EDUCATION
Master of Computer Science
Aug ‘23 - May ‘25
Arizona State University (ASU), Tempe, AZ(GPA: 4/4)
Coursework: Cloud Computing, Data Intensive System for Machine Learning, Data Mining, Principles of Programming Languages,
Data Processing at Scale, Mobile Computing.
Bachelor of Technology in Information and Communication Technology
Aug ‘18 - May ‘22
Dhirubhai Ambani Institute of Information and Communication Technology, India
Coursework: Database Management Systems, Data Structures and Algorithms, Systems Software, Computer Networks, Digital
Image Processing, Project Management
TECHNICAL SKILLS
Programming Languages: Python, C#, Go, C, SQL, Typescript , JavaScript
Frameworks/Libraries: Node.js, .NET, Nginx, Redis, MessageQueue, Langchain, Llama Index, Gradio, NumPy, Pandas, Matplotlib,
TensorFlow, scikit-learn, Seaborn, Flask, django, React.Js, Express.js, Ruby on Rails.
Databases/Tools: MySQL, AWS EC2, SQS, S3, and lambda, VSCode, Git, Excel, Postman, Docker, Hugging Face, Prompt Engineering,
OpenAI API, Linux, Kubernetes, Ansible, Nginx, Redis, RabbitMQ.
PROFESSIONAL EXPERIENCE
Student Software Developer, Arizona State University
Sept ‘23 – Present
● Led development of corrective retrieval-augmented generation(RAG) based chatbot system, facilitating 1000+ faculties to
design courses for 60,000+ students. (Python, Langchain, OpenAI, Prompt Flow, Semantic Kernel, Neo4j)
● Designed and implemented APIs and webpages for quiz platform and question bank in ASU Online courses. (Python)
● Supported the functionality and performance of backend services, contributing to the smooth operation of ASU online courses.
Software Engineer, Zeus Learning
Jan ‘22 – July ‘23
● Refactored the monolithic backend services into various microservices to optimize and scale the infrastructure using
Kubernetes, resulting in a 20% reduction in resource usage and a 35% cost reduction. (.NET, C#, MessageQueue, Redis, AWS
S3, Nginx, Docker, Kubernetes, RabbitMQ)
● Optimized students listing into multiple pages and the relevant SQL queries for fetching data in the class-details web page,
resulting in 30% faster screen loading and 10% improvement in the average latency. (Angular, JavaScript, AWS S3)
● Developed a space reservation system to book desks and meeting rooms for 300+ locations, enhancing occupancy rates and
facilitating efficient booking amidst COVID-19 restrictions for Goldman Sachs and Merck. (Node.js, Nginx, Redis)
● Formulated and integrated a custom node package for retrieving N-latest messages from Slack channels, including attached
media, documents, and reactions into an internal social networking web app for employees. (Node.js)
● Implemented a feature in the custom Learning Management System (LMS) to grade exams and link solution videos,
empowering 100+ teachers and 10k+ students to access educational resources seamlessly. (React.js, Node.js)
Product Intern, EAT.FIT
Sept ‘21 – Dec ‘21
● Took ownership to implement an order tracking system optimizing driver location tracking, reducing costs by 45% and
enhancing customer experience. (React.js, Google Maps API)
● Automated system to scrap competitor product details and reviews using script to better understand business data analytics ,
positioning of products, and better customer service following Software development life cycle. (Python)
PROJECTS
Image Recognition as a Service | AWS S3, AWS EC2, AWS SQS, Python
Jan ‘24 – Feb ‘24
● Developed an elastic cloud application using AWS EC2 and AWS SQS for automatic linear scaling based on demand providing
image recognition service through deep learning models, serving 100 concurrent requests in 5 seconds.
Soccer Game Result Prediction | Python, Deep Learning, Data Science, Statistics
Oct ‘23 – Dec ‘23
● Increased soccer game’s result-prediction accuracy by 12% using long short-term memory, recurrent neural networks, data
analysis and Random Forest classifier with XG Boost to supplement past game’s result with user tweets, sentiment analysis
and game’s bet data.
FitLife Health Tracking App | Android Studio, Matlab
Oct ‘23 – Dec‘23
● Programmed an android application measuring heart and breath rates, tracking daily exercise goals, and suggesting
personalized workout routines using machine learning and Fuzzy Logic Control in Matlab.
Reverse-Mode Automatic Differentiation | Python, CUDA
Feb ‘24 – March ‘24
● Implemented reverse-mode auto-differentiation to adjust weights in models using key concepts and data structures like
computation graph and Node, operators such as Add, MatMul, Ones and construction of gradient nodes given forward
graph. Added kernels for cuda GPU graph executor that can train simple neural nets such as multilayer perceptron
models.
