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    <title>Heterogeneous Systems &#187; HetSys Cohort Newsfeed &#187; Informal Seminar: Molecular Dynamics in Differentiable Languages</title>
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    <description>The latest posts to Heterogeneous Systems &#187; HetSys Cohort Newsfeed &#187; Informal Seminar: Molecular Dynamics in Differentiable Languages</description>
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    <lastBuildDate>Wed, 14 Oct 2026 14:27:02 GMT</lastBuildDate>
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      <title>Informal Seminar: Molecular Dynamics in Differentiable Languages</title>
      <link>https://warwick.ac.uk/fac/sci/hetsys/studentinformationhub/externalopportunites/?post=8ac672c4a12e128b01a13acf3e4c2e76</link>
      <description>&lt;p&gt;&lt;strong&gt;Tuesday 20th October 14.00-15.00 B2.02 (Sci Conc)&lt;/strong&gt;&lt;/p&gt; 
&lt;p&gt;Dear Cohorts 4, 5, 6 and 7 -&amp;nbsp;&lt;/p&gt; 
&lt;p&gt;Please join us for this informal seminar, followed by coffee - sign up below so that we have an idea of numbers please &lt;span contenteditable="false" title="Smile" type="(smile)" class="animated-emoticon-20-smile"&gt;&lt;img itemtype="http://schema.skype.com/Emoji" itemid="smile" title="Smile" alt="&#x1f642;" src="https://statics.teams.cdn.office.net/evergreen-assets/personal-expressions/v2/assets/emoticons/smile/default/20_f.png" style="width: 20px; height: 20px;"&gt;&lt;/span&gt;&lt;/p&gt; 
&lt;p&gt;&lt;a href="https://warwick.ac.uk/fac/sci/hetsys/newsandevents/seminar/" itemtype="http://schema.skype.com/HyperLink" rel="noreferrer noopener" title="https://warwick.ac.uk/fac/sci/hetsys/newsandevents/seminar/" target="_blank" itemid="4102caf3-8bed-4476-9d27-43c83fa258a4"&gt;https://warwick.ac.uk/fac/sci/hetsys/newsandevents/seminar/&lt;/a&gt;&lt;br&gt;&lt;br&gt;&lt;strong&gt;Speaker: &lt;/strong&gt;Abhijeet Gangan&lt;br&gt;&lt;strong&gt;Title: &lt;/strong&gt;Molecular dynamics in differentiable languages: lessons from JAX-MD and TorchSim&lt;br&gt;&lt;br&gt;&lt;strong&gt;Abstract:&lt;/strong&gt; JAX and PyTorch are popular languages for ML applications, but they can also be used to build simulation engines for molecular dynamics. In this presentation, I will discuss my experience developing JAX-MD and TorchSim to show what this approach provides: automatic differentiation, batching, just-in-time compilation and native support for machine-learned potentials.&lt;br&gt;&lt;br&gt;I will also discuss the limitations, such as static-shape array operations being a poor fit for dynamic neighbour lists and variable system sizes, which can lead to recompilation, memory overhead and irregular memory access. Finally, I will outline the path ahead for performance, covering topics like custom kernels and coupling JAX/PyTorch models to production MD codes such as LAMMPS and OpenMM.&lt;br&gt;&lt;br&gt;&lt;strong&gt;Bio:&lt;/strong&gt; I currently work as a Member of Technical Staff at Periodic Labs. Before that, I completed my PhD at UCLA, during which I also worked at Radical AI and Lawrence Livermore National Laboratory. My work is focused on developing atomistic simulation codes and machine-learned interatomic potentials.&lt;/p&gt; 
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      <pubDate>Wed, 14 Oct 2026 14:27:02 GMT</pubDate>
      <author>Sarah Jarratt</author>
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