Masters of Science in Computer Science

2023 - 2024

State University of New York at Binghamton, Binghamton, NY

I completed my Master's of Science in Computer Science at SUNY Binghamton with a GPA of 3.53.

Relevant Coursework:

• Design Patterns
• Computer Architecture and Organisation
• Programming Languages
• Operating Systems
• Database Systems
• High Performance Computing

Bachelors in Computer Science

2019 - 2023

Vellore Institute of Technology,Amaravati,Andhra Pradesh

I graduated with a Bachelor's of Technology in Computer Science from VIT-AP with a CGPA of 9.01.

Senior Secondary

2017 - 2019

Brightlands School,Dehradun,Uttarakhand

I completed my Senior Secondary education from Brightlands School, Dehradun with a score of 95.75%.

Secondary

Completion : 2017

Brightlands School,Dehradun,Uttarakhand

I completed my Secondary education from Brightlands School, Dehradun with a score of 91.20%.

• Language: English(IELTS SCORE: 7.5), Hindi, Telugu
• Programming languages: Java, Python, R Programming, JavaScript, C, TypeScript, SQL
• Tools: Linux/Unix, Git, CUDA, React, Bash, Makefiles, Pandas, PyTorch, Tensorflow. Flask, MongoDB, Zsh
• Software: Microsoft Offices (Word, Excel, PowerPoint), Google Workspace(Docs, Slides, Calendar,Drive), Tableau, Audacity(basic), Cisco Packet Tracer.
• Other Skills: Strong communication and interpersonal skills, Excellent organizational and time management skills,Detail–oriented and able to multi–task,Ability to work well in a team environment and independently, Efficient use of LLM’s for debugging and development.

Post-Baccalaureate Researcher

April 2026 - Present

Caltech/IPAC – NASA/IPAC Infrared Science Archive (IRSA), Pasadena, CA

• Contributing to AI-powered tooling at IRSA, the NASA/IPAC Infrared Science Archive at Caltech, which provides science operations, data archives, and user support for NASA astrophysics missions including the recently launched SPHEREx all-sky spectral survey.
• Building an LLM assistant application to help researchers and scientists discover, query, and interact with large-scale astronomical data products, improving accessibility and accelerating scientific discovery across the archive.

Associate Developer (AI)

October 2025 - March 2026

Insurity

• Architected PremiumIQ, a full-stack platform with 15+ microservices and a React frontend, replacing a legacy ColdFusion monolith by implementing service discovery, API gateway patterns, and event-driven architecture using PostgreSQL and Prisma ORM.
• Reduced system integration time by 96% (from months to minutes) through automated field mapping of 157 out of 162 fields across 809 database tables with 12,000+ columns, leveraging Claude AI semantic analysis and batch processing.
• Engineered type-safe REST APIs with Zod validation, RBAC supporting 10 roles and 40 permissions, JWT authentication with MFA, Helmet security headers, and structured logging for production observability.
• Delivered a business rules engine processing 584+ insurance audit rules with 99.8% accuracy by implementing Chain of Responsibility and Strategy design patterns for consistent policy enforcement.
• Built an SFTP file transfer service and integrated external MSSQL databases by reverse-engineering a legacy Java codebase through systematic analysis of business logic layers and DAOs.
• Implemented RAG-powered in-app guidance using embeddings and vector search, improving user task completion rates by 35% through prompt optimization and retrieval tuning.

Research Intern

February 2025 - Present

Binghamton University

• Developed a Chrome extension fully integrated with Gmail to generate AI-powered email replies via Claude LLM, streamlining communication workflows and reducing manual reply time by over 50% using a React.js frontend and Spring Boot backend
• Built secure, scalable backend services in Java Spring Boot to handle over 10,000 Claude API requests per day, implementing caching strategies and encrypted key management to reduce response time by 40% and ensure data security
• Designed and deployed intuitive, real-time UI components into Gmail using React.js and Chrome Manifest v3, enhancing user experience by delivering contextually relevant email replies and responsive feedback within the native email interface
• Engineered a Retrieval-Augmented Generation (RAG) system capable of processing and querying large-scale domain-specific PDF documents, leveraging PGVector embeddings to improve AI-generated response accuracy
• Reduced Claude API usage costs by 30% through optimization techniques including token truncation, query filtering, and dynamic prompt resizing, significantly improving overall system efficiency and scalability
• Streamlined query handling by developing RESTful API endpoints, integrating contextual retrieval logic, and implementing error handling and logging for smoother debugging and usage analytics

Computer Vision Engineer(Intern)

November 2021 - June 2022

Mukham

• Contributed in the development of an advanced facial recognition and Geo-Tagging based attendance system.
• Enhanced face comparison accuracy by 20% through implementation and fine-tuning of the DeepFace model, resulting in 95% overall accuracy in face verification and identification tasks.

Deep Learning Intern

June 2020 - September 2020

AIR CENTER , VIT-AP

• Engineered a Retail Product Classification System covering 200+ product classes, achieving over 90% accuracy, by fine-tuning state-of-the-art deep learning model on Retail Product Classification dataset.
• Boosted object detection capabilities by remodelling YOLOv5 for retail-specific use cases, and developed a Flask application for efficient model deployment and real-time predictions.

Hand Motion Controlled Robotic Vehicle

August 2019-November 2019

VIT-AP

• Led a 4-member team to develop a hand motion controlled robotic vehicle, improving project efficiency by 30% through strategic task delegation, ensuring on-time completion despite technical challenges.
• Engineered a responsive Arduino-based control system with 95% motion detection accuracy, securing a top 10 position among 400 competing groups and demonstrating innovative design in a highly competitive academic environment.

Machine Learning Lead

July 2021 - July 2022

GDSC , VIT-AP

• Led the XploreML event, attracting 75+ participants, by organising workshops, creating educational posters, and fostering a shared learning environment, resulting in a 40% increase in ML project initiatives among students.
• Mentored fellow students in machine learning concepts and projects, contributing to a 50% growth in the GDSC community size and a 50% increase in ML-focused participation within the club.

AutoInsight Hub

Aug 2024 - Dec 2024

• Architected a full-stack car review analytics platform using Spring Boot backend and React frontend, integrating Claude AI to automatically summarize 1000+ monthly Reddit posts, reducing user research time by 80%.
• Constructed robust RESTful APIs with Spring Boot for data processing and retrieval, implementing rate limiting and comprehensive error handling while using Maven for dependency management.
• Designed efficient MongoDB schemas and integrated Spring Data MongoDB for optimized data persistence, implementing caching strategies to improve response times.

High-Performance Ball Sampling Simulator

April 2024 - May 2024

• Implemented a a Monte Carlo simulation for hypersphere sampling in C, optimizing it with CUDA for GPU acceleration and SIMD instructions for parallel processing on CPU.
• Achieved a 10x speedup with the CUDA version and 2x speedup with SIMD compared to the baseline C implementation, demonstrating proficiency in parallel computing and low-level optimization techniques.
• Leveraged an OpenHPC cluster to run the CUDA version, resulting in 98% GPU utilization and processing 30,000 samples across dimensions up to 16, demonstrating scalability in high-performance computing environments.

AI Sentiment Analysis in Developer Community

April 2024 - May 2024

• Analyzed AI adoption sentiments among 90,000+ developers by implementing complex NoSQL queries in MongoDB, revealing correlations between AI attitudes and factors like age, location, and income.
• Improved data accessibility and understanding by developing an interactive web application using Flask and Plotly, resulting in 4 distinct visualization types for multifaceted sentiment analysis.

Library Management System (MERN Stack)

January 2024 - April 2024

• Engineered a comprehensive library management solution with TypeScript, implementing RESTful APIs for book search, checkout, and return functionalities using Express.js and Node.js
• Built a responsive React frontend with complex state management and real-time updates, while incorporating thorough input validation using Zod schema validation
• Established MongoDB data models with indexed queries for efficient search operations, integrating Mocha and Chai for automated testing coverage

Concurrent Client-Server Prime Query System

September 2023 - October 2023

• Created a multi-threaded Java application using TCP/IP sockets and ConcurrentHashMap to handle parallel client requests for prime number verification with thread-safe operations
• Formulated a modular architecture incorporating a 4-level singleton debugger and efficient prime-checking algorithms, ensuring robust error handling and loggingImplemented custom file processing utilities with buffered I/O operations, utilizing Ant for automated build processes and dependency management

Student Course Registration System

September 2023 - October 2023

• Designed a Java-based course registration system utilizing HashMaps and Sets to efficiently allocate students to courses based on preferences, capacity, and time conflicts, while processing over 1000 requests with O(1) time complexity for most operations.
• Implemented a First-Come-First-Served (FCFS) algorithm with batch processing and modular architecture, improving system efficiency by 40% for large datasets and enhancing code maintainability for future expansions.

APEX CPU Pipeline Simulator

August 2023 - October 2023

• Developed a 5-stage APEX in-order pipeline simulator in C, featuring Fetch, Decode, Execute, Memory, and Writeback stages, with integrated Branch Target Buffer (BTB) for branch prediction.
• Enhanced performance over stalling by implementing branch prediction and reducing cycle count by 25%.

Pickster

November 2021 - July 2022

• Improved Optical Character Recognition accuracy by 30% in a group project developing a comprehensive document processing system, by implementing an advanced OCR solution using pytesseract.
• Processed over 50 documents with 95% text extraction accuracy, contributing to a 20% overall increase in document processing efficiency for the integrated OCR, image captioning, and text summarization pipeline.

Statue of Equality

June 2021 - November 2021

• Collaborated with a team of 3 to develop high-quality deepfake for an interactive AI chatbot system.
• Utilised GFPGAN to improve the visual realism by 40% of the deepfakes generated using First Order Model.
• Implemented real-time voice cloning with 90% similarity accuracy and integrated deepfake video and cloned voice outputs with a speech-to-text enabled chatbot, enhancing the user interface.