CS121 Teaching Fellow / Harvard University / Aug 2019 – Present
Teaching Fellow for Harvard’s CS121: Introduction to Theoretical Computer Science course. Responsibilities include: answering students’ questions about homework and course materials during office hours; preparing and holding review sessions for students; grading problem sets and exams.
Summer Intern / SoundAround / Jun 2019 – Aug 2019
Trained and tested machine learning models (in Python using Keras and TensorFlow) for speech analysis. Designed and implemented a phoneme recognition model in Keras to meet processing power and energy constraints. Developed code to stream device microphone audio to multiple analysis services in real-time. Implemented other voice analysis features (such as emotion detection and speaking rate) in Java. SoundAround is an early-stage startup launching wearable devices with voice analysis features.
CS152 Teaching Fellow / Harvard University / Jan 2019 – May 2019
Teaching Fellow for Harvard’s CS152: Programming Languages course, which covers the theory, design, and implementation of programming languages. Prepared and held review sections for students. Held weekly office hours to answer students’ questions on course materials. Graded and provided feedback on problem sets and exams. Received a Certificate of Distinction in Teaching by the Office of Undergraduate Education.
Data Analyst / Bluebonnet Data / May 2018 – present
Data Analyst at a student-led startup with the mission of providing down-ballot Democratic campaigns with high-quality data analysis at a low cost. Providing data-driven insights for effective campaign strategy. Making queries in voter databases to target specific voter demographics. Automating the merging of data between voter databases. Developing software (in R) to automate expected-vote-analysis calculations on datasets from voter databases. Assisting in the creation (using R and Shiny) of a web-based platform to provide campaigns access to useful voter analysis tools. Producing reports on vote projections for diverse campaign strategies.
Machine Learning Research Laboratory Assistant / University of North Texas / Jun 2016 – Aug 2016
Collaborated in the design of an algorithm capable of extracting key phrases from scholarly articles that was three and a half times more likely than competing algorithms to identify relevant words from a given scholarly article. Wrote an optimized, multithreaded implementation of the algorithm in Java with Weka to facilitate fast and efficient key phrase tagging for large datasets.
Harvard University, 2017-2021
Relevant Coursework: [Spring 2019] Data Structures and Algorithms. [Past] Introduction to Theoretical Computer Science; Applied Algebra (used SageMath Python-based mathematics language); Introduction to Probability; Principles of Economics (Macro/Micro); Programming Languages (used OCaml, Haskell, Datalog/Prolog); Systems Programming and Machine Organization (used C, x86/x86-64 Assembly); Mathematics for Computation, Statistics, & Data Science (used R); Linear Algebra & Real Analysis I.
Texas Academy of Mathematics and Science (TAMS) at the University of North Texas (UNT), 2015-2017
An early college program for 11th and 12th graders to obtain two years of college credits at UNT. | SAT I: Math 790, Verbal 760. SAT II: Math 800, Biology-M 800. GPA: 4.0 / 4.0. | Relevant Coursework: Computing Foundations I (Data structures and formalisms in CS, used C++); Special Problems in Computer Science (Research course, used Java); Differential Equations I; Multivariable Calculus.
Programming: C++/C (4+years, expert), Java (4+ years, intermediate), R (1 year, intermediate), Python (6 months, intermediate), OCaml (6 months, intermediate), SageMath Python-Based Mathematics Language (6 months, intermediate), x86/x86-64 Assembly (6 months, novice), Swift (6 months, novice), Haskell (1 month, novice), Prolog (1 month, novice)
Tools: Visual Studio Code, Eclipse, Android Studio, Xcode, RStudio, GDB, Valgrind, LaTeX, Excel, PowerPoint, Word
Operating Systems: macOS, Linux, Windows
(Harvard): Spring 2019: Data Structures and Algorithms, Probability and Random Processes with Economic Applications. Past: Introduction to Theoretical Computer Science; Applied Algebra (used SageMath Python-based mathematics language); Introduction to Probability; Principles of Economics (Macro/Micro); Programming Languages (used OCaml, Haskell, Datalog/Prolog); Systems Programming and Machine Organization (used C, x86/x86-64 Assembly); Mathematics for Computation, Statistics, & Data Science (used R); Linear Algebra & Real Analysis I.
(UNT): Computing Foundations I (Data structures and formalisms in CS, used C++); Special Problems in Computer Science (Research course, used Java); Differential Equations I; Multivariable Calculus.
Certificate of Distinction in Teaching by The Office of Undergraduate Education at Harvard University ● National Merit Finalist ● National Hispanic Scholar ● UNT President’s List (4 semesters) ● $3,000 TAMS Summer Research Scholarship