<div dir="ltr"><div class="gmail-group-header" style="box-sizing:inherit;font-family:Mallory,Verdana,Arial,Helvetica,sans-serif;font-size:17px"><span class="gmail-field gmail-field-name-title gmail-field-type-ds gmail-field-label-hidden" style="box-sizing:inherit"><span style="box-sizing:inherit"><span class="gmail-odd gmail-first gmail-last" style="box-sizing:inherit"><h1 class="gmail-title" style="box-sizing:inherit;font-weight:300;padding:0px;font-feature-settings:"kern","liga","dlig";font-size:1.76471em;line-height:normal;font-stretch:normal;color:rgb(0,60,118);text-transform:uppercase;display:inline-block">TAILIN WU</h1></span></span></span>, <span class="gmail-field gmail-field-name-field-university gmail-field-type-text gmail-field-label-hidden" style="box-sizing:inherit;margin-left:5px"><span style="box-sizing:inherit"><span class="gmail-odd gmail-first gmail-last" style="box-sizing:inherit">Stanford University</span></span></span><div class="gmail-field gmail-field-name-field-abstract-title gmail-field-type-text gmail-field-label-hidden" style="box-sizing:inherit"><div class="gmail-field-items" style="box-sizing:inherit"><div class="gmail-field-item even" style="box-sizing:inherit;font-size:20px;font-weight:600;line-height:1.2;margin-bottom:1em;margin-top:0.5em">Learning structured representations for accelerating scientific discovery and simulation</div></div></div></div><div class="gmail-group-left" style="box-sizing:inherit;float:left;width:auto;padding-right:15.3125px;max-width:30%;font-family:Mallory,Verdana,Arial,Helvetica,sans-serif;font-size:17px"><div class="gmail-field gmail-field-name-field-image gmail-field-type-image gmail-field-label-hidden" style="box-sizing:inherit"><div class="gmail-field-items" style="box-sizing:inherit"><div class="gmail-field-item even" style="box-sizing:inherit"><img src="https://statistics.yale.edu/sites/default/files/styles/user_picture_node/public/photo-oct-28-2022-10-20-47-copy-2-6-1024x977.jpg?itok=I9ZOMdEP" width="400" height="480" alt="" style="box-sizing: inherit; border: 0px; max-width: 100%; height: auto; vertical-align: bottom;"></div></div></div></div><div class="gmail-group-right" style="box-sizing:inherit;float:left;width:auto;max-width:65%;padding-left:22.9766px;font-family:Mallory,Verdana,Arial,Helvetica,sans-serif;font-size:17px"><div class="gmail-field gmail-field-name-field-event-time gmail-field-type-datetime gmail-field-label-hidden" style="box-sizing:inherit"><div class="gmail-field-items" style="box-sizing:inherit"><div class="gmail-field-item even" style="box-sizing:inherit;color:rgb(0,60,118);font-size:18px;line-height:1.4"><span class="gmail-date-display-single" style="box-sizing:inherit">Wednesday, February 22, 2023<span class="gmail-date-display-range" style="box-sizing:inherit;float:left;width:425.195px"><span class="gmail-date-display-start" style="box-sizing:inherit">4:00PM</span> to <span class="gmail-date-display-end" style="box-sizing:inherit">5:00PM</span></span></span></div></div></div><div class="gmail-field gmail-field-name-field-location gmail-field-type-location gmail-field-label-hidden" style="box-sizing:inherit"><div class="gmail-field-items" style="box-sizing:inherit"><div class="gmail-field-item even" style="box-sizing:inherit"><div class="gmail-location gmail-vcard" style="box-sizing:inherit"><div class="gmail-adr" style="box-sizing:inherit"><span class="gmail-fn" style="box-sizing:inherit">Mason Lab 211</span> <span class="gmail-map-icon" style="box-sizing:inherit;margin-left:0.25em;font-size:0.925em;line-height:1.55;letter-spacing:0.05em;word-spacing:0.05em;text-transform:lowercase;font-feature-settings:"smcp""><a href="http://maps.google.com/?q=9+Hillhouse+Ave%2C+New+Haven%2C+CT%2C+06511%2C+us" style="box-sizing:inherit;outline:none;line-height:inherit;color:rgb(40,109,192)">see map</a> </span><div class="gmail-street-address" style="box-sizing:inherit">9 Hillhouse Ave</div><span class="gmail-locality" style="box-sizing:inherit">New Haven</span>, <span class="gmail-region" style="box-sizing:inherit">CT</span> <span class="gmail-postal-code" style="box-sizing:inherit">06511</span></div></div></div></div></div><div class="gmail-field gmail-field-name-field-website gmail-field-type-link-field gmail-field-label-hidden" style="box-sizing:inherit"><div class="gmail-field-items" style="box-sizing:inherit"><div class="gmail-field-item even" style="box-sizing:inherit"><a href="https://tailin.org/" style="box-sizing:inherit;text-decoration-line:none;outline:none;line-height:1.5;color:rgb(0,60,118);font-size:16px">Website</a></div></div></div></div><div class="gmail-group-footer" style="box-sizing:inherit;clear:both;padding-top:15px;font-family:Mallory,Verdana,Arial,Helvetica,sans-serif;font-size:17px"><div class="gmail-field gmail-field-name-body gmail-field-type-text-with-summary gmail-field-label-above" style="box-sizing:inherit"><div class="gmail-field-label" style="box-sizing:inherit;font-weight:bold">Information and Abstract: </div><div class="gmail-field-items" style="box-sizing:inherit"><div class="gmail-field-item even" style="box-sizing:inherit"><p style="box-sizing:inherit;margin:0px 0px 1em;padding:0px"><span style="box-sizing:inherit">Across most disciplines of science, e.g., physics, chemistry, biomedicine, materials, mechanical engineering, and energy, a most critical challenge is that their simulations and discoveries are typically slow due to the large-scale, complex and multi-scale nature of the system. In this talk, I will introduce my research that tackles this challenge by developing machine learning models with structured and efficient representations for accelerating scientific discovery and simulation. To accelerate scientific discovery, I developed neuro-symbolic methods which can distill the data into human-interpretable symbolic knowledge (governing equations and relational structures) and generalize to more complex data in inference. To accelerate large-scale scientific simulations, I developed structured representations to accelerate critical scientific simulations for fluid dynamics, plasma science, and generic partial differential equations (PDEs). For example, I developed a hybrid particle-fluid representation for simulating a large-scale laser-plasma interaction in a national lab facility that has important applications in physics, materials, and biomedical science. Our model is able to simulate millions of particles per time step, orders of magnitude faster than the classical solver, and significantly reduce long-term prediction error compared to strong deep learning baselines.</span></p><p style="box-sizing:inherit;margin:0px 0px 1em;padding:0px"><strong style="box-sizing:inherit">BIO: </strong>Tailin Wu is a postdoctoral scholar in the Computer Science Department at Stanford University, working with Prof. Jure Leskovec. He received his Ph.D. from MIT Physics, where his thesis focused on AI for Physics and Physics for AI. His research interests include developing machine learning methods for large-scale scientific simulations, neuro-symbolic methods for scientific discovery, and representation learning, using tools of graph neural networks, information theory, and physics. His work has been published in top machine learning conferences and leading physics journals, and featured in MIT Technology Review. He also serves as a reviewer for high-impact journals such as PNAS, Nature Communications, Nature Machine Intelligence, and Science Advances. </p></div></div></div><div class="gmail-field gmail-field-name-field-event-description gmail-field-type-text-with-summary gmail-field-label-hidden" style="box-sizing:inherit"><div class="gmail-field-items" style="box-sizing:inherit"><div class="gmail-field-item even" style="box-sizing:inherit"><p style="box-sizing:inherit;margin:0px 0px 1em;padding:0px"><em style="box-sizing:inherit"><strong style="box-sizing:inherit">In-Person seminars will be held at Mason Lab 211, 9 Hillhouse Avenue with the option of virtual participation (</strong></em><a href="https://yale.hosted.panopto.com/Panopto/Pages/Sessions/List.aspx?folderID=f8b73c34-a27b-42a7-a073-af2d00f90ffa" rel="nofollow" style="box-sizing:inherit;outline:none;line-height:inherit;color:rgb(40,109,192);word-break:break-word">https://yale.hosted.panopto.com/Panopto/Pages/Sessions/List.aspx?folderID=f8b73c34-a27b-42a7-a073-af2d00f90ffa</a>)</p><p style="box-sizing:inherit;margin:0px 0px 1em;padding:0px"><em style="box-sizing:inherit"><strong style="box-sizing:inherit"><a href="https://0.0.0.10/" rel="nofollow" style="box-sizing:inherit;outline:none;line-height:inherit;color:rgb(40,109,192);word-break:break-word">3:30pm</a> -   Pre-talk meet and greet teatime - Dana House, 24 Hillhouse Avenue </strong></em></p></div></div></div></div></div>