I earned a Bachelor of Science in Computer Engineering from UC San Diego, graduating in September 2024. Over the course of my studies, I developed a strong foundation in designing algorithms, implementing complex systems, and creating software solutions for real-world challenges. I also gained valuable experience in collaborative development, problem-solving, and applying advanced concepts in artificial intelligence, data analysis, and web development.
I am currently working as a Member of Technical Staff at Perplexity, where I apply my expertise in full-stack engineering and AI to build advanced systems that elevate the user search experience. I focus on developing end-to-end solutions, from backend architecture to front-end features, integrating AI-driven functionalities that drive user engagement and introduce innovative capabilities. Additionally, I collaborate closely with cross-functional teams to align technical strategies with business goals, contributing to impactful product developments.
As a Software Engineer at a Fintech startup, I built and maintained a platform designed to provide real-time updates and ensure seamless scalability. I led the development of core features that improved user engagement, optimized backend workflows to increase data processing efficiency, and designed tools to deliver interactive experiences for users. My work also included streamlining deployment processes and improving the reliability and consistency of platform releases.
I achieved the Eagle Scout Rank in the Boy Scouts of America program, a prestigious distinction earned by only 4% of scouts, demonstrating leadership, dedication, and a commitment to community service. Additionally, I graduated in just three years while consistently earning Provost Honors, recognized four times for maintaining a quarterly GPA above 3.5, reflecting my strong academic performance and discipline.
Here are some of my recent projects:
A captivating mobile game designed for word game enthusiasts: an enhanced version of the classic Boggle game. This app allows players to choose from diverse board configurations, unlock intricate themes, and select their preferred game time limit. After each game, players are presented with all potential words, along with their definitions. The use of a trie data structure ensures efficient and precise word searches.
Technologies Used: React Native, Express.js, Node.js, Firebase, and AWS.
A predictive machine learning model was developed to accurately forecast business ratings, aimed at providing valuable insights into how geolocation affects business ratings in California. This model analyzes business categories and geolocation data to predict ratings, helping users understand potential business performance in various locales. It features an in-depth analytical report that explains the dataset used, the algorithm selection process, and the techniques employed for parameter tuning and result validation to ensure optimal accuracy.
Technologies used: Python, NumPy, scikit-learn, pandas, and statsmodels.
PopcornPal is an advanced movie recommendation engine built using a Retrieval-Augmented Generation (RAG) approach. It integrates the power of OpenAI's GPT API to process user queries and summarize results, along with the TMDB API to fetch real-time movie data. This project demonstrates the synergy between AI and modern web technologies to enhance user-centric movie discovery.
Technologies used: Next.js, TailwindCSS, DaisyUI, Express.js, and Node.js.
An interactive web application that showcases statistics for both current and former NBA players. It includes features such as the ability to add favorite players, compare players, generate random players, and view a detailed player profile. It also features user authentication and the ability to follow other users, make posts, and earn virtual coins. For demo account, Username: demo Password: demo1234
Technologies used: React.js, Express.js, Node.js, and MongoDB
