- 🚀 Build scalable data pipelines & backend systems
- 🌐 Create full-stack apps that solve real problems
- 🤖 Explore ML/DL for predictive & classification tasks
- ✨ Blend research + engineering for practical impact
- ZS Associates | Software Engineer (Aug'2023 - July'2025)
- At ZS, I engineered and optimized large-scale data pipelines leveraging Apache Airflow, Python, SQL, and AWS, automating end-to-end ingestion, transformation, and secure delivery processes.
- I worked on migrating 300+ GB of legacy data repositories to modern infrastructure, implementing integrity checks and monitoring scripts to ensure reliability and availability.
- My role also involved debugging complex production issues, redesigning SQL logic, and developing customer validation queries to stabilize core functionalities and improve system performance.
- Defence Research and Development Organization | Software Development Internship (May' 2022 - Jun' 2022)
- At DRDO, I developed a dynamic room reservation system using React.js, Node.js, PHP, MySQL, and Bootstrap, enabling seamless drag-and-drop scheduling and improving operational efficiency.
- I also implemented a secure authentication framework with advanced login tracking and email-based recovery, alongside building an admin dashboard with reporting/export features that streamlined data handling plus reduced manual effort.
- Astron – Enterprise Management Application Source Code
- Built a Java Swing desktop application backed by an AWS-hosted MySQL database to digitize manual textile workflows.
- Integrated interactive forms for stock/design/dealer management and automated order PDF generation via Jasper Reports, reducing errors and saving hours of administrative effort.
- Blood Donation Web Application Source Code
- Developed a full-stack platform with HTML, CSS, JavaScript, PHP, and MySQL to connect donors, patients, and centers through city-wide search and registration.
- Enhanced usability with OTP verification, chatbot assistant, and eligibility quiz, making the system secure, reliable, and engaging.
- Titanic Survival Prediction Source Code
- Implemented machine learning models in R for survival prediction using preprocessing, feature engineering, and classification techniques.
- Compared decision trees and Naïve Bayes, gaining insights into predictive modeling, visualization, and feature impact on real-world datasets.
- Prediction of COVID-19 using Deep Learning: A comparative Study Publication link - Conducted an extensive review of machine learning and deep learning techniques for COVID-19 detection using CT and X-ray imaging.
- Analyzed 60+ research studies covering dataset preparation, feature extraction, CNN architectures, transfer learning methods, and evaluation metrics, highlighting the potential of AI for early and accurate disease diagnosis.
- Potato Plant Leaf Disease Classification using Deep CNN Publication link - Proposed a deep CNN-based approach for classifying potato leaf diseases such as Early Blight, Late Blight, and Healthy categories.
- Explored pre-trained architectures and optimized CNN models to achieve high accuracy, demonstrating how AI can accelerate agriculture disease detection and support sustainable farming practices.
Master of Science in Computer Science (Sep'2025 - Present)
B.Tech Computer Engineering (July' 2019 - July' 2023)
CGPA: 3.75/4
- Recognized with the “Deep Diver” award at ZS Associates’ 2025 Rewards & Recognition ceremony for demonstrating end-to-end technical expertise across tools, pipelines, and business-critical processes.
- Selected as an open-source contributor in GirlScript Summer of Code 2022
