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<!DOCTYPE HTML>
<html>
<head>
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<title>Tim Lin</title>
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<li><a href="mailto:"> Contact me</a></li>
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<p style="font-weight: bold;font-size:46px; color:white">Tim Lin <span style="font-weight: bold;font-size:14px; color: #ffffff80;">PhD Earth Sciences, Geophysics MS</span> </p>
<p>Postdoctoral Researcher at <span style="font-weight: bold;font-size:20px; "><a href="https://www.llnl.gov/">LLNL</a></span> formerly <span style="font-weight: bold;font-size:20px; "><a href="https://www.nasa.gov/">NASA</a></span> Earth & Space Science Fellow </p>
<p>Expertise in machine learning, computational seismology, and large-scale data analysis</p>
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<video autoplay loop muted playsinline src="images/Mountains in the fog.mp4"></video>
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<!-- <p style="font-weight: bold;font-size:32px; ">What I'm working</p> -->
<!-- <h2>What I'm working</h2> -->
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<p style="display: block;margin-block-start: 0em; margin-block-end: 2.5em; font-weight: bold; font-size:40px; text-shadow:0 0 15px rgb(20, 20, 20);">Applied Research & Methods</p>
<!-- 1. ML & DL part -->
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<p1 style="font-family:Arial, Helvetica, sans-serif; font-size:28px; text-shadow:0 0 6px rgb(20, 20, 20); transition: 0.3s"><u>Machine Learning & Deep Learning</u></p1>
</div>
<p class="research-text">
We apply machine learning and deep learning to advance earthquake early warning systems, predict ground motions, detect waveform anomalies, and uncover hidden earthquakes from noisy datasets.
</p>
<a href="https://doi.org/10.1029/2021JB022703" target="_blank" rel="noopener" class="paper-link">
📄 Paper: Deep RNN (Recurrent Neural Network) in magnitude prediction for early warning
</a>
<a href="https://doi.org/10.1785/0220240331" target="_blank" rel="noopener" class="paper-link">
📄 Paper: Deep CNN (Convolutional Neural Network) autoencoder in time series anomaly detection for health monitoring
</a>
<a href="https://doi.org/10.1029/2023JB027255" target="_blank" rel="noopener" class="paper-link">
📄 Paper: RNN in real-time rupture geometry tracking and shaking prediction
</a>
<br><br><br><br>
<!-- 2.Data Driven part -->
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<p1 style="font-family:Arial, Helvetica, sans-serif; font-size:28px; text-shadow:0 0 6px rgb(20, 20, 20); transition: 0.3s"><u>Data Driven Insights</u></p1>
</div>
<p class="research-text">
Seismology is inherently data-rich and data-driven. We analyze large-scale observational and simulated seismic data. A typical broadband three-component seismometer collects over 20–65 million data points per day, enabling deep analysis and pattern discovery at scale.
</p>
<a href="https://doi.org/10.26443/seismica.v2i4.1134" target="_blank" rel="noopener" class="paper-link">
📄 Paper: Unet CNN (Convolutional Neural Network) in earthquake signal data mining
</a>
<br><br><br><br>
<!-- 3.Physics-based part -->
<div>
<p1 style="font-family:Arial, Helvetica, sans-serif; font-size:28px; text-shadow:0 0 6px rgb(20, 20, 20); transition: 0.3s"><u>Physics-Based Modeling</u></p1>
</div>
<p class="research-text">
We simulate kinematic rupture models, seismic wave propagation, and inversion of source. These physics-based models provide insights into rupture processes and support hazard assessment.
</p>
<a href="https://doi.org/10.5281/zenodo.5015610" target="_blank" rel="noopener" class="paper-link">
📂 Dataset: Rupture simulation archived on Zenodo
</a>
<a href="https://doi.org/10.1016/j.epsl.2020.116353" target="_blank" rel="noopener" class="paper-link">
📄 Paper: Joint inverion for solving kinematic rupture processes
</a>
<br><br><br><br>
<!-- 4.HPC part -->
<div>
<p1 style="font-family:Arial, Helvetica, sans-serif; font-size:28px; text-shadow:0 0 6px rgb(20, 20, 20); transition: 0.3s"><u>High-Performance Simulation</u></p1>
</div>
<p class="research-text">
Leveraging HPC resources, we simulate realistic large earthquake ruptures and their ground motions. These simulations are vital for understanding seismic risk in urban and tectonically active regions.
</p>
</div>
</section>
<!-- <div style="border: 3px solid green; margin-left: auto;margin-right: auto;"> -->
<br> </br>
<br> </br>
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<h3 class="section-title">Portfolio</h3>
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<li data-filter=".filter-data, .filter-ML, .filter-science" class="">All</li>
<li data-filter=".filter-data" class="">Data</li>
<li data-filter=".filter-ML" class="filter-active">ML/AI</li>
<li data-filter=".filter-science" class="">Science</li>
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<a href="images/DB_map.png">
<img src="images/DB_map_small.png" alt="">
<div class="details">
<h4>Database</h4>
<span>A global earthqukae and station database</span>
</div>
</a>
</div>
<div class="col-lg-3 col-md-6 portfolio-item filter-data" style="transform: scale(0); display: none;">
<a href="images/research_4_1.png">
<img src="images/research_4_1_small.png" alt="">
<div class="details">
<h4>Simulation</h4>
<span>Rupture simulation and synthetic waveforms in Chile</span>
</div>
</a>
</div>
<div class="col-lg-3 col-md-6 portfolio-item filter-ML" style="transform: scale(1)">
<a href="images/Exp_architecture.png">
<img src="images/Exp_architecture_small.png" alt="">
<div class="details">
<h4>Deep learning on large earthquakes</h4>
<span>M-LARGE: A RNN model for large earthquake early warning</span>
</div>
</a>
</div>
<div class="col-lg-3 col-md-6 portfolio-item filter-ML" style="transform: scale(1)">
<a href="images/research_3_1.png">
<img src="images/research_3_1_small.png" alt="">
<div class="details">
<h4>Deep learning on small earthquakes</h4>
<span>A CNN U-net based model for low-frequency earthquake mining</span>
</div>
</a>
</div>
<div class="col-lg-3 col-md-6 portfolio-item filter-ML" style="transform: scale(1)">
<a href="images/research_6_1.png">
<img src="images/research_6_1_small.png" alt="">
<div class="details">
<h4>GenAI on data simulation</h4>
<span>A GAN model for synthetic earthquake and explosion</span>
</div>
</a>
</div>
<div class="col-lg-3 col-md-6 portfolio-item filter-science" style="transform: scale(0); display: none;">
<a href="images/research_2_2.png">
<img src="images/research_2_2_small.png" alt="">
<div class="details">
<h4>Overlapping fast & slow slip</h4>
<span>A detailed inversion model reveals overlapping fast and slow slip</span>
</div>
</a>
</div>
</div>
</div>
</section>
<div class="highlights">
<section>
<div class="content">
<header>
<a href="https://drive.google.com/file/d/1Do5SogcdvddbXexriWdWdPXk1-cQLR_h/view?usp=sharing" class="icon fa-vcard-o"><span class="label">Icon</span></a>
<h3>CV</h3>
</header>
<p>Education, experiences and skills</p>
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</section>
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<h3>Publications & Talks</h3>
</header>
<p>Peer-reviewed journal publications & conference presentations</p>
</div>
</section>
<section>
<div class="content">
<header>
<a href="https://zenodo.org/record/5015610" class="icon fa-file-text"><span class="label">Icon</span></a>
<h3>Open source & datasets</h3>
</header>
<p>Published source code & datasets</p>
</div>
</section>
<section>
<div class="content">
<header>
<iframe src="https://www.google.com/maps/embed?pb=!1m18!1m12!1m3!1d17132.986255919488!2d-121.72037019012137!3d37.68846663895221!2m3!1f0!2f0!3f0!3m2!1i1024!2i768!4f13.1!3m3!1m2!1s0x808fde1cf96c9a41%3A0xf7e280030f00ed38!2sLawrence%20Livermore%20National%20Laboratory!5e0!3m2!1sen!2sus!4v1745535088838!5m2!1sen!2sus" width="100%" height="100%" style="border:0;" allowfullscreen="" loading="lazy"></iframe>
<h3 style="margin: 0 0 0.5rem 0">Where am I</h3>
</header>
<p style="margin: 0 0 0 0">Lawrence Livermore National Laboratory</p>
<p style="margin: 0 0 0 0">7000 East Ave</p>
<p style="margin: 0 0 0 0">Livermore, CA 94550</p>
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</section>
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<a href="mailto:jiunting@uoregon.edu" class="icon fa-paper-plane-o"><span class="label">Icon</span></a>
<h3>Contact me</h3>
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<!-- <p></p> -->
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<a href="https://github.com/jiunting" class="icon fa-github"><span class="label">Icon</span></a>
<h3>Others</h3>
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<p style="font-weight: bold; font-family:Arial, Helvetica, sans-serif; font-size:26px; text-shadow:0 0 20px rgb(20, 20, 20);">Check out more in the <a href='research.html' style="color:rgb(255, 174, 0)" >Research project</a> </p>
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<h3 style="margin: 0 0 0.5rem 0">About Me</h3>
<h4 style="margin: 0 0 0.5rem 0">Machine Learning and Computational Earth Scientist</h4>
<p>Over 10 years of experience working with time series data, developing modeling and machine learning models that solve real challenging problems. I led a NASA project applying deep learning for earthquake time series forecasting, significantly enhancing early warning capabilities. I also developed and optimized high-performance data mining tools for large-scale seismic signal detection and analysis. I'm driven by curiosity and always thinking about what we can learn from data.</p>
</section>
<section>
<h4>Award & Grant Links</h4>
<ul class="alt">
<li><div class="tooltip"><a href="https://science.nasa.gov/researchers/sara/grant-stats/nasa-earth-and-space-science-fellowship-nessf-selections">NASA Earth & Space Science Fellow</a> <a class="tooltiptext" target="_blank" rel="noopener noreferrer">Click: NESSF 2018 Awards and Information -> Selections -> Earth Science -> then search the name: Jiun-Ting Lin</a> </div> </li>
<li><div class="tooltip"><a href="https://www.agu.org/Learn-and-Develop/Learn/Student-Competitions/OSPA/OSPA-Winners">Outstanding Student Presentation Award</a> <a class="tooltiptext" target="_blank" rel="noopener noreferrer">Click: 2019 Winners -> then search the name: Jiun-Ting Lin</a> </div> </li>
<li><div class="tooltip"><a href="https://www.gst.org.tw/cht/about_award.php?serial=7">Dr. Juan V.C. Best Paper Award</a> <a class="tooltiptext" target="_blank" rel="noopener noreferrer"> Search the 2017 Winners</a> </div> </li>
<li><a href="https://earthsciences.uoregon.edu/">Research Recognition Award @ UO</a></li>
</ul>
</section>
<section>
<h4>Social Media</h4>
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<!-- <li><a href="#"><i class="icon fa-twitter"> </i>Twitter</a></li> -->
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<li><a href="https://github.com/jiunting"><i class="icon fa-github"> </i>Github</a></li>
<li><a href="https://scholar.google.com/citations?user=DKi9fRQAAAAJ"><i class="icon fa-graduation-cap"> </i>Google Scholar</a></li>
<li><a href="https://sites.google.com/site/jtimweb/"><i class="icon fa-globe"> </i>Google Site</a></li>
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© 2025 Tim Lin
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