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title: lalitjain.com
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description: Lalit Jain
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    <img  class="avatar" alt="Lalit Jain" src="img/cse.jpg" width="200px" >
    <br>
    Assistant Professor <br>
    <a href="http://cs.washington.edu">Foster School of Business</a><br>
    <a href="http://washington.edu">University of Washington</a><br>
    lalitj@uw.edu<br><br>
    <button type="button" onclick="window.location.href='http://lalitjain.com/files/LalitJainCV.pdf'" class="btn btn-primary">Curriculum Vitae (PDF)</button><br>
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  	<li><a href="https://www.linkedin.com/in/lalit-jain-87ab9223">@LinkedIn</a></li>
  	<li><a href="http://github.com/lalitkumarj">@GitHub</a></li>
    <li><a href="https://scholar.google.com/citations?user=hGMSFu4AAAAJ&hl=en">Google Scholar</a></li>
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    <p class="lead" >
      Hi, I'm Lalit Jain, an Assistant Professor at the Foster School of Business, University of Washington.
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    <p> My research focuses on developing new machine learning algorithms and systems for practitioners who need to collect expensive experimental data under limited budget constraints. I combine theoretical mathematical insights with practical implementations to develop methods that effectively provide statistical insights in far fewer measurements than naive passive data collection methods. This work has been applied to many marketing applications such as optimizing crowdfunding and microlending platforms, measuring conceptual perception in cognitive psychology, detecting humor in jokes, and controlling false discovery rate in online experimental platforms.  </p>

    <p> <b>Bio:</b> Before joining the Foster School of Businees, I was a postdoc in <a href='https://homes.cs.washington.edu/~jamieson/about.html'>Professor Kevin Jamieson's group</a> and prior to that, a postdoc at the University of Michigan mentored by <a href="https://annacgilbert.github.io/">Professor Anna Gilbert</a>. My PhD in Mathematics was advised by Professor <a href="http://math.wisc.edu/~ellenber">Jordan Ellenberg</a> and  Professor <a href="http://nowak.ece.wisc.edu">Robert Nowak.</a></p>
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        <b>New Yorker Caption Contest:</b> For the last 8 years, I've been involved in running the online crowdsourced voting system for the New Yorker caption contest. Checkout the current voting page <a href="https://mlnow-newyorker.s3-us-west-2.amazonaws.com/captioncontest_s3.html">here</a>. Our extensive dataset is <a href="https://nextml.github.io/caption-contest-data/">here.</a>
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        <img src="https://nextml.github.io/caption-contest-data/cartoons/859.jpg" width="200px"> 
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        <img src="https://nextml.github.io/caption-contest-data/cartoons/862.jpg" width="200px">
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    <b> Announcements: </b>
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      <li>1/2024:  Our many-year <a href="https://arxiv.org/pdf/2402.10870.pdf"> effort on best-arm identification </a> at Amazon was accepted to WWW 2024! </li>
      <li>1/2024:  Three papers accepted to AISTATS. Congrats to <a href="https://arxiv.org/abs/2310.06069">Zhaoqi</a>, <a href="https://arxiv.org/abs/2307.15154">Romain and Zhihan</a>. Also excited to have a work on <a href="https://arxiv.org/abs/2310.18617">multi-object optimization </a>a> with Brano and the team at Amazon. </li>
      <li>12/2023: Excited to be at Neurips! Checkout <a href="https://arxiv.org/abs/2310.04390">Justin's paper</a> and the <a href="https://realworldml.github.io">Adaptive Experimentation workshop.</a> </li>
      <li>11/2023: Presenting two works at Code@MIT - our work deploying bandits at Amazon, and recent work on bandits under endogeneity. </li>
      <li>10/2023: Check out Zhaoqi's talk about our recent work on Top-Two sampling for linear bandits at Informs 2023 next week! </li>
      <li>10/2023: Congrats to Justin Weltz for his recent paper on pure exploration with heteroskedastic variance accepted at Neurips 2023!</li>
      <li>10/2023: Don't forget to submit to the Neurips 2023 workshop on <a href="https://realworldml.github.io/">Adaptive Experimental Design in the Real World!</a></li>
      <li> 9/2023: Presenting recent work on Pessimistic Multi-Objective Optimization at Amazon's RL Seminar. </li>
      <li> 8/2023: Attending the Choice Symposium in Fontainebleau.</li>
      <li> 6/2023: Presenting recent work on adaptive pricing at SICS 2023 in Berkeley</li>
      <li> 4/2023: Presenting recent work on adaptive pricing at Kellogg School of Business, Northwestern </li>
      <li> 4/2023: Teaching MKTG 596: Real World Adaptive Experimentation </li>
      <li> 6/2022: Congrats to Jennifer Brennan for the best paper award at the ICML 2022 workshop on Adaptive Experimental Design in the Real World! </li>
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