- B.S/M.S, Computer Science (GPA: 4.00) Georgia Institute of Technology (Aug 2021 - May 2025)
- Specialization in Machine Learning, Info-Internetworks
- Relevant Coursework: Object Oriented Programming, Design and Analysis of Algorithms, Computer Organization, Operating Systems and Networks, Machine Learning, Computer Vision, Automata and Complexity, Robotics and Perception, Databases, Intro to Info Security
Software Engineer Intern | Instructify.ai - Atlanta, GA
- Engineered a Retrieval-Augmented Generation (RAG) system integrating course materials to enhance a language model's capabilities as an intelligent teaching assistant.
- Utilized LangChain and LlamaIndex for material retrieval, enabling contextually relevant question/answer generation.
- Implemented LLM guardrails with a text classification model, ensuring accurate and appropriate student responses.
- Developed and maintained back-end REST API endpoints and extensively tested for reliability with Postman.
Undergraduate Research Assistant | Georgia Institute of Technology - Atlanta, GA
- Wrote Research Paper: From Posts to Predictions: Leveraging Reddit Sentiments for Bitcoin Price Analysis.
- Conducted time series analysis using LSTM-GRU and Transformer models to predict Bitcoin prices based on historical data and sentiment analysis.
- Web scraped Reddit comments and posts in relevant cryptocurrency sub-reddits to gather data for analysis.
- Cleaned and pre-processed data using Entity Recognition techniques to enhance sentiment analysis accuracy.
- Performed sentiment analysis on Reddit comments with various models, aggregating scores to ensure unbiased results.
Ansys - Atlanta, GA
- Developed a new suite of benchmarking tools in Python aimed to improve efficiency of code.
- Incorporated benchmarking tools into existing CI/CD pipeline ensuring that inefficient code is not deployed.
- Created elegant UI for benchmarking data analysis including graphs and tables for easy understanding of data.
- Utilized NoSQL queries in MongoDB to query database and perform data analysis to provide useful metrics for employees.
Lead Machine Learning Intern | Runway - Atlanta, GA
- Spearheaded the development of Natural Language Processing algorithm for improved resume candidate selection.
- Employed an augmented spaCy model to perform tokenization, part-of-speech tagging, and dependency parsing, ensuring precise data extraction and analysis.
- Leveraged Named Entity Recognition (NER) techniques to identify and categorize key information such as names, skills, education, and experience within resumes.
- Implemented a backend route using AWS Lambda, Flask in the Dynamo DB database on resume changes/additions.
iFAN Lab | Georgia Institute of Technology - Atlanta, GA
- Worked with Dr. Fan Zhang in analyzing the areas of use for ML and Generative AI in a nuclear power plant.
- Analyzed the security vulnerabilities within an Autonomous ML-based power plant and theorized plans of attacks.
- Built attack strategies using Adversarial Machine Learning techniques to infiltrate the plant and cause undesirable behavior.
- Began development of a Bi-directional GAN for anomaly detection within the nuclear power plant.
Georgia Institute of Technology - Atlanta, GA
- Worked 20 hours/week as TA for Computer Organization and Programming, managing a class of 835 students.
- Leveraged strong foundation in C and Assembly, as well as strong interpersonal skills to teach and guide students.
- Recognized for exemplary teaching, with Thank-A-Teacher Award.
- Conducted consumer research to address the need for authentic social interaction, leading to the creation of "Three," an app that enhances connections through daily three-word summaries.
- Implemented sentiment analysis using LLMs to create a "mood wheel," visually summarizing friends' emotions.
- Developed a secure journaling feature with FaceID integration, allowing for private introspection and reflection.
- Incorporated gamification, including mood-based challenges and streaks, to boost user engagement and consistent interaction.
- Published an iOS app for learning Morse Code by converting hand poses to Morse with 150+ downloads.
- Utilized Machine Learning (CoreML) and Computer Vision (Apple Vision) to track key points in the hand.
- Led a team of 9 developers leveraging Swift and SwiftUI to create an innovative and interactive experience.
- Developed supervised and unsupervised learning models to recommend movies to users using 25 million data points.
- Clustered movies using KMeans, DBSCAN, GMM, and Bag-of-Words text embedding, PCA for data processing.
- Developed a supervised learning model using k-NN, SVD, and Random Forests to recommend movies to users based on past preferences.
PictionAiR: Pictionary in AR, iOS Application | Swift, SwiftUI, Computer Vision (Aug. 2023 -- Dec. 2023)
- Developed an iOS app enabling users to play Pictionary by drawing in augmented reality using the MVVM design pattern.
- Leveraged Multipeer Connectivity to facilitate local device connections, sharing curated packets with Game Manager data.
- Utilized ARKit to create a shared AR space by synchronizing placed nodes and anchors across devices.
- Designed an image classification model for 3D AR image detection, integrated an LLM API for custom category generation.
- Semester Project for CS 2340: Object-Oriented Programming
- Worked in a team of 5 using time-boxed sprint development.
- Developed Frogger game with a focus on Object-Oriented Programming practices.
- Incorporated Collision Detection, Object Inheritance.
- "How Discrete Mathematics Empowers Strong Security of RSA Cryptosystems"
- Researched RSA Cryptography, underlying algorithms, and analyzed effectiveness.
- Constructed a 46-page report encompassing 150+ hours of research, compilation, and collation.
- Built a Game Boy Advance game, implementing collision logic to avoid moving targets.
- Implemented states for different parts of the game, a video buffer allowing for collisions, responsive animations, and detailed graphics.
- Implemented a modification of Dijkstra’s shortest path graph algorithm to model the Rubik’s cube.
- Developed an algorithm based on the Old Pochmann Method.
- Created a Wordle clone using JavaFX scenes, panes, layouts, nodes, and event-based programming.
- Implemented a user-friendly, customizable UI (Dark Mode, Instruction Boxes, Easy Maneuverability).
- Handled a $10,000+ budget and oversaw all club operations.
- Ensured smooth running of events with 100+ individuals and coordination between multiple teams.
- Led several teams of developers producing user-friendly, useful, and impactful iOS apps.
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Key member of the Strategy and Race-Ops team.
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Developed a strategy using Python to simulate the optimal way to manage the car’s scarce resources.
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Pulled data from an API (Solcast) to gauge conditions on race days.
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Processed JSON files and utilized Python libraries (NumPy, SciPy, and Pandas).