Louis Ye

Hello there! I am a SWE at Google. I majored in Computer Science and Economics at Carleton College.

I am originally from Singapore but grew up in Portland, Oregon, where I attended Catlin Gabel. At Catlin, I served as the student body Vice President, led the Boys Varsity Tennis Team, and volunteered on the InvenTeam to engineer solutions to societal problems. In my free time, you can find me practicing piano, playing tennis, or weightlifting.

• Research

• Industry

• Entrepreneurial

• Courses

• Extracurricular Activities

• Carleton Programs

• For Fun

• Multivariable Calculus

  Vectors, curves, calculus of functions of three independent variables, including directional derivatives and triple integrals, cylindrical and spherical coordinates, line integrals, Green's theorem, sequences and series, power series, Taylor series

• Entrepreneurship, Innovation, and Economic Performance

  Microeconomic theory of entrepreneurship, theoretical role of entrepreneurs and intrapreneurs within company, business development of entrepreneurs case studies

• Probability

  Discrete probability, random variables, independence, joint and conditional distributions, expectation, limit laws and properties of common probability distributions

• Corporate Organization & Finance

  Tradeoffs in corporate organization, executive compensation, project valuation, the cost of capital under debt and equity financing, the firm’s optimal capital structure

• Math of Computer Science

  Logic and proofs, number theory, elementary complexity theory and recurrence relations, basic probability, counting techniques, graphs

• The Theory of Investment Finance

  Bond pricing, stock pricing, option pricing, the mortgage market, hedge funds, private equity, optimal portfolios, defaults, financial intermediary capital, investors' behavioral biases

• Programming Languages: Design & Implementation

  Syntax and semantics, mechanisms for parameter passing, typing, scoping, control structures

• Software Design

  Code construction techniques, debugging and profiling tools, testing methodologies, UML, principles of object-oriented design, design patterns, user interface design

• Hardware/Software Interface

  Structure of computer processors, with attention to digital logic, assembly language, performance evaluation, computer arithmetic, data paths and control, pipelining, and memory hierarchies

• Algorithms

  Greedy algorithms, dynamic programming, divide and conquer, and network flow. Applications of algorithm techniques in natural language processing, economics, computational biology, and data mining.

• Linear Algebra

  Vector spaces, linear transformations, determinants, inner products and orthogonality, eigenvectors and eigenvalues.

• Statistical Inference

  Resampling methods (permutation tests, bootstrap intervals), classical methods (parametric hypothesis tests and confidence intervals), parameter estimation, goodness-of-fit tests, regression, and Bayesian methods.

I took Data Structures prior to attending Carleton College and thus placed out of that class in college.