Masters of Science in Computer Science

2023 - Present

State University of New York at Binghamton, Binghamton, NY

I am currently pursuing my Master's of Science in Computer Science at SUNY Binghamton and my current GPA is 3.518.

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.

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.

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

• Architected a comprehensive full-stack library management solution utilising MongoDB, Express.js, React, Node.js, and TypeScript, crafting RESTful APIs for book search, checkout, and return functionalities.
• Developed a robust backend with error handling and custom response envelopes, alongside a responsive React frontend with complex state management, resulting in a 40% improvement in library task efficiency and seamless real-time updates.

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.