Timothy Qian — Resume

Education

Massachusetts Institute of Technology

2024 — 2025

MEng in Electrical Engineering and Computer Science (GPA: 5.0/5.0)

Massachusetts Institute of Technology

2021 — 2024

B.S. in Electrical Engineering and Computer Science (GPA: 5.0/5.0)

Teaching:

  • TA for Machine Learning (6.7900), Fall 2024

Graduate technical coursework:

  • Deep Generative Modeling (6.S978)
  • Inference and Information (6.7800)
  • Machine Learning (6.7900)
  • Statistical Learning Theory (9.520)
  • Advanced Algorithms (6.5210)
  • Distributed Systems (6.5840)
  • Computer System Security (6.5660)
  • Stochastic Processes (18.615)
  • Nonlinear Optimization (6.7220)
  • Optimization Methods (6.7200)
  • Probability (6.7700)
  • Computational Photography (6.8370)
  • Abstract Algebra (18.701)

Undergraduate technical coursework:

  • Software Performance Engineering (6.1060)
  • Natural Language Processing (6.8611)
  • Operating Systems (6.1810)
  • Signal Processing (6.3000)
  • Computation Structures (6.1910)
  • Embedded Systems (6.08)
  • Computer Systems Engineering (6.1800)
  • Signals, Systems, and Inference (6.3010)

Experience

Chunky Post-training with Seoirse Murray, Sara Price, Collin Burns, John Schulman at MATS

Berkeley, CA2025

  • Framed LLM behavior as mapping input prompts to post-training data chunks.
  • Designed methods to probe decision boundaries between chunks using base models.
  • Assessed consistency in how language models rely on spurious prompt features.

    • Layered Unlearning for Adversarial Relearning with Prof. Dylan Hadfield-Menell at MIT CSAIL

    Cambridge, MA2025

  • Proposed Layered Unlearning (LU) for robustness against adversarial relearning.
  • Designed synthetic experiments and proposed theory to interpret results.
  • Evaluated LU on LLM unlearning benchmarks and showed robustness over existing methods.
  • Preprint: [arXiv:2505.09500]

    • Quantitative Research Intern at Citadel Securities

    New York, NY2023, 2024

  • Worked under the systematic options team, created a risk model and performed alpha research.
  • Studied deep learning in the context of alpha research.
  • Designed a distributed computing framework to analyze large-scale datasets.

    • Cooperative Multi‑Agent Reinforcement Learning with Prof. Dylan Hadfield-Menell at MIT CSAIL

    Cambridge, MA2024

  • Designed experiments to encourage agents to find cooperative solutions.
  • Optimized Melting Pot substrates in JAX for end-to-end GPU reinforcement learning.

    • 2D Object Detection with Learning Proximal Operators with Prof. Justin Solomon at MIT CSAIL

    Cambridge, MA2022, 2023

  • Developed efficient object-detection pipeline without predicting fixed number of boxes.
  • Used proximal operators to model the problem as a multi-solution optimization problem.
  • Analyzed diffusion object detection methods and conducted ablation studies.

    • Software Engineering Intern at Vividly (formerly Cresicor)

    Cambridge, MA2022

  • Migrated database from Firebase to Django, Relay, and GraphQL.
  • Designed an efficient system for using hierarchical models represented by a DAG.

    • Optimal Measurement of Field Properties with Quantum Sensor Networks with Prof. Alexey Gorshkov at UMD JQI

    College Park, MD2020, 2021

  • Investigated measurement accuracy improvement using quantum sensor networks.
  • Developed a measurement protocol and proved the protocol’s optimality.
  • US Patent, (US‑20230259806‑A1), Aug 2023.
  • Physical Review A, Vol.103, Issue 3, 2021. [arXiv:2011.01259]
  • American Physical Society Meeting, Mar 2021: E32.00005. (Quantum Metrology and Sensing IV)

    • Awards

    Research:

    • Regeneron Science Talent Search, Finalist (5th place, $90,000 award), 2021
    • Davidson Fellows Scholarship ($25,000 award), 2021

    Computer Science:

    • Meta Hacker Cup, Round 3 Qualifier (120th place globally), 2022
    • Google Code Jam, Round 3 Qualifier (238th place globally), 2021
    • USA Computing Olympiad, Finalist (9th place in USA Team Selection), 2020, 2021

    Mathematics:

    • William Lowell Putnam Competition, Honorable Mention (46th place), 2022
    • USA Math Olympiad, Qualifier (47th place), 2020, 2021
    • USA Junior Math Olympiad, Honorable Mention (top 24 in USA), 2019

    Physics:

    • USA Physics Olympiad, Honorable Mention (top 300 in USA), 2021