About Me
I'm a Developer & a Computer Science Student.
Currently working on my bachelor's in Computer Science at George Mason University. I'm all about building cool stuff—whether it's a large-scale app, a small-scale side project, or even a machine learning model. If it's interesting, I'm in.
Love exploring new tech ( especially Quantum Computing! ), finding creative solutions to everyday problems, and building cool projects that push my skills a little further each time.
Interests & Skills:
Experience
Dec 2024 – Present (5 months)
CEO & Founding Engineer
TheCollegeTech, India
- • Co-founded this startup that provides Managements Systems and Tech services to Colleges and Universities across India
- • Designed & developed two comprehensive large-scale Learning Management Systems (LMS) Platform and a Job Portal for Universities across India
- • Feature development for applications: Contributed to building new features for analytics applications, writing and testing code, and integrating APIs
- • Managed a team of 10+ developers and designers to deliver high-quality products on time and within budget
Skills:
Jan 2025 – May 2025 (5 months)
Data Analytics Intern
Eera Technology, Virginia
- • Built and tested AI/ML use cases for healthcare analytics: Researched, designed, and implemented machine learning models to address specific challenges in healthcare analytics
- • Developed AI/ML solutions for retail analytics: Implemented machine learning use cases tailored to retail analytics, including recommendation systems and sales forecasting optimization
- • Data preparation and visualization: Prepared raw datasets by cleaning, transforming, and standardizing data; created interactive visualizations and dashboards using Tableau
- • Conducted market research on analytics: Investigated current trends and emerging opportunities in data analytics across industries to inform business strategies
- • Feature development for applications: Contributed to building new features for analytics applications, writing and testing code, and integrating APIs
Technologies:
Jan 2024 – Present
CEC IT Technician and Help Desk
George Mason University
- • Provided first-level technical support to Faculty and staff, ensuring uninterrupted academic and research activities
- • Customized Linux, Windows, and Mac operating systems and software to meet the unique needs of each user, optimizing their work environments for maximum efficiency
- • Oversaw and resolved complex technical issues across the College of Engineering's student and research labs, managing over 250 workstations and handling network requests
- • Imaged, troubleshot, and set up Linux and Windows workstations for both personal and research purposes, tailoring operating systems and software to meet specific requirements
Technologies:
Projects
PlaceEasy
Comprehensive placement management platform
A full-stack web application designed to streamline the campus placement process. Features student profile management, company registration, application tracking, and automated matching between students and job opportunities.
Tech Stack:
Vidya LMS
Modern learning management system
A comprehensive educational platform built to facilitate online learning. Features course management, assignment submission, grade tracking, and interactive communication tools for students and instructors.
Tech Stack:
Data Analytics Workflow Automation
- • Develop an AI-driven platform that automates data analysis, insight generation, and executive-level summarization using advanced machine learning models, aiming to reduce manual analytics effort for business users.
- • Leverage LangChain to interpret both structured and unstructured data from diverse sources, enabling intelligent context-aware reporting with automated summaries for datasets.
- • Engineered a React.js front end for AI-driven analytics platform; empowered business users to configure models and upload CSV files, resulting in generation of insights.
- • Orchestrated backend infrastructure with Django, managing REST API endpoints to trigger machine learning model execution and asynchronous processing of complex data workflows, improving pipeline efficiency.
- • Deployed the application on scalable cloud infrastructure using AWS EC2 and Azure VMs, ensuring high availability, low-latency processing, and secure access for up to 100 concurrent users in pilot testing.
Tech Stack: