Yizhou Lu

Intern @ Databricks | M.S. in Machine Learning @ CMU | B.S. CS & MATH @ USC | ex-AI/ML Intern @ NVIDIA | ex-MLE & SDE Intern | Researcher @ CMU RAIL Lab

Pittsburgh, Pennsylvania, United States

About

Hi, I'm a master student for the Master of Science in Machine Learning program at Carnegie Mellon University (CMU) with an expected graduation date of Dec 2026. I'm looking for 2026 Summer Intern opportunities in SDE, MLE and Quantitative roles.

Experience

  • Software Engineer Intern at Databricks
    May 2026 - Present · 2 mos

  • Student Researcher at RAIL Lab at Carnegie Mellon University
    Sep 2025 - Present · 10 mos

    Supervisor: Prof. Pradeep Ravikumar Working on Identifiable Representation Learning with Weak Supervision, designing generic frameworks to extract symbolic features/meanings from data sources (e.g. including but not limited to tabular data). Explored density ratio estimation approaches to evaluate the KL divergence of approximated density ratios in the algorithm.

  • AI/ML Solutions Architect Intern at NVIDIA
    Jun 2025 - Aug 2025 · 3 mos

    Surveyed vision-language-action benchmarks and built a multi-modal data pipeline through video generation model. Adapted the RDT-1B diffusion model to the IsaacLab workflow, enabling smooth humanoid benchmark evaluation for Piper robotic arm.

  • USC Viterbi School of Engineering (Part-time · 2 yrs 10 mos)
    • Researcher at the AI-Drug Lab
      Aug 2024 - May 2025 · 10 mos

      Designed a multi-agent LLM framework to resolve the lack of domain knowledge for LLM drug discovery task. Implemented domain knowledge identification, tool construction and reflective analysis for optimizing solution. Proposed the expansion-by-pruning approach, integrated expansion phase for novel idea generation and the pruning phase for filtering out impractical and non-optimal solutions, resulted in an improved efficiency of idea exploration.

    • Course Producer (TA) for CSCI270
      Aug 2023 - Apr 2025 · 1 yr 9 mos

      Introduction to Algorithms and the Theory of Computing

    • Course Producer (TA) for CSCI170
      Jan 2023 - Apr 2025 · 2 yrs 4 mos

      Discrete Methods in Computer Science

  • Machine Learning Engineer Intern at AIForceTech
    May 2024 - Aug 2024 · 4 mos

    - Researched high-precision centimeter-level positioning based on visual odometers and navigation satellite data. - Designed, developed, and deployed a multisensory fusion and autoencoder neural network to increase positioning accuracy. Built data ETL pipeline to integrate streaming data from multiple sources.