Curriculum Vitae

General Information

Name Yiqi "Andrew" Liu
Location Princeton, NJ, United States
Email andrew.liu@princeton.edu
Telephone (667) 218-8691

Education

  • 2023 - present
    PhD in Physics
    Princeton University, Princeton, New Jersey, United States
    • Research: Cosmic Microwave Background
  • 2019 - 2023
    B.S. in Applied Math & Statistics, Physics, Mathematics
    Johns Hopkins University, Baltimore, Maryland, United States
    • GPA: 3.99 / 4.0
    • Departmental Honors: Applied Math & Stats, Physics, Math
    • Minor: Computer Science

Honors and Awards

  • 2023
    • Donald E. Kerr Memorial Award
    • Applied Mathematics and Statistics Achievement Award
  • 2022
    • Provost's Undergraduate Research Award
    • Sigma Pi Sigma Physics Honors Society
  • 2020 - 2021
    • Bloomberg Distinguished Professor Research Fellowship
  • 2019 - 2022
    • Dean's List

Publications

Research Experience

  • 2023 - present
    Simons Observatory
    Mentors: Jo Dunkley, Susanna Azzoni
    • Cross C_ell Foreground Cleaning: Investigating the potential impact of dust complexity on the bias of tensor-to-scalar ratio.
    • SO-Planck cross analysis: estimating calibration factors to SO maps using Planck data.
  • 2019 - 2023
    Cosmology Large Angular Scale Surveyor
    Mentors: Charles L. Bennett, Tobias A. Marriage, Ivan L. Padilla
    • Component Separation Algorithm: Implemented the needlet internal linear combination (NILC) for foreground component separation. Tested the algorithm under different foreground conditions. Used pixel covariance to reduce the NILC bias at large angular scale.
    • Polarized Foreground Masks: Constructed masks based on polarized intensity with WMAP and Planck maps specific to the CLASS scanning region. Tested power spectrum estimators' performances over different polarization masks.
    • Instrumentation: Assisted in designing telescope components with SolidWorks. Assembled CLASS cryogenic receivers. Used Tormach CNC to produce infrared filters for the CLASS detector assembly.
  • 2021 - 2023
    Zakamska Stellar Astrophysics Group
    Mentor: Nadia L. Zakamska, Hsiang-Chih Hwang
    • Cataclysmic Variable: First-authored paper on the puzzling cataclysmic variable CSS1603+19. Performed various analysis over infrared and optical observations. Demystified unusual emission structure from the system. Concluded with a physical model for this system including the stellar mass and radius of the system.
    • Time-Domain Astrophysics: Designed a range of routines for decoding photometry and spectroscopy observations. Identified fine line and continuum structure from large data sets.
    • PypeIt Data Reduction: Reduce raw GNIRS near-infrared exposures with data-reduction pipeline PypeIt.

Selected Talks and Presentations

Teaching

  • 2023 spring
    • EN.553.430 Intro to Statistics (Undergrad, 14 students)
  • 2022 fall
    • EN.553.633 Monte Carlo Method (Graduate, 17 students)
    • AS.171.103 General Physics I (Undergrad, 23 students)
  • 2020 fall
    • AS.171.103 General Physics I (Undergrad, 39 students)

Industrial Experience

  • 2021
    Quantitative Researcher
    Zhejiang Longwin Investment Ltd., Hangzhou, Zhejiang, China
    • High-Frequency Trading Backtest: Backtested high-frequency trading based on Box Arbitrage. Constructed testing framework for quantitative strategies with high-performance python routines.
    • Sentiment Investment: Analyzed commodity trading strategy using market sentiment based on institutional investors' open interests.
    • Factor Investment Strategy: Helped to develop quantitative stock trading model based on analyst report and company earnings.

Skills

Programming Python, SQL, C, C++, Java, Matlab, R, HTML, Julia, PHP
Machining Tormach CNC Mill, Monarch Lathes, Bridgeport Mill
Language English, Mandarin-Chinese
Other LaTeX, JupyterLab, SolidWorks, Mathematica, Rowing, Alpine Ski