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<html>
<script src="header.js"></script>
[<a href="#interests"><font face="Times New Roman" size="3">Interests</font></a><font face="Times New Roman" size="3">]
[<a href="#experiences"><font face="Times New Roman" size="3">Experiences</font></a><font face="Times New Roman" size="3">]
[</font><a href="pubs.html" target="_self"><font face="Times New Roman" size="3">Publications</font></a><font face="Times New Roman" size="3">]
[<a href="#activities"><font face="Times New Roman" size="3">Professional Activities</font></a><font face="Times New Roman" size="3">]
<hr>
<a name="interests">
<h2>Interests</h2>
My core research interest is in machine learning for interactive systems that maximizes a utility function by taking actions, which is in contrast to prediction-oriented machine learning like supervised learning. I am working on <b>large language models</b>, <b>reinforcement learning</b>, <b>contextual bandits</b>, and related areas. I have applied my work to recommendation, Web search, advertising, and conversational systems.
<p>
Most of my work can be grouped into several clusters:
<ul>
<li><a href="projects/exploration.html">Exploration (<b>data collection</b> in RL)</a>
<li><a href="projects/vfa.html">Value function and policy learning (<b>training</b> in RL)</a>
<li><a href="projects/off-policy.html">Off-policy learning (<b>evaluation</b> in RL)</a>
<li><a href="projects/app-web.html">Applications to the Web</a>
<li><a href="projects/app-nlp.html">Applications to NLP</a>
</ul>
</p>
<p>
More information can be found in <a href="https://scholar.google.com/citations?user=Rqy5KDEAAAAJ&hl=en&authuser=1">Google Scholar</a>, <a href="http://dblp.uni-trier.de/pers/hd/l/Li:Lihong">DBLP</a>, <a href="https://www.linkedin.com/in/lihong-li-9620164/">LinkedIn</a>.<p/>
Somewhat up-to-date <a href="cv-lihong.pdf">CV</a>, and <a href="bio.html">short bio</a>.<p/>
I am also on Twitter as <a href="https://twitter.com/lihongli20">@LihongLi20</a>.
<p></p><hr>
<a name="experiences">
<h2>Experiences</h2>
<ul>
<li>2020 - present: Senior Principal Scientist, Amazon
<li>2017 - 2020: Research Scientist, Google Research
<li>2012 - 2017: Senior, Principal, Sr Principal Researcher, Microsoft Research
<li>2009 - 2012: Research Scientist, Yahoo! Research
<li>2009: PhD in Computer Science, Rutgers University
<li>2004: MSc in Computing Science, University of Alberta
<li>2002: BE in Computer Science and Technology, Tsinghua University
</ul>
<p></p><hr>
<a name="activities">
<h2> Professional Activities</h2>
<ul>
<li>Recent and upcoiming events
<ul>
<b>
</b>
<li>[2024/01] Panel at the AAAI 2024 Workshop: <a href="https://sites.google.com/view/rl-llm-aaai2024">Synergy of Reinforcement Learning and Large Language Models</a>, Vancouver, Canada.
<li>[2023/09] <a href="https://www.nae.edu/294989/Innovative-EarlyCareer-Engineers-Selected-to-Participate-in-The-Grainger-Foundation-Frontiers-of-Engineering-2023-Symposium-of-the-National-Academy-of-Engineering-">Grainger Foundation Frontiers of Engineering 2023 Symposium</a> of the National Academy of Engineering, at the Univ of Colorado.
<li>[2023/05] Amazon Science & Technology Summit in San Francisco.
<li>[2023/05] Seoul Test of Time Award by IW3C2, for our WWW'2010 paper on contextual bandits for personalized recommendation. See <a href="https://www.amazon.science/news-and-features/lihong-li-wins-2023-seoul-test-of-time-award">the article</a> by Amazon Science.
<li>[2022/01] Article by Amazon Science on how we use RL to delight customers in Amazon, and more. [<a href="https://www.amazon.science/working-at-amazon/amazon-advertising-lihong-li-using-reinforcement-learning-algorithms">link</a>]
<li>[2021/08] Invited talk at KDD Workshop on <a href="https://sites.google.com/view/marble-kdd">Multi-Armed Bandits and Reinforcement Learning</a> (with Yi Liu). [<a href="slides/slides_mapofbandits.pdf">slides</a>]
<li>[2021/07] Co-organizer of ICML Workshop on <a href="https://sites.google.com/view/RL4RealLife">RL for Real Life</a>.
<li>[2021/07] Minitutorial on <a href="https://meetings.siam.org/sess/dsp_programsess.cfm?SESSIONCODE=71887">Optimization in Policy Gradient</a> (with <a href="https://scholar.google.com/citations?user=vK0-CDcAAAAJ&hl=en">Lin Xiao</a>) at the <a href="https://www.polyu.edu.hk/ama/events/conference/op20/en/">SIAM Conference on Optimization</a>.
<li>[2021/04] Amazon Advertising opens the <a href="https://www.amazon.science/amazon-advertising-opens-applications-for-early-career-scientists">Early-career Scientist</a> program with full-time research positions. Application deadline: May 14.
<li>[2020/12/15] Invited talk at <a href="http://www.aiforeconomics.com">AI for Economics Seminar</a>.
<li>[2020/12/12] Co-organizer of NeurIPS Workshop on <a href="https://offline-rl-neurips.github.io">Offline Reinforcement Learning</a>.
<li>[2020/10] Invited talk at Department of Computer Science, University of California, Los Angeles, CA, USA.
<li>[2020/09] Co-organizer of Simons Institute's <a href="https://simons.berkeley.edu/workshops/rl-2020-1">Deep Reinforcement Learning</a> workshop, as part of the <a href="https://simons.berkeley.edu/programs/rl20">Theory of Reinforcement Learning</a> program.
<li>[2020/09] Invited talk at Department of Statistics and Data Science, Yale University, New Haven, CT, USA.
<li>[2020/04 (cancelled)] Invited talk at Reinforcement Learning workshop at the <a href="http://dalimeeting.org">DALI (Data, Learning and Inference) meeting</a>, Balearic Islands, Spain.
<li>[2019/03 (cancelled)] Invited talk at <a href="http://ee-ciss.princeton.edu">CISS</a>, Princeton, NJ, USA.
<li>[2019/12] Co-organizer of NeurIPS Workshop on the <a href="https://optrl2019.github.io">Optimization Foundations of Reinforcement Learning</a>, Vancouver, BC, Canada.
<li>[2019/10] Machine Learning Journal Special Issue on "Reinforcement Learning for Real Life". Paper deadline: March 15, 2020. Please consider submitting to it! (<a href="https://www.springer.com/journal/10994/updates/17254266">CFP</a>)
<li>[2019/10] Invited talk at University of Alberta, Edmonton, AB, Canada
<li>[2019/10] Invited talk at DeepMind, Edmonton, AB, Canada
<!-- <li>[2019/10] Invited talk at Machine Learning Summit, Google Cloud AI, Sunnyvale, CA, USA. -->
<li>[2019/08] Invited talk at Simons Institute's <a href="https://simons.berkeley.edu/workshops/dl2019-2">Emerging Challenges in Deep Learning</a> workshop.
<li>[2019/06] Co-organizer of ICML Workshop on <a href="https://sites.google.com/corp/view/RL4RealLife">RL for Real Life</a>, Long Beach, CA, USA.
<li>[2019/04] Invited talk at <a href="http://www.stat.purdue.edu/student_organizations/gso/spring-speakers/index.php">GSO Spring Seminar</a>, Department of Statistics, Purdue University, West Lafayette, IN, USA.
<li>[2018/12] Invited talk at NIPS Workshop on <a href="https://nips.cc/Conferences/2018/Schedule?showEvent=10938">Wordplay: Reinforcement and Language Learning in Text-based Games</a>, Montreal, QC, Canada.
<li>[2018/10] Invited talk at <a href="https://sites.google.com/view/maddd">MADDD</a>, University of California, Davis, CA, USA.
<li>[2018/09] Invited talk at University of Texas, Austin, TX, USA.
<li>[2018/07] Tutorial on ``Neural Approaches to Conversational AI'' (with <a href="https://www.microsoft.com/en-us/research/people/jfgao">Jianfeng Gao</a> and <a href="https://www.microsoft.com/en-us/research/people/mgalley">Michel Galley</a>) at <a href="http://acl2018.org">ACL</a>, Melbourne, Australia. [<a href="https://1drv.ms/p/s!AshEqwB44aR6k8wgo9s-Jk3-A8ZiaQ">PPT<a/>, <a href="https://1drv.ms/b/s!AshEqwB44aR6k8wfrYIJEv2sbi9IFg">PDF</a>]
<li>[2018/07] Tutorial on ``Neural Approaches to Conversational AI'' (with <a href="https://www.microsoft.com/en-us/research/people/jfgao">Jianfeng Gao</a> and <a href="https://www.microsoft.com/en-us/research/people/mgalley">Michel Galley</a>) at <a href="http://sigir.org/sigir2018">SIGIR</a>, Ann Arbor, MI, USA.
<li>[2018/07] Invited talk at <a href="https://ismp2018.sciencesconf.org">ISMP</a>, Bordeaux, France.
<li>[2018/06] Invited talk at <a href="http://meetings2.informs.org/wordpress/2018international">INFORMS</a>, Taipei.
<li>[2018/06] Invited talk at <a>Machine Learning Theory Workshop</a>, Peking University, Beijing, China.
<li>[2018/04] Guest lecture at Tsinghua University, Beijing, China.
<li>[2018/03] Invited talk at <a href="http://ee-ciss.princeton.edu">CISS</a>, Princeton, NJ, USA.
<li>[2018/02] Invited talk at Stanford University, Palo Alto, CA, USA.
<li>[2017/12] Co-organizer of NIPS Workshop on <a href="https://sites.google.com/corp/view/causalnips2017">From "What If" to "What Next"</a>, Long Beach, CA, USA.
<li>[2017/11] Co-organizer of the <a href="http://www.aifrontiers.com">AI Frontiers</a> conference, San Jose, CA, USA.
<li>[2017/09] Invited talk at Google Brain, Montreal, Canada.
<li>[2017/08] Invited talk at ICML Workshop on <a href="https://sites.google.com/corp/view/interactive-ml/home">Interactive Machine Learning and Semantic Information Retrieval</a>, Sydney, Australia.
<li>[2017/06] Invited talk at <a href="http://www.kaist.edu">Korea Advanced Institute of Science and Technology</a>, Daejeon, Korea.
<li>[2017/06] Invited talk at <a href="http://www.skku.edu">Sungkyunkwan University</a>, Suwon, Korea.
<li>[2017/06] Invited talk at <a href="http://www.rldm.org">RLDM</a>, Ann Arbor, MI, USA.
<li>[2017/05] Co-organizer of Algorithms for Reinforcement Learning Minisymposium at <a href="https://www.siam.org/meetings/op17/">SIAM Optimization Conference</a>, Vancouver, Canada.
<li>[2017/05] Invited talk at Stanford University, Palo Alto, CA, USA.
<li>[2017/05] Invited talk at New York University, New York, NY, USA.
<li>[2017/02] Invited talk at <a href="https://simons.berkeley.edu">Simons Institute</a>, Berkeley, CA, USA.
</ul>
<!--<li>Area chair and/or senior program committee member for AAAI (2017-2019), AISTATS (2017, 2019), ICLR (2019, 2022), ICML (2012-2017, 2019-2021), IJCAI (2011, 2016, 2017), NIPS/NeurIPS (2014, 2017-2021).-->
<li>Recent duties as Senior Area Chair: ICLR (2022-2024), ICML (2021-2024), NeurIPS (2021, 2023-2024), and RLC (2024).
<!--<li>Tutorial at WSDM 2015: ''Offline Evaluation and Optimization for Interactive Systems: A Practical Guide''-->
<li>Editorial board of <a href="https://jmlr.org/tmlr">Transactions on Machine Learning Research</a>; (formerly) IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI).
</ul>
<p></p><hr>
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