B.S Computer Science

New Brunswick, New Jersey

GPA: 3.85, Magna Cum Laude

South Brunswick, New Jersey

Amazon

Bellevue, WA

• Part of the Optimal Inventory Health team under SCOT.

Deloitte Touche Tohmatsu Limited

Princeton, NJ

• Reduced database access points by 70% throughout the multi-cloud architecture to enhance security.
• Integrated a robust monitoring tool for the service, providing real-time logging and tracing.
• Improved AWS and Azure infrastructure, leading to a 10% decrease in response time of the service API.
• Implemented a tool that periodically pings the service’s APIs in order to assess their health and provide statistics, improving service health visibility and allowing all APIs to be monitored on a central page.
• Used queries provide insights from the data ingested from monitoring tools, providing an executive dashboard to monitor the whole service.
• Created a notification system to alert engineers when the monitoring tool has detected anomalies, effectively reducing response times to an instant.

Deloitte Touche Tohmatsu Limited

Princeton, NJ

• Part of the Object Managed Neural Inventory Team, which allows centralized tracking of company-wide subscriptions, events, etc. across multiple cloud platforms.
• Assisted with development and modernization of a multi-layered cloud architecture, learning about the intricacies and differences between the three major cloud platform services (AWS, GCP, and Azure).
• Maintained and kept multiple repositories updated, working with platform teams when needed.

Deloitte Touche Tohmatsu Limited

Princeton, NJ

• Used monitoring and OSINT tools to research user-reported emails and determined whether they were malicious.
• Worked with senior analysts and global member firms and followed proper protocols to eradicate malicious emails from global mail boxes.
• Led an intern project aimed to allow hybrid workers to connect with their teams and colleagues through chats, puzzles and VR.

Python, AWS, Spotify API

• Developed a program that automatically saves a user’s recently played songs on a playlist.
• Songs are assigned a lifetime, which dictates how long they stay in the playlist before being rotated out.
• Song’s lifetime determined by how similar it is to the user’s music preferences using a KNN model.
• Service deployed on AWS using serverless deployment, with an efficient and scalable architecture.

HTML, CSS, Javascript

• The website you are currently viewing!
• Built from scratch using basic HTML, CSS, and Javascript.
• Dynamic elements to be added in the future using Javascript.

Python, OpenAI, Pinecone, Flask

• An interactive program that allows users to converse with a number of pseudo-sentient NPCs.
• NPCs reside in a meticulously created world, named "Talis", that is rich with different regions, countries, people and religions.
• NPCs respond to the user based on many different aspects, including (but not limited to) the user's previous responses, the NPC's region and beliefs, and the user's traits.
• Levarages a vector database to limit the NPC's information to be relevant to only their traits (region, town, species, etc.).

Python, Pandas, SKlearn, Spotipy

• An application which adds songs to a user's Spotify queue based on their current heart rate.
• Aimed to help athletes maintain their pace while exercising, preventing slower songs from being played during a high-intensity activity.
• Uses a KNN model to also randomly add songs that the user has never heard before, akin to Spotify's "smart shuffle".
• Built at a 24-hour hackathon, winning first place in the health track, which shows the potential positive impact that can be achieved from the application.

Python, NumPy, Pygame

• Developed efficient implementations of repeated A* algorithm to find the shortest path in a maze with barriers.
• Efficient implementations led to a 96% improvement in speed, and 96% less number of nodes expanded during the search.
• Conducted extensive testing of the algorithm, and achieved a 99% success rate in finding the shortest path and resolving edge cases.

Python, SKlearn, Pandas, NumPy, Matplotlib

• Developed an application that uses an LSTM model to predict the stock prices of a given ticker.
• Can be trained on datasets taken from Kaggle and other data sources.
• Outputs predictions that are, on average, 10% within the true price of the stock.

Ever since I was a kid, I would always play video games on my Playstation 2 with my older brother such as Tekken 5, Gran Tourismo 4, and Ratchet and Clank! When I got to middle school, I quickly bought myself a PS3 and later a PS4 to play games such as Call of Duty, Destiny, and others. I then built my first PC when I was a sophomore in high school, and moved to playing FPS games such as CS:GO, Valorant, Destiny 2, and also RPG games such as Elden Ring. My current interest is Tekken 8, which is a nice full-circle moment.