Research
Relevant experience
University of Maryland, College Park
Research Assistant August 2022 - May 2023
- Researched the Quantum Fourier Transform and Classification Algorithms on Quantum Computers and presented a research poster to other researchers.
- Learned about quantum computing and implementation of machine learning algorithms with Qiskit, PyTorch, Sklearn.
- Tech: Qiskit, Matplotlib, Python
University of California, Santa Barbara
Research Assistant April 2022 - July 2022
- Presented a research project in-person about the orbit of binary star system HIP18267 at the Sagan Workshop at CalTech.
- Conducted a research project that simulated the orbit around Black Hole Sagittarius A*.
- Coded web scraper to download astrometric data from Hipparcos Catalog.
- Tech: Astropy, Numpy, Pandas,Matplotlib, PyTest, Python
University of California, Santa Barbara
Research Assistant July 2021
- Researched and collected data about eclipsing binary SW Lac using the telescopes at the Las Cumbres Observatory.
- Parsed Gigabytes of raw telescope data to extract the brightness of the star system over time.
- Generated a light curve with parsed data using a fourier series and presented findings at a research symposium.
- Tech: Astropy, Photutils,Numpy, Matplotlib, LaTex, Python
- GitHubPaperPresentation
Competitions & Hackathons
Video Conference Platform, Finalist @ UC Berkeley Hackathon
- Developed video conference platform with meeting rooms, screen sharing, and recording with React and WebSockets.
- Queried facial and audio expression APIs to track over 100+ emotions of each participant in the video call.
- Aggregated data from backend and created 4 visualizations to track emotions/sentiment over time.
- Video
Crop Disease Classification App, Honorable Mention @ Silicon Valley Science Fair
- Developed IOS and Android app to classify plant diseases using image classification.
- Built a backend server with AWS services to handle CRUD operations from the apps.
- Trained deep learning model Convolutional Neural Network (CNN) on AWS SageMaker with Python, Keras, TensorFlow, using the plant dataset from the UCI Machine Learning Repository, achieving an accuracy of 90% and validation accuracy of 80%.
- Coded Nitrogen Detection by using masking, image segmentation, and OpenCV to determine the color of the leaf.
- GitHubVideo