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Ruipu Li

Ph.D. Student in Computer Science · University of Michigan

Education

University of Michigan, Ann Arbor

Ph.D. Student, Computer Science

Aug 2024 – Present

University of Michigan, Ann Arbor

M.S., Computer Science

Aug 2022 – Apr 2024

University of Michigan, Ann Arbor

B.S., Computer Science

Aug 2020 – Apr 2022

Shanghai Jiao Tong University

B.S., Electrical and Computer Engineering

Aug 2018 – Aug 2022

Publications

Neural Conformal Control for Time Series Forecasting

Ruipu Li and Alexander Rodríguez.

Proceedings of the 39th AAAI Conference on Artificial Intelligence (AAAI ’25), 2025.

Adaptive Conformal Prediction Intervals Over Trajectory Ensembles

Ruipu Li, Daniel Menacho, and Alexander Rodríguez.

Submitted to the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD ’26), 2026.

Research projects

CausalSim: Generative Causal AI for Strategic Decision Support

Graduate Researcher, University of Michigan

Jan 2026 – Present

  • Build an LLM-driven reasoning pipeline combining retrieval with structural causal models to debug discrepancies across black-box simulators.
  • Engineer infrastructure to ground explanations in domain constraints for trustworthy what-if analysis.

ML to Reduce Uncertainty in Climate Forcing by Aerosols

Research Assistant, Climate and Space Sciences and Engineering, University of Michigan

Aug 2022 – Aug 2024

  • Process satellite observations using interpolation, PCA, and feature analysis for aerosol-cloud modeling inputs.
  • Train predictive models for aerosol optical depth and cloud droplet number concentration.

Collaborations and applied forecasting

FluSight Forecasting Challenge (CDC)

Team Lead, UM-DeepOutBreak, University of Michigan

Jul 2023 – Present

  • Top-3 accuracy (MAE) out of about 40 teams in the 2023–2024 FluSight season.
  • Built an end-to-end probabilistic forecasting pipeline for CDC ensemble submissions.
  • Develop calibrated multi-step prediction intervals using conformal prediction methods.

Reliable Uncertainty Cones for Cyclone Trajectory Prediction

Collaboration with Google DeepMind WeatherLab

Oct 2025 – Present

  • Apply an adaptive conformal method (CP-Traj) to ensemble cyclone forecasts for long-horizon coverage.
  • Coordinate larger-ensemble experiments and possible integration into trajectory uncertainty products.

Teaching

Graduate Student Instructor (GSI), EECS 492

Introduction to Artificial Intelligence

Jan 2026 – Present

  • Design and release weekly homework aligned with course learning goals.
  • Lead discussion sections and support students in problem solving and core AI concepts.

Industry

NIO, Autonomous Driving System

Machine Learning Intern

May 2021 – Aug 2021

  • Curated and cleaned large-scale road-test logs to build datasets for lane-change modeling.
  • Improved lane-change decision-making with an LSTM-based motion prediction model.
  • Built Python tooling for road-test analysis and integrated automated testing.

Honors

  • Graduated summa cum laude, University of Michigan
  • Dean’s List, University of Michigan
  • Undergraduate Excellent Scholarship, Shanghai Jiao Tong University
  • John Wu and Jane Sun Excellence Scholarship (Top 3%)

Skills

  • Programming: C, C++, C#, Python, JavaScript, Go, Rust
  • Systems and tools: Great Lakes HPC, Google Cloud Platform (GCP)

Hobbies

Badminton Street photography Table tennis Skiing