kahneman </li>
<li>Stories of Your Life and Others - Ted Chiang </li>
</ul>
<h3 class="major">2022 Book List</h3>
<ul>
<li>The Path of Daggers - WOT Series - Robert Jordan</li>
<li>The Hard Thing about Hard Things - Ben Horowitz</li>
<li>The Everything Store - Brad Stone</li>
<li>The Alignment Problem - Brian Christian </li>
<li>Poorly Understood: What America gets wrong about poverty - Heather E. Bullock et Al</li>
<li>Race After Technology - Ruha Benjamin</li>
<li>The Graveyard Book - Neil Gaiman</li>
<li>Dreams of a Final Theory - Steven Weinberg </li>
<li>Chaos - James Gleick </li>
<li>Existential Physics - Sabine Hossenfelder</li>
<li>The Selfish Gene - Richard Dawkins</li>
</ul>
<h3 class="major">2021 Book List</h3>
<ul>
<li>The Sandman Act I & II - Neil Gaiman</li>
<li>A Crown of Swords - WOT Series - Robert Jordan</li>
<li>Intimations - Zadie Smith</li>
<li>Project Hail Mary - Andy Weir</li>
<li>Hold Everything Dear - John Berger</li>
<li>Guns, Germs and Steel - Jared Diamond</li>
<li>Hyperbole and Half - Allie Brosh</li>
<li>Ministry For The Future - Kim Stanley Robinson </>
</ul>
<h3 class="major">2020 Book List</h3>
<p>
<ul>
<li>The Stranger - Albert Camus</li>
<li>Awards for good boys - Shelby Lorman </li>
<li>The Game - Neil Strauss </li>
<li>Predictably Irrational - Daniel Ariely </li>
<li>The Genealogy of Morals - Friedrich Nietzsche</li>
<li>The Three-Body Problem - Cixin Liu </li>
<li>Atomic Habits - James Clear </li>
<li>Modern Ethics in 77 Arguments : A Stone Reader </li>
<li>Dune - Frank Herbert </li>
</ul>
</p>
<h3 class="major">2019 Book List</h3>
<p>
<ul>
<li>Man's Search For Meaning - Viktor Frankl </li>
<li>Reductionism in Art and Brain Science - Eric R. Kandel </li>
<li>The Myth of Sisyphus - Albert Camus </li>
<li>Logic Comix - Apostolos Doxiadis, Christos Papadimitriou </li>
<li>The New Jim Crow - Michelle Alexander</li>
<li>The Fifth Season - N.K. Jemisin </li>
<li>Deep Work - Cal Newport</li>
<li>The Riddle Master Series [3 Books] - Patricia McKillip</li>
<li>His Dark Materials [3 Books] - Phillip Pullman</li>
<li>The Upward Spiral - Alex Korb</li>
<li>Portraits of Resilience - Daniel Jackson</li>
</ul>
</p>
</article>
<!-- Work -->
<article id="work">
<p>
<h3><a href="https://github.com/ldery/ldery.github.io/blob/master/latest_resume.pdf">Full CV</a></h3>
</p>
<p>
<h3 id="-education">
<i class="icon fa-chevon-right"></i>
Education
</h3>
<table class="table table-hover">
<tbody>
<tr>
<td class="col-md-3">Aug 2019 - July 2024</td>
<td>
<strong>PhD in Computer Science </strong>
<br> Carnegie Mellon University
</td>
</tr>
<tr>
<td class="col-md-3">Sept 2016 - June 2018</td>
<td>
<strong>Masters in Computer Science ** Tau Beta Pi </strong>
<br> Stanford University
</td>
</tr>
<tr>
<td class="col-md-3">Sept 2013 - June 2018</td>
<td>
<strong>Bachelors in Physics, Minor in Computer Science ** with Distinction</strong>
<br> Stanford University
</td>
</tr>
</tbody>
</table>
</p>
<p>
<h3 id="-experience">
<i class="icon fa-chevon-right"></i>
Experience
</h3>
<table class="table table-hover">
<tbody>
<tr>
<td class="col-md-3">August 2024 - </td>
<td>
<strong>Research Scientist </strong>, Google DeepMind
</td>
</tr>
<tr>
<td class="col-md-3">May 2023 - August 2023</td>
<td>
<strong>AI/ML Research Intern</strong>, Apple
</td>
</tr>
<tr>
<td class="col-md-3">March 2023 - May 2023</td>
<td>
<strong>Student Researcher</strong>, Google Research
</td>
</tr>
<tr>
<td class="col-md-3">May 2022 - August 2022</td>
<td>
<strong>Research Scientist Intern</strong>, DeepMind
</td>
</tr>
<tr>
<td class="col-md-3">July 2020 - August 2020</td>
<td>
<strong>Research Scientist Intern</strong>, Google Brain - Google
</td>
</tr>
<tr>
<td class="col-md-3">July 2018 - July 2019</td>
<td>
<strong>Research Engineer</strong>, Facebook A.I Research - Facebook
</td>
</tr>
<tr>
<td class="col-md-3">June 2017 - Sept 2017</td>
<td>
<strong>Software Engineering Intern</strong>, Applied Machine Learning - Facebook
</td>
</tr>
<tr>
<td class="col-md-3">June 2016 - Sept 2016</td>
<td>
<strong>Software Engineering Intern</strong>, Terra Bella - Google
</td>
</tr>
<tr>
<td class="col-md-3">June 2015 - Sept 2015</td>
<td>
<strong>Software Engineering Intern</strong>, Google Analytics - Google
</td>
</tr>
</tbody>
</table>
</p>
<p>
<h3 id="2025-publications">
<i class="icon fa-chevon-right"></i>
2026
</h3>
<table class="table table-hover">
<tbody>
<tr>
<td>
<a href="https://arxiv.org/abs/2601.06123">
<strong>Latent Space Communication Via K-V Cache Alignment </strong>
</a>
<br> <strong>Lucio Dery</strong>, Zohar Yahav, Henry Prior, Qixuan Feng, Jiajun Shen, Arthur Szlam
<br> Preprint (Under Submission)
</td>
</tr>
</tbody>
</table>
<h3 id="2025-publications">
<i class="icon fa-chevon-right"></i>
2025
</h3>
<table class="table table-hover">
<tbody>
<tr>
<td>
<a href="https://arxiv.org/pdf/2503.09799">
<strong>Communication-Efficient Language Model Training Scales Reliably and Robustly: Scaling Laws for DiLoCo </strong>
</a>
<br> Zachary Charles, Gabriel Teston, <strong>Lucio Dery</strong>, Keith Rush, Nova Fallen, Zachary Garrett, Arthur Szlam, Arthur Douillard
<br> Neurips 2025
</td>
</tr>
</tbody>
</table>
<h3 id="2024-publications">
<i class="icon fa-chevon-right"></i>
2024
</h3>
<table class="table table-hover">
<tbody>
<tr>
<td>
<a href="https://arxiv.org/abs/2402.05406">
<strong>Everybody Prune Now: Structured Pruning of LLMs with only Forward Passes </strong>
</a>
<br> <strong>Lucio Dery</strong>, Steven Kolawole, Jean-François Kagy, Virginia Smith, Graham Neubig, Ameet Talwalkar
<br> Preprint (under submission)
</td>
</tr>
<tr>
<td>
<a href="http://reports-archive.adm.cs.cmu.edu/anon/2024/CMU-CS-24-136.pdf">
<strong>On Resource Efficient Transfer Learning via End Task Aware Training </strong>
</a>
<br> <strong>Lucio Dery</strong>
<br> PhD Thesis
</td>
</tr>
<tr>
<td>
<a href="https://arxiv.org/abs/2311.06379">
<strong> DeMuX: Data-efficient Multilingual Learning </strong>
<!-- <img style='object-fit: fill' class="image fit" src="images/generate.png" alt=""/> -->
</a>
<br>Simran Khanuja, Srinivas Gowriraj, <strong>Lucio Dery</strong>, Graham Neubig
<br> NAACL 2024
</td>
</tr>
<tr>
<td>
<a href="https://arxiv.org/pdf/2312.03151.pdf">
<strong> Multitask Learning can improve robustness to worst group outcomes </strong>
<!-- <img style='object-fit: fill' class="image fit" src="images/generate.png" alt=""/> -->
</a>
<br> Atharva Kulkarni*, <strong>Lucio Dery*</strong>, Amrith Setlur, Aditi Raghunathan, Ameet Talwalkar, Graham Neubig
<br> TMLR 2024
<br> SSL Theory and Practice Workshop NeurIPS 2023
</td>
</tr>
</tbody>
</table>
<h3 id="2023-publications">
<i class="icon fa-chevon-right"></i>
2023
</h3>
<table class="table table-hover">
<tbody>
<tr>
<td>
<a href="https://arxiv.org/abs/2311.06382">
<strong> Tranfer Learning for Structured Pruning under Limited Data </strong>
<!-- <img style='object-fit: fill' class="image fit" src="images/generate.png" alt=""/> -->
</a>
<br> <strong>Lucio Dery</strong>, Awni Hannun, David Grangier
<br> ENLSP Workshop NeurIPS 2023
</td>
</tr>
<tr>
<td>
<a href="https://arxiv.org/abs/2302.05738">
<strong> Cross-Modal Fine-Tuning: Align then Refine </strong>
<!-- <img style='object-fit: fill' class="image fit" src="images/generate.png" alt=""/> -->
</a>
<br> Junhong Shen, Liam Li, <strong>Lucio Dery</strong>, Corey Staten, Mikhail Khodak, Graham Neubig, Ameet Talwalkar.
<br> ICML 2023 <strong>(Oral)</strong>
</td>
</tr>
<tr>
<td>
<a href="https://arxiv.org/abs/2205.14082">
<strong>AANG: Automating Auxiliary Learning </strong>
<!-- <img style='object-fit: fill' class="image fit" src="images/generate.png" alt=""/> -->
</a>
<!-- <strong>AANG: Automating Auxiliary Learning </strong> -->
<br> <strong>Lucio Dery</strong>, Paul Michel, Mikhail Khodak, Graham Neubig, Ameet Talwalkar.
<br> ICLR 2023 <strong>(Spotlight)</strong>
</td>
</tr>
</tbody>
</table>
<h3 id="2022-publications">
<i class="icon fa-chevon-right"></i>
2022
</h3>
<table class="table table-hover">
<tbody>
<tr>
<td>
<a href="https://arxiv.org/abs/2210.04971">
<strong>Multi-step Planning for Automated Hyperparameter Optimization with OptFormer </strong>
<!-- <img style='object-fit: fill' class="image fit" src="images/plan_viz.png" alt=""/> -->
</a>
<!-- <strong>Multi-step Planning for Automated Hyperparameter Optimization with OptFormer </strong> -->
<br> <strong>Lucio Dery</strong>, Abram L. Friesen, Nando De Freitas, Marc'Aurelio Ranzato, Yutian Chen
<br> <a href="https://sites.google.com/view/fmdm-neurips/">Workshop on Foundation Models For Decision Making - NeurIPS 2022 </a>
</td>
</tr>
<tr>
<td>
<a href="https://arxiv.org/pdf/2109.07437.pdf">
<strong>Should we be <i>Pre</i>-Training ? An Argument for End-Task Aware Training as an Alternative </strong>
<!-- <img style='object-fit: fill' class="image fit" src="images/eatmt.png" alt=""/> -->
</a>
<!-- <strong>Should we be <i>Pre</i>-Training ? An Argument for End-Task Aware Training as an Alternative </strong> -->
<br> <strong>Lucio Dery</strong>, Paul Michel, Ameet Talwalkar, Graham Neubig
<br> ICLR, 2022
</td>
</tr>
</tbody>
</table>
<h3 id="2021-publications">
<i class="icon fa-chevon-right"></i>
2021
</h3>
<table class="table table-hover">
<tbody>
<tr>
<td>
<a href="https://openreview.net/forum?id=1GTma8HwlYp">
<strong>Auxiliary Task Update Decomposition : The Good, The Bad and The Neutral </strong>
<!-- <img style='object-fit: contain' class="image fit" src="images/attitud_img.png" alt=""/> -->
</a>
<!-- <strong>Auxiliary Task Update Decomposition : The Good, The Bad and The Neutral </strong> -->
<br> <strong>Lucio Dery</strong>, David Grangier, Yann Dauphin
<br> ICLR, 2021
</td>
</tr>
</tbody>
</table>
<h3 id="2018-publications">
<i class="icon fa-chevon-right"></i>
2018
</h3>
<table class="table table-hover">
<tbody>
<tr>
<td>
<a href="http://openaccess.thecvf.com/content_cvpr_2018/papers/Shlizerman_Audio_to_Body_CVPR_2018_paper.pdf">
<strong>Audio to Body Dynamics</strong>
<!-- <img style='object-fit: contain' class="image fit" src="images/aud_to_bod.png" alt=""/> -->
</a>
<!-- <strong>Audio to Body Dynamics</strong> -->
<br> Eli Shlizerman, <strong>Lucio Dery</strong>, Hayden Schoen, Ira Kemelmacher. “Audio to Body Dynamics.”
<br> CVPR, 2018
</td>
</tr>
<tr>
<td>
<a href="http://openaccess.thecvf.com/content_cvpr_2018/papers/Huang_Finding_It_Weakly-Supervised_CVPR_2018_paper.pdf">
<strong>Finding ‘It’: Weakly-Supervised Reference-Aware Visual Grounding in Instructional Video </strong>
<!-- <img style='object-fit: contain' class="image fit" src="images/ramil.png" alt=""/> -->
</a>
<!-- <strong>Finding ‘It’: Weakly-Supervised Reference-Aware Visual Grounding in Instructional Video </strong> -->
<br> D.A-Huang, Shyamal Buch, <strong>Lucio Dery</strong>, Animesh Garg, Li Fei-Fei, Juan Carlos Niebles
<br> CVPR, 2018 <strong>(Oral)</strong>
</td>
</tr>
</tbody>
</table>
<h3 id="2017-publications">
<i class="icon fa-chevon-right"></i>
2017
</h3>
<table class="table table-hover">
<tbody>
<tr>
<td>
<a href="https://link.springer.com/article/10.1007/JHEP05(2017)145">
<strong>Weakly supervised classification in high energy physics</strong>
<!-- <img style='object-fit: contain' class="image fit" src="images/hep.png" alt=""/> -->
</a>
<!-- <td> -->
<!-- <strong>Weakly supervised classification in high energy physics</strong> -->
<br> <strong>Lucio Dery </strong>, Benjamin Nachman, Francesco Rubbo, Ariel Schwartzman
<br> Journal of High Energy Physics 2017.5 (2017): 1-11
<!-- </td> -->
</td>
</tr>
</tbody>
</table>
</p>
<p>
<h3 id="-teaching">
<i class="icon fa-chevon-right"></i>
Teaching
</h3>
<table class="table table-hover">
<tbody>
<tr>
<td class="col-md-3">Fall 2023</td>
<td>
<strong>Teaching Assistant, Machine learning with large datasets (10-605)</strong> Carnegie Mellon University
</td>
</tr>
<tr>
<td class="col-md-3">Fall 2022</td>
<td>
<strong>Teaching Assistant, Advanced Natural Language Processing (11-711)</strong> Carnegie Mellon University
</td>
</tr>
<tr>
<td class="col-md-3">Winter 2018</td>
<td>
<strong>Head Teaching Assistant, Deep Learning (CS230)</strong> Stanford University
</td>
</tr>
<tr>
<td class="col-md-3">Spring 2018</td>
<td>
<strong>Course Assistant, Deep Learning (CS230)</strong> Stanford University
</td>
</tr>
<tr>
<td class="col-md-3">Fall 2017</td>
<td>
<strong>Course Assistant, Machine Learning (CS229)</strong> Stanford University
</td>
</tr>
<tr>
<td class="col-md-3">Winter 2014 - Spring 2017</td>
<td>
<strong>Section Leader, Programming Abstactions (CS106A)</strong> Stanford University
</td>
</tr>
<tr>
<td class="col-md-3">Winter 2014 - Spring 2017</td>
<td>
<strong>Section Leader, Programming Methodology (CS106B) </strong> Stanford University
</td>
</tr>
</tbody>
</table>
</p>
</article>
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<h3> Email : </h3>
<p>ldery [at] andrew [dot] cmu [dot] edu</p>
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Working on getting better at drawing and painting ! I hope I find the time. Here's some random artwork I've made in the past
<p>
<h3>Art</h3>
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<img src="images/pencil1.jpg">
<img src="images/pencil2.jpg">
<img src="images/pencil3.jpg">
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<img src="images/charcoal1.jpg">
<img src="images/charcoal2.jpg">
<img src="images/charcoal3.jpg">
<img src="images/pencil4.jpg">
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<img src="images/paint1.jpg">
<img src="images/pencil6.jpg">
<img src="images/pencil5.jpg">
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