DynamicRNA
Developed a machine learning model to predict RNA folded secondary structure using Structured SVMs and dynamic programming.
MSCS @ NYU Courant
I am a graduate from the University of Manchester where I studied Computer Science and am currently enrolled as a master’s student at NYU Courant. I started programming and learning about the field of software development about 6 years ago when I wrote my very first “Hello, World!” program-tens of thousands of lines of code later in numerous projects and web apps, I have not looked back. I am most comfortable working with Python and Java but do have experience in C/C++ and JavaScript as well. The various projects I have worked on range from topics like Natural Language Processing to Computational Biology to exploring gradient based optimization in neural networks written from scratch in C.
NYU Steinhardt School of Culture, Education, and Human Development
5 mos · New York, New York, United States
Amazon
3 mos · Seattle, Washington, United States
• Interned with the Talent Evaluation team within Amazon’s People Experience and Technology (PXT) org, focusing on improving reliability and observability of internal evaluation services. • Built a canary stack which injects synthetic traffic to all of the services owned by the team in preprod environments to enable continuous monitoring. The technologies involved ranged from AWS Lambda and CloudWatch to Amazon’s internal testing system and CI/CD framework.
NYU Steinhardt
3 mos · Brooklyn, New York, United States
• Worked under NSF-funded research led by Prof. Kayla Desportes on the Creative Computing Cookbook project to support equity-oriented computing education. • Integrated interactive Parsons problems using the js-parsons library and built internal tooling to automate content workflows, streamlining on-boarding and updates for contributors.
The University of Manchester
4 mos · Manchester, England, United Kingdom
Discover Financial Services
3 mos · Farnborough, England, United Kingdom
Collaborated with the Business Technology team to enhance the Diners Club International portal. Developed an automated health-check system using Playwright and Java, reducing manual testing hours for the Digital Payments team through process streamlining and refactoring of health-check systems.
Discover Financial Services
3 mos
• Collaborated within the Business Technology team to enhance the Diners Club International portal, leading the development of an automated health-check system using Playwright and Java. • Achieved significant efficiency gains for the Digital Payments team, reducing hours of manual testing by streamlining processes and refactoring health-check systems for critical sub-applications.
EY
2 mos · Noida, Uttar Pradesh, India
Amazon
1 mo
Discover Financial Services
1 mo
Amazon
June 2025 – August 2025 · Seattle, WA
Worked with the Talent Evaluation team within Amazon’s People Experience and Technology organization to improve reliability and observability of internal evaluation services. Built a canary stack injecting synthetic traffic into team-owned services in preproduction environments for continuous monitoring, using AWS Lambda, CloudWatch, Amazon’s internal testing system, and CI/CD frameworks.
NYU Steinhardt
March 2025 – May 2025 · New York, NY
Worked on the NSF-funded Creative Computing Cookbook project led by Prof. Kayla Desportes to support equity-oriented computing education. Integrated interactive Parsons problems using js-parsons and built internal tooling to automate content workflows, streamlining contributor onboarding and updates.
Master of Science - MS, Computer Science
Aug 2024 - May 2026
BSc (Hons), Computer Science
Sep 2021 - Jul 2024
2014 - 2021
Bachelor of Science, Computational Science
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Master of Science, Computational Science
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Coursework: GPU Programming, Efficient AI, Compiler Construction, Parallel Algorithms, Heuristic Problem Solving.
BSc (Hons), Computer Science
Sep. 2021 – July 2024
Coursework: Natural Language Processing, NLU, Knowledge-Based AI, Distributed Systems.
Developed a machine learning model to predict RNA folded secondary structure using Structured SVMs and dynamic programming.
Designed a neural network for image classification using the MNIST dataset, implementing gradient-based optimization techniques.