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<!DOCTYPE HTML>
<html>
<head>
<!-- Google analytics tag (gtag.js) -->
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<!-- Title -->
<title>Kay - Physical Intelligence</title>
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<body id="body">
<div id="main">
<div id="intro">
<div id="intro-text">
<h1>Kay - Liyiming Ke</h1>
<p>
Hi 👋 I work at <a href="https://www.physicalintelligence.company/">Physical Intelligence</a>
researching on Machine Learning for Robot Manipulation.
During my PhD at University of Washington, I built a chopsticks-welding robot to showcase data-driven fine
motor skills.
My path to robotics started unconventionally—I majored in Economics before diving into AI, with internships at
Meta AI, Microsoft Research, and Google Search along the way. I’m driven by curiosity and currently I aim to
design robot policies that master Robustness, Precision, and Dexterity.
<br><br>
<!-- In PhD program:
Hi :wave: I am Liyiming Ke, 柯丽一鸣, or "Kay". I am a final-year grad student at University of Washington, advised by [Siddhartha Srinivasa](https://goodrobot.ai/). I research on Robotics :robot: Learning, with a focus on **Data-Driven Fine Manipulation**.
As a test-bed for pushing the limit of fine manipulation, I built [a chopsticks robot](https://goodcherrybot.github.io/) to showcase the _precision_ and _dynamic reactivity_ of systems trained via reinforcement learning. I have also developed theories like [f-divergence framework for imitation learning and adversarial imitation learning](https://arxiv.org/abs/1905.12888) and [leveraging local-continuity in dynamics](https://arxiv.org/pdf/2310.12972).
I was very fortunate to work with [Abhishek Gupta](https://homes.cs.washington.edu/~abhgupta/), [Tapomayukh Bhattacharjee](https://robotics.cornell.edu/faculty/tapomayukh-bhattacharjee-bio/), [Byron Boots](https://homes.cs.washington.edu/~bboots/) and [Sanjiban Choudary](https://sanjibanchoudhury.com/).
-->
<div id="more-bio" style="display: None">
<br>
<p>Liyiming Ke is a full stack robotist at Physical Intelligence researching on Machine Learning for Robot
Manipulation. She earned her Ph.D. from the University of Washington with her thesis titled "Data-driven
Fine Manipulation". She built a chopsticks-welding robot that demonstrate fine motor skills and developed
theoretical frameworks for robot learning. She has led human-robot interactive demonstration at AAAS in 2020
and has been selected as one of the Rising Stars in EECS 2023.</p>
</div>
<br>
<a href="javascript:toggle_bio()">Formal Bio</a>
<a href="https://scholar.google.com/citations?user=EhOtO3cAAAAJ">G. Scholar</a>
<a href="https://github.com/kelym">Github</a>
<a href="https://www.linkedin.com/in/kelym/">LinkedIn</a>
<a href="https://x.com/xkelym">Twitter</a>
<br><br>
kay at workplace dot company
<br><br>
</p>
</div>
<div id="intro-image">
<img src="images/profile.jpg">
</div>
</div>
<div id="filters" class="button-group">
<!-- <button class="button" data-filter="*">Show All</button> -->
<button class="button is-checked" data-filter=".highlight">Highlights</button>
<button class="button" data-filter=".publication">Research</button>
<button class="button" data-filter=".talk">Talks</button>
<button class="button" data-filter=".misc">Misc</button>
</div>
<div class="grid">
<!-- Highlights -->
<div class="list-item highlight description" data-category="highlight">
<!-- Some recent highlights from our research:-->
</div>
<!-- Preview Videos -->
<div class="list-item highlight previews" data-category="highlight">
<a href="https://personalrobotics.github.io/CCIL/"><video class="preview3" playsinline="" muted="" autoplay=""
loop="">
<source src="images/20241101-ccil-applied.mp4" type="video/mp4">
</video></a>
<a href="https://www.physicalintelligence.company/blog/pi0"><video class="preview1" playsinline="" muted=""
autoplay="" loop="">
<source src="images/20241101-pizero_bussing_trashpile.mp4" type="video/mp4">
</video></a>
<a href="https://goodcherrybot.github.io/"><video class="preview2" playsinline="" muted="" autoplay="" loop="">
<source src="images/20230315-cherrybot-granola_retry.mp4" type="video/mp4">
</video></a>
</div>
<!-- Truncated Set of Highlights (Shown by Default) -->
<div id="main-highlights">
<!--
<div class="list-item highlight" data-category="highlight">
<b>some place</b> <a href="some link">some award</a>
</div>
-->
</div>
<!-- All Archived Highlights (Click to Show) -->
<div id="more-highlights" style="display: None">
<div class="list-item highlight" data-category="highlight">
<p class="date">2024</p> <a href="https://personalrobotics.github.io/CCIL/">Can we improve robustness of
Imitation Learning by generating synthetic corrective labels?</a>
</div>
<div class="list-item highlight" data-category="highlight">
<p class="date">2024</p> <a href="https://www.physicalintelligence.company/blog/pi0">Can imitation learning
benefits from large-scale pre-training on diverse task and robot embodiment?</a>
</div>
<div class="list-item highlight" data-category="highlight">
<p class="date">2023</p> <a href="https://goodcherrybot.github.io/">Can we learn fine motor
skills like picking up cherries with chopsticks using reinforcement learning?</a>
</div>
<div class="list-item highlight" data-category="highlight">
<p class="date">2020</p> <a href="https://arxiv.org/abs/1905.12888">Viewing imitation learning from the frame
of
divergence minimization</a>
</div>
<!-- <div class="list-item highlight" data-category="highlight">
<p class="date">Year</p> Stuff <a href="link">link</a>
</div> -->
</div>
<!-- Toggle highlights button. -->
<div class="list-item highlight toggle-button" data-category="highlight">
<a id="toggle_highlights_button" href="javascript:toggle_highlights()">Show more</a>
</div>
<!-- Publications -->
<div class="list-item publication" data-category="publication">
<a href="https://www.physicalintelligence.company/blog/pi0" class="thumbnail">
<video playsinline="" muted="" autoplay="" loop="" width="180px">
<source src="images/20241101-pizero.mp4" type="video/mp4">
</video>
</a>
<div class="project-description">
<h3><a href="https://www.physicalintelligence.company/blog/pi0">π0: A Vision-Language-Action Flow
Model for
General Robot Control</a></h3>
<p>
Kevin Black, Noah Brown, Danny Driess, Adnan Esmail, Michael Equi, Chelsea Finn, Niccolo Fusai,
Lachy Groom, Karol Hausman, Brian Ichter, Szymon Jakubczak, Tim Jones, <b>Liyiming Ke</b>, Sergey Levine,
Adrian Li-Bell, Mohith Mothukuri, Suraj Nair, Karl Pertsch, Lucy Xiaoyang Shi, James Tanner, Quan Vuong,
Anna Walling, Haohuan Wang, Ury Zhilinsky<br>
<!--<i>Venue 2024</i><br>-->
<a href="https://www.physicalintelligence.company/download/pi0.pdf">PDF</a> •
<span class="excerpt-container">
<a href="#">Summary</a>
<span class="excerpt-content">
Can you train cross-embodiment robotic policies over many many tasks and expect it to work? We show that
it is promising: a big pre-training model can be finetuned on a single task and outperform
dedicated policy that has only seen task-specific data.
</span>
</span>
</p>
</div>
</div>
<div class="list-item publication" data-category="publication">
<a href="https://arxiv.org/abs/2410.20254" class="thumbnail">
<img src="images/20241101-sim2real.jpg" alt="" />
</a>
<div class="project-description">
<h3><a href="https://arxiv.org/abs/2410.20254">Overcoming the Sim-to-Real Gap: Leveraging Simulation to Learn
to Explore for Real-World RL</a></h3>
<p>
Andrew Wagenmaker, Kevin Huang, <b>Liyiming Ke</b>, Byron Boots, Kevin Jamieson, Abhishek Gupta<br>
<i>NeurIPS 2024</i><br>
<a href="https://arxiv.org/abs/2410.20254">PDF</a> •
<span class="excerpt-container">
<a href="#">Summary</a>
<span class="excerpt-content">
We show that, learning an exploration policy in simulation can boost the real-world reinforcement
learning
finetuning efficiency (versus learning an optimal policy in the sim and transfer the policy).
</span>
</span>
</p>
</div>
</div>
<div class="list-item publication" data-category="publication">
<a href="https://arxiv.org/abs/2405.19307" class="thumbnail">
<video playsinline="" muted="" autoplay="" loop="" width="180px">
<source src="images/20241101-ccil-applied.mp4" type="video/mp4">
</video>
</a>
<div class="project-description">
<h3><a href="https://arxiv.org/abs/2405.19307">Data Efficient Behavior Cloning for Fine Manipulation via
Continuity-based Corrective Labels</a></h3>
<p>
Abhay Deshpande, <b>Liyiming Ke</b>, Quinn Pfeifer, Abhishek Gupta, Siddhartha S. Srinivasa<br>
<i>In submission 2024</i><br>
<a href="https://personalrobotics.github.io/CCIL/">Webpage</a> •
<a href="https://arxiv.org/abs/2405.19307">PDF</a> •
<span class="excerpt-container">
<a href="#">Summary</a>
<span class="excerpt-content">
We apply CCIL to real world robotic manipulation tasks and it kinda worked after some design tweak. The
most juice comes from setting up trust threshold for the generated labels in a task-agnostic way.
</span>
</span>
</p>
</div>
</div>
<div class="list-item publication" data-category="publication">
<a href="https://arxiv.org/abs/2310.12972v1" class="thumbnail">
<img src="images/20231019-ccil.png" alt="" />
</a>
<div class="project-description">
<h3><a href="https://arxiv.org/abs/2310.12972v1">CCIL: Continuity-based Data Augmentation for Corrective
Imitation Learning</a></h3>
<p>
<b>Liyiming Ke*</b>, Yunchu Zhang*, Abhay Deshpande, Siddhartha Srinivasa, Abhishek Gupta<br>
<i>International Conference on Learning Representations (ICLR) 2024</i><br>
<a href="https://personalrobotics.github.io/CCIL/">Webpage</a> •
<a href="https://github.com/personalrobotics/CCIL">Code</a> •
<a href="https://arxiv.org/abs/2310.12972v1">PDF</a> •
<span class="excerpt-container">
<a href="#">Summary</a>
<span class="excerpt-content">
Enhances robustness of imitation learning by generating synthetic corrective labels:
The trick is to leverage local continuity in the environment dynamics - and for regions that are
discontinuous, quantify the confidence and skip them.
</span>
</span>
</p>
</div>
</div>
<div class="list-item publication" data-category="publication">
<a href="https://goodcherrybot.github.io/" class="thumbnail">
<video playsinline="" muted="" autoplay="" loop="" width="180px">
<source src="images/20230315-cherry-picking.mp4" type="video/mp4">
</video>
</a>
<div class="project-description">
<h3><a href="https://goodcherrybot.github.io/">Cherry Picking with Reinforcement Learning</a></h3>
<p>
Yunchu Zhang*, <b>Liyiming Ke*</b>, Abhay Deshpande, Abhishek Gupta, Siddhartha Srinivasa<br>
<i>Robotics Science and Systems (RSS) 2023</i><br>
<a href="https://goodcherrybot.github.io/">Webpage</a> •
<a href="https://arxiv.org/abs/2303.05508">PDF</a> •
<span class="excerpt-container">
<a href="#">Summary</a>
<span class="excerpt-content">
Use reinforcement learning to learn fine motor skills: pick up slippery cherries with chopsticks under
wind or human disturbances. And I refuse to do parameter sweeping or random seed cherry picking.
</span>
</span>
</p>
</div>
</div>
<div class="list-item publication" data-category="publication">
<a href="https://sites.google.com/view/real-orl" class="thumbnail">
<img src="images/20220930-real-offlinerl.png" alt="" />
</a>
<div class="project-description">
<h3><a href="https://sites.google.com/view/real-orl">Real World Offline Reinforcement Learning with Realistic
Data Sources</a></h3>
<p>
Gaoyue Zhou*, <b>Liyiming Ke*</b>, Siddhartha Srinivasa, Abhinav Gupta, Aravind Rajeswaran, Vikash Kumar<br>
<i>IEEE International Conference on Robotics and Automation (ICRA) 2023</i><br>
<a href="https://sites.google.com/view/real-orl">Webpage</a> •
<a href="https://arxiv.org/abs/2210.06479">PDF</a> •
<span class="excerpt-container">
<a href="#">Summary</a>
<span class="excerpt-content">
Eval offline RL in real-world: emphasize on data being "kinda good" but not perfect.
</span>
</span>
</p>
</div>
</div>
<div class="list-item publication" data-category="publication">
<a href="https://personalrobotics.cs.washington.edu/publications/ke2021grasping.pdf" class="thumbnail">
<img src="images/20201101-chopsticks-grasping.jpg" alt="" />
</a>
<div class="project-description">
<h3><a href="https://personalrobotics.cs.washington.edu/publications/ke2021grasping.pdf">Grasping with
Chopsticks: Combating Covariate Shift in Model-free Imitation Learning for Fine Manipulation</a></h3>
<p>
<b>Liyiming Ke</b>, Jingqiang Wang, Tapomayukh Bhattacharjee, Byron Boots, Siddhartha S. Srinivasa<br>
<i>IEEE International Conference on Robotics and Automation (ICRA) 2021</i><br>
<a href="https://arxiv.org/abs/2011.06719">PDF</a> •
<span class="excerpt-container">
<a href="#">Summary</a>
<span class="excerpt-content">
Teach a robot to use chopsticks for precise manipulation tasks through human demonstrations: Addresses
covariate shift in imitation learning by noise-injection, object-centric transformation and
bunch of hacks.
</span>
</span>
</p>
</div>
</div>
<div class="list-item publication" data-category="publication">
<a href="https://personalrobotics.cs.washington.edu/publications/ke2020teleop.pdf" class="thumbnail">
<img src="images/20200630-chopsticks-teleop.gif" alt="" />
</a>
<div class="project-description">
<h3><a href="https://personalrobotics.cs.washington.edu/publications/ke2020teleop.pdf">Telemanipulation with
Chopsticks: Analyzing Human Factors in User Demonstrations</a></h3>
<p>
<b>Liyiming Ke</b>, Ajinkya Kamat, Jingqiang Wang, Tapomayukh Bhattacharjee, Christoforos Mavrogiannis,
Siddhartha S. Srinivasa<br>
<i>IEEE International Conference on Intelligent Robots and Systems (IROS) 2020</i><br>
<a href="https://arxiv.org/abs/2008.00101">PDF</a> •
<span class="excerpt-container">
<a href="#">Summary</a>
<span class="excerpt-content">
Built a chopsticks robot and a fun human-interactive demo collection interface: turns out that tracking
a
wand and commmand the robot can be really easy.
</span>
</span>
</p>
</div>
</div>
<div class="list-item publication" data-category="publication">
<a href="https://arxiv.org/abs/1905.12888" class="thumbnail">
<img src="images/20190608-fimitation-teaser.png" alt="" />
</a>
<div class="project-description">
<h3><a href="https://arxiv.org/abs/1905.12888">Imitation Learning as f-Divergence Minimization</a></h3>
<p>
<b>Liyiming Ke</b>, Sanjiban Choudhury, Matt Barnes, Wen Sun, Gilwoo Lee, Siddhartha Srinivasa<br>
<i>International Workshop on the Algorithmic Foundations of Robotics (WAFR) 2020</i><br>
<a href="https://arxiv.org/abs/1905.12888">PDF</a> •
<span class="excerpt-container">
<a href="#">Summary</a>
<span class="excerpt-content">
A unified theoretical framework for imitation learning! Turns out some SOTA algorithms are using
f-divergence. We show how different divergence measures lead to different imitation learning approaches.
</span>
</span>
</p>
</div>
</div>
<div class="list-item publication" data-category="publication">
<a href="http://openaccess.thecvf.com/content_CVPR_2019/html/Ke_Tactical_Rewind_Self-Correction_via_Backtracking_in_Vision-And-Language_Navigation_CVPR_2019_paper.html"
class="thumbnail">
<img src="images/20190607-vln-teaser.png" alt="" />
</a>
<div class="project-description">
<h3><a
href="http://openaccess.thecvf.com/content_CVPR_2019/html/Ke_Tactical_Rewind_Self-Correction_via_Backtracking_in_Vision-And-Language_Navigation_CVPR_2019_paper.html">Tactical
Rewind: Self-Correction via Backtracking in Vision-and-Language Navigation</a></h3>
<p>
<b>Liyiming Ke</b>, Xiujun Li, Yonatan Bisk, Ari Holtzman, Zhe Gan, Jingjing Liu, Jianfeng Gao, Yejin Choi,
Siddhartha Srinivasa<br>
<i>IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2019</i><br>
<font color="49bf9"><i>★ Oral Presentation, CVPR (5.6%) ★</i></font><br>
<a href="https://arxiv.org/abs/1903.02547">PDF</a> •
<span class="excerpt-container">
<a href="#">Summary</a>
<span class="excerpt-content">
Baking Search and Planning into ML-based navigation: We propose a new framework for VL navigation,
enabling agents to recover from mistakes by maintaining internal search tree and returning to previous
positions and trying alternative
paths.
</span>
</span>
</p>
</div>
</div>
<div class="list-item publication" data-category="publication">
<a href="https://ojs.aaai.org/index.php/AAAI/article/view/10061" class="thumbnail">
<img src="images/20160101-email-teaser.png" alt="" />
</a>
<div class="project-description">
<h3><a href="https://ojs.aaai.org/index.php/AAAI/article/view/10061">Behavioral Experiments in Email Filter
Evasion</a></h3>
<p>
<b>Liyiming Ke</b>, Bo Li, Yevgeniy Vorobeychik<br>
<i>AAAI Conference on Artificial Intelligence (AAAI) 2016</i><br>
<a href="https://ojs.aaai.org/index.php/AAAI/article/view/10061">PDF</a> •
<span class="excerpt-container">
<a href="#">Summary</a>
<span class="excerpt-content">
Studies how humans attempt to evade email spam filters.
Provides insights into adversarial behavior and implications for security system design.
</span>
</span>
</p>
</div>
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<p class="date">2024</p>OpenAI Reading Group
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<p class="date"></p>University of Washington, Robotics Seminar (<a
href="https://www.youtube.com/watch?v=LeHYQVR8a8k">video</a>)
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<p class="date">2023</p>Stanford University, <a href="https://iliad.stanford.edu/">ILIAD Lab</a>
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<p class="date"></p>University of California Berkeley, <a href="https://bair.berkeley.edu/">BAIR Lab</a>
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<p class="date"></p>Carnegie Mellon University, <a href="https://www.cs.cmu.edu/~cga/">Atkeson Lab</a>
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<p class="date"></p>Shanghai Jiaotong University, <a href="https://automation.sjtu.edu.cn/">Department of
Automation</a>
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<p class="date"></p>Stanford University, <a href="https://iprl.stanford.edu/">Interactive Perception and Robot
Learning Lab</a>
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<p class="date">2022</p>Cornell University, <a href="https://emprise.cs.cornell.edu/">EmPRISE
Lab</a>
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<p class="date"></p> <a href="https://mila.quebec/en/">Mila - Quebec AI Institute</a> (<a
href="https://www.youtube.com/watch?v=LeHYQVR8a8k">video</a>)
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<p class="date">2021</p>MetaAI Reading Group
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<p class="date">2018</p>Microsoft Research Dialogue Group Reading Group
</div>
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<div class="list-item misc" data-category="misc">
<p class="date"> </p>Reviewer of AAMAS, CoRL, HRI, ICLR, ICRA, IJRR, IROS, NeurIPS, RA-L
</div>
<div class="list-item misc" data-category="misc">
<p class="date">2023</p>Honored to be selected as one of the <a
href="https://www.eecs.mit.edu/community-equity/rising-stars-in-eecs/">Rising Stars in EECS</a>
</div>
<div class="list-item misc" data-category="misc">
<p class="date">2020</p>Chopsticks Robot featured on <a
href="https://spectrum.ieee.org/video-friday-agility-robotics-robot-production">IEEE Spectrum Video
Friday</a>
</div>
<div class="list-item misc" data-category="misc">
<p class="date">2020</p>Led a human-robot interactive demo at the <a
href="https://www.aaas.org/events/2020-aaas-annual-meeting">AAAS
gathering</a>
</div>
<div class="list-item misc" data-category="misc">
<p class="date">2017</p>Graduated as one of the <a href="https://my.vanderbilt.edu/collegescholars/">Honor
Scholars</a> from Vanderbilt University
</div>
<div class="list-item misc" data-category="misc">
<p class="date">2015</p>First prize in the Vanderbilt Student Consulting for Non-profit Organization
</div>
<div class="list-item misc" data-category="misc">
<p class="date"> - </p>Inspired by:
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<li style="display: inline;"><a href="https://distill.pub/">Distill</a></li>
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<li style="display: inline;"><a href="https://colah.github.io/">Colah's Blog</a></li>
<li style="display: inline;"> • </li>
<li style="display: inline;"><a href="http://neuralnetworksanddeeplearning.com/">Michael Nielsen</a></li>
<li style="display: inline;"> • </li>
<li style="display: inline;"><a href="https://karpathy.github.io/">Andrej Karpathy</a></li>
<li style="display: inline;"> • </li>
<li style="display: inline;"><a href="https://danielseita.github.io/">Seita's Place</a></li>
<li style="display: inline;"> • </li>
<li style="display: inline;"><a href="https://www.ruder.io/">Sebastian Ruder</a></li>
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