Resume of Yue (Julien) Yu

Yue (Julien) Yu

USC Viterbi School of Engineering

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EDUCATION

University of Southern California Los Angeles, CA

PhD in Industrial and Systems Engineering, GPA: 4.00/4.00 2019.08-2023.09 MS in Computer Science, GPA: 4.00/4.00 2019.08-2022.05

• Faculty advisor: Dr. John Gunnar Carlsson, Stipend: $38,000/year

• Completed coursework: analysis of algorithms, applied cryptography, artificial intelligence, design of experiments, machine learning, natural language processing, parallel computing and visualization, stochastic process, convex/combinatorial/stochastic/large scale optimization, linear/integer/equilibrium programming University of California, Berkeley Berkeley, CA

MEng in Industrial Engineering and Operations Research, GPA: 3.81/4.00 2018.08-2019.05

• Fung excellence scholarship of $20,000 offered by Fung institute for engineering leadership BA in Applied Mathematics and BA in Statistics, GPA: 3.89/4.00 2014.08-2018.05

• High distinction in general scholarship, Lifetime member of Phi Beta Kappa EXPERIENCE

Research Assistant & Teaching Assistant, USC Department of ISE, Los Angeles 2019.08-2023.09

• Devised a lossless approach to solve split-delivery routing problems including SDVRP and SDVRPTW, designed and ran computational experiments showing remarkable performance with solvers coded in C

• Presented computer-aided proof of a new upper bound of the Euclidean-TSP constant, applying techniques of combinatorial optimization, high-dimensional integration, numerical analysis, and supervised learning

• Researched on algorithmic approaches to solve resource allocation problems including GTSP and CCC-TSP, featured as chair of the Travelling Salesman Problem (TSP) session in the 2022 Informs annual conference

• Graded assignments and hosted office hours for “Introduction to Operations Research: Stochastic Model” Data Scientist Intern, MOLOCO, Inc., Remote 2021.05-2021.08

• Built a framework to prevent click and install fraud, and wrote an adaptive algorithm to reduce the 10 biggest clients’ monthly ad spending on fraudulent publishers by an estimated 70%, using SQL, Python, and Jenkins

• Assisted the machine learning team in its transition from second-price auction to first-price auction, fixed a robustness issue inside the updated spending stabilizer, and avoided company-wide sunk cost Researcher of Automated Vehicle Technology, General Motors, Remote 2018.08-2019.05

• Collected vehicle data, and completed the proof of concept that automation and electrification would reduce the energy consumption of Cadillac, using spline interpolation and model predictive control on MATLAB

• Applied learning techniques including principal component analysis to extract features from GM’s enormous driving datasets with Python, and developed metrics for good driving behaviors under different constraints Analyst Intern of Artificial Intelligence, Agile Venture Capital/IOVC, San Francisco 2018.05-2018.08

• Researched on major AI fields including natural language processing, computer vision, and knowledge representation, and analyzed US technology companies based on their financial health, products, and talents Adjunct Instructor, Grader & Tutor, Berkeley Learning Center, Berkeley 2016.01-2018.05

• Taught “Introductory Statistics for Business”, drafted study guides, and hosted office hours and review sessions

• Graded “Introduction to Statistical and Critical Thinking” and “Introduction to Probability and Statistics”

• Tutored “Multivariable Calculus”, “Linear Algebra and Differential Equations” and “Concepts of Probability” Research Apprentice, Berkeley URAP, Berkeley 2017.01-2017.12

• Studied the synergistic and antagonistic effects across 6 types of ionizing radiation, and solved the ordinary differential equations featuring their incremental effect additivity numerically with Euler’s method

• Calibrated the adjustable parameters of a model featuring mixture dose-effect relationships, calculated their correlations and confidence intervals, and performed sensitivity analysis on background radiation levels Co-Chair & Head of Marketing, BSCF/Decode Innovation Conference, Stanford 2017.06-2017.10

• Led a marketing team to draft 100+ articles on numerous platforms, line up 50+ organizations and 20+ media including IEEE, World Economic Forum, Bloomberg, and Forbes, and attract 1,500+ attendees

• Interviewed speakers including Anne Casscells, Wei-Ying Ma, Joris Poort, Michael Seibel, and Hans Tung System R&D Intern, Orient Securities, Shanghai 2016.05-2016.08

• Mined high-frequency financial data using SQL, tuned ARMA and ARIMA model parameters to predict prices of 1000+ SSE stocks using R, and evaluated model quality based on cross-validation, AIC, and BIC PUBLICATION

Jones, B., Yu, J., & Carlsson, J. (2021). A lossless a priori splitting rule for resource allocation problems. Submitted to Transportation Science.

Ham, D., Song, B., Gao, J., Yu, J., & Sachs, R. K. (2018). Synergy Theory in Radiobiology. Radiation Research. SKILL

• Language: English, French, Mandarin

• Computer: C, CPLEX, Git, Julia, LaTeX, MATLAB, Microsoft Excel, Python, PyTorch, R, SQL, TensorFlow

• Research-related: data science, machine learning, mathematical modelling, optimization, probability, statistics