I'm currently a 3rd year Computer Engineering student at UC Santa Barbara. The field of CS is my focus, and I'm proficient in full-stack development and AI tools. I excel in problem-solving, with a range of engineering skills. In my free time, I love watching history documentaries and playing the piano.
Skills:
C++
Java
Python
HTML/CSS/JS
React
Next.js
TypeScript
Tailwind CSS
Node.js
SQL
Resume
Education
UC Santa Barbara Computer Engineering • Sept 2022 - June 2026 Coursework: • Lin Alg, Diff Equations, Vector Calculus, Data Structures & Algorithms, Object Oriented Design, Discrete Math, Physics 1-4, Analog and Digital Circuits and Systems A-B-C, Digital Design Principles
Experience
Java Instructor Project Edge • Sept 2022 - Present • Curated comprehensive computer science curriculum for 50+ high school students • Advised students in strategies for the AP exam and personalized Java lessons on Object Oriented Programming
AI Trainer Outlier AI • Feb 2024 - Present • I evaluated the quality of AI-generated code in C++/Java/Python/JavaScript/SQL • Debugged 400+ code responses
Engineering President Titanium Robotics • Sep 2018 - June 2022 • Mentored and recruited 40+ members for FRC team 1160 • Spearheaded design and manufacturing of the competition robot • Piloted development of Java control systems, PID control loops, and target detection • Achieved Rockwell Automation’s Creativity Award and finished 8th out of 43 teams in Offensive Power Rating at 2022 FIRST Sacramento Regional, team’s best performance in nearly 20 seasons
Machine Learning Researcher Caltech • May 2022 - Sept 2022 • Under mentorship of Prof. Babak Hassibi, applied deep reinforcement learning algorithms to engineer a model that could solve a 2x2 Rubik's cube in the least moves possible • Trained models implementing Monte Carlo tree search, deep approximate value iteration, and weighted A* search; final program had baseline accuracy of 83.78% • Utilized: Python, tensorflow, numpy, Jupyter Notebook
Projects
Stock Market Prediction using LSTM • Predicting stock market trends using long short-term memory (LSTM) neural networks • Real-time data is sourced from yfinance library. • Proven to be effective, with R-Squared coefficient of 0.89 • Utilized: Python, tensorflow, pandas, numpy
COVID-19 Visualizer • COVID-19 tracker app showing map with number of cases in proportional circles, recovered cases, deaths, active cases. • Data is sourced from the disease.sh API. • HTML, CSS, Javascript, React.js, Charts.js, Material UI, Firebase
Get In Touch
Currently looking for a new opportunity, you can contact me by clicking on the button below. Whether you have a question or just want to say hi, feel free to contact me!
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