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<!DOCTYPE html>
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<meta name="generator" content="Perplexity Computer">
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<p class="eyebrow">University of Michigan · Computer Science</p>
<p class="eyebrow eyebrow--advisor">Advised by <a href="https://alrodri.engin.umich.edu/" target="_blank" rel="noopener noreferrer">Prof. Alexander Rodríguez</a></p>
<p class="hero__summary">
I am a Ph.D. student in Computer Science at the University of Michigan. My research focuses on uncertainty quantification for sequential prediction — particularly the design of reliable predictive sets and intervals for non-stationary time series. My work spans conformal prediction, causal inference, and applications in epidemiology and public health, weather forecasting, and autonomous driving.
</p>
<div class="hero__meta" aria-label="Primary details">
<span>Ann Arbor, MI</span>
<span>Ph.D. student</span>
<span>Uncertainty quantification</span>
<span>Conformal prediction</span>
<span>Time series forecasting</span>
<span>Causal inference</span>
</div>
<div class="hero__actions">
<a class="button button--primary" href="cv.html">View CV</a>
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<a class="button button--ghost" href="https://github.com/RRemixx" target="_blank" rel="noopener noreferrer">GitHub</a>
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<ul class="hero__links" role="list">
<li><a href="mailto:liruipu@umich.edu">liruipu@umich.edu</a></li>
<li><a href="tel:+17346043832">+1 734 604 3832</a></li>
</ul>
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<aside class="hero__aside">
<figure class="portrait-card">
<img src="images/profile.jpg" alt="Portrait of Ruipu Li" class="portrait-card__image">
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</section>
<section class="section-shell news-section" id="news">
<div class="page-width">
<div class="section-heading section-heading--wide">
<div>
<p class="section-label">News</p>
<h2>Recent updates</h2>
</div>
</div>
<ul class="news-list">
<li class="news-item"><time class="news-date">Apr 2026</time><span class="news-text">Paper submitted to KDD 2026: <em>Adaptive Conformal Prediction Intervals Over Trajectory Ensembles</em></span></li>
<li class="news-item"><time class="news-date">Jan 2026</time><span class="news-text">Started as GSI for EECS 492: Introduction to Artificial Intelligence</span></li>
<li class="news-item"><time class="news-date">Jan 2026</time><span class="news-text">Began CausalSim project on Generative Causal AI for Strategic Decision Support</span></li>
<li class="news-item"><time class="news-date">Oct 2025</time><span class="news-text">Collaboration with Google DeepMind WeatherLab on cyclone trajectory uncertainty</span></li>
<li class="news-item"><time class="news-date">Feb 2025</time><span class="news-text">Paper accepted at AAAI 2025: <em>Neural Conformal Control for Time Series Forecasting</em></span></li>
</ul>
</div>
</section>
<section class="section-shell" id="publications">
<div class="page-width">
<div class="section-heading section-heading--wide">
<div>
<p class="section-label">Publications</p>
<h2>Selected papers</h2>
</div>
<p class="section-intro">Links are attached directly on each paper card for faster access.</p>
</div>
<div class="publication-grid">
<article class="paper-card">
<p class="paper-card__meta">AAAI 2025</p>
<h3>Neural Conformal Control for Time Series Forecasting</h3>
<p class="paper-card__authors"><strong>Ruipu Li</strong> and Alexander Rodríguez</p>
<p class="paper-card__venue">Introduces a neural conformal prediction framework for time series that adapts to non-stationary environments. Leverages auxiliary multi-view encoders end-to-end, enforces monotonicity constraints for consistent prediction intervals across quantiles, and supports few-shot learning via related-task data. Achieves state-of-the-art coverage and calibration across epidemic, weather, and energy demand benchmarks.</p>
<div class="paper-card__actions">
<a href="https://dl.acm.org/doi/10.1609/aaai.v39i17.34029" target="_blank" rel="noopener noreferrer">AAAI record</a>
<a href="https://arxiv.org/abs/2412.18144" target="_blank" rel="noopener noreferrer">arXiv</a>
</div>
</article>
<article class="paper-card">
<p class="paper-card__meta">Submitted to KDD 2026</p>
<h3>Adaptive Conformal Prediction Intervals Over Trajectory Ensembles</h3>
<p class="paper-card__authors"><strong>Ruipu Li</strong>, Daniel Menacho, and Alexander Rodríguez</p>
<p class="paper-card__venue">Proposes a unified conformal prediction framework that transforms ensemble trajectory samples into calibrated prediction intervals with formal coverage guarantees. Introduces an online update step and an optimization step that captures inter-step temporal dependencies, yielding sharper and more adaptive uncertainty estimates for autonomous driving, hurricane forecasting, and epidemic modeling.</p>
<div class="paper-card__actions">
<a href="https://arxiv.org/abs/2508.13362" target="_blank" rel="noopener noreferrer">arXiv</a>
<a href="https://scholar.google.com/citations?user=pMTyBugAAAAJ&hl=en" target="_blank" rel="noopener noreferrer">Google Scholar</a>
</div>
</article>
</div>
</div>
</section>
<section class="section-shell" id="projects">
<div class="page-width">
<div class="section-heading section-heading--wide">
<div>
<p class="section-label">Research projects</p>
<h2>Current and recent work</h2>
</div>
<p class="section-intro">Lab-based research projects and applied forecasting collaborations with external partners.</p>
</div>
<div class="stack-grid">
<article class="stack-card">
<div class="stack-card__top">
<div>
<h3>CausalSim: Generative Causal AI for Strategic Decision Support</h3>
<p class="stack-card__role">Graduate Researcher, University of Michigan</p>
</div>
<p class="stack-card__date">Jan 2026 – Present</p>
</div>
<ul>
<li>Build an LLM-driven reasoning pipeline that combines retrieval with structural causal models.</li>
<li>Anchor model explanations in domain-specific constraints to support trustworthy counterfactual analysis and systematic simulator validation.</li>
</ul>
</article>
<article class="stack-card">
<div class="stack-card__top">
<div>
<h3>ML to Reduce Uncertainty in Climate Forcing by Aerosols</h3>
<p class="stack-card__role">Research Assistant, Climate and Space Sciences and Engineering, University of Michigan</p>
</div>
<p class="stack-card__date">Aug 2022 – Aug 2024</p>
</div>
<ul>
<li>Processed satellite observations using interpolation and PCA for aerosol-cloud modeling inputs.</li>
<li>Trained predictive models for aerosol optical depth and cloud droplet number concentration with feature analysis using SHAP.</li>
</ul>
</article>
<article class="stack-card stack-card--accent">
<div class="stack-card__top">
<div>
<h3>FluSight Forecasting Challenge (CDC)</h3>
<p class="stack-card__role">Team Lead, UM-DeepOutBreak, University of Michigan</p>
</div>
<p class="stack-card__date">Jul 2023 – Present</p>
</div>
<ul>
<li>Built an end-to-end forecasting pipeline from data ingestion through evaluation and submission.</li>
<li>Submitted weekly real-time probabilistic forecasts used in CDC ensemble modeling.</li>
<li>Developed calibrated multi-step prediction intervals using conformal prediction methods.</li>
<li>Mentored undergraduates on reproducible experiments, deployment, and pipeline reliability.</li>
</ul>
</article>
<article class="stack-card stack-card--accent">
<div class="stack-card__top">
<div>
<h3>Reliable Uncertainty Cones for Cyclone Trajectory Prediction</h3>
<p class="stack-card__role">Collaboration with Google DeepMind WeatherLab</p>
</div>
<p class="stack-card__date">Oct 2025 – Present</p>
</div>
<ul>
<li>Applied an adaptive conformal method (CP-Traj) to ensemble cyclone forecasts for multi-step coverage.</li>
<li>Coordinated large-ensemble experiments and explored integration of uncertainty cones into operational trajectory forecasting products.</li>
</ul>
</article>
</div>
</div>
</section>
<section class="section-shell" id="experience">
<div class="page-width section-grid">
<div class="section-heading">
<p class="section-label">Experience</p>
<h2>Teaching and industry</h2>
</div>
<div class="split-columns">
<article class="mini-card">
<h3>Graduate Student Instructor, EECS 492</h3>
<p class="mini-card__meta">Introduction to Artificial Intelligence · Jan 2026 – Present</p>
<p>Design weekly assignments, lead discussion sections, and support students in understanding core AI concepts and problem-solving strategies.</p>
</article>
<article class="mini-card">
<h3>NIO, Autonomous Driving System</h3>
<p class="mini-card__meta">Machine Learning Intern · May 2021 – Aug 2021</p>
<p>Worked on lane-change modeling, motion prediction, and Python tooling for large-scale road-test analysis.</p>
</article>
</div>
</div>
</section>
<section class="section-shell" id="education">
<div class="page-width section-grid">
<div class="section-heading">
<p class="section-label">Education</p>
<h2>Training</h2>
</div>
<div class="education-list">
<article class="education-item">
<div>
<h3>University of Michigan, Ann Arbor</h3>
<p>Ph.D. Student, Computer Science</p>
</div>
<p class="education-item__date">Aug 2024 – Present</p>
</article>
<article class="education-item">
<div>
<h3>University of Michigan, Ann Arbor</h3>
<p>M.S., Computer Science</p>
</div>
<p class="education-item__date">Aug 2022 – Apr 2024</p>
</article>
<article class="education-item">
<div>
<h3>University of Michigan, Ann Arbor</h3>
<p>B.S., Computer Science</p>
</div>
<p class="education-item__date">Aug 2020 – Apr 2022</p>
</article>
<article class="education-item">
<div>
<h3>Shanghai Jiao Tong University</h3>
<p>B.S., Electrical and Computer Engineering</p>
</div>
<p class="education-item__date">Aug 2018 – Aug 2022</p>
</article>
</div>
</div>
</section>
<section class="section-shell" id="hobbies">
<div class="page-width section-grid">
<div class="section-heading">
<p class="section-label">Hobbies</p>
<h2>Outside research</h2>
</div>
<div class="hobby-grid">
<article class="hobby-card">
<h3>Badminton</h3>
<p>Competitive play, including UofM OPEN Fall 2025 men's doubles champion in the B group.</p>
</article>
<article class="hobby-card">
<h3>Photography</h3>
<p>Street photography with a focus on candid moments and urban scenes.</p>
<a href="https://liruipu.myportfolio.com/" target="_blank" rel="noopener noreferrer">Photography portfolio</a>
</article>
<article class="hobby-card">
<h3>Table tennis</h3>
<p>Regular play for fun and fitness, with an ongoing interest in improving technique.</p>
</article>
<article class="hobby-card">
<h3>Skiing</h3>
<p>Recreational skiing on groomed runs and occasional off-piste terrain.</p>
</article>
</div>
</div>
</section>
<section class="section-shell" id="contact">
<div class="page-width contact-panel">
<div>
<p class="section-label">Contact</p>
<h2>Get in touch</h2>
<p>I am happy to connect regarding research collaborations, forecasting systems, uncertainty quantification, causal modeling, and related topics in machine learning and statistics.</p>
</div>
<div class="contact-panel__links">
<a href="mailto:liruipu@umich.edu">Email</a>
<a href="cv.html">Curriculum vitae</a>
<a href="https://scholar.google.com/citations?user=pMTyBugAAAAJ&hl=en" target="_blank" rel="noopener noreferrer">Google Scholar profile</a>
<a href="https://github.com/RRemixx" target="_blank" rel="noopener noreferrer">GitHub profile</a>
</div>
</div>
</section>
</main>
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<div class="page-width site-footer__inner">
<p>Ruipu Li · Ann Arbor, Michigan</p>
<p>Last updated April 2026 · <a href="https://www.perplexity.ai/computer" target="_blank" rel="noopener noreferrer">Created with Perplexity Computer</a></p>
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