Developed "Nessus Parser," a Python package for automating CVE and CPE scanning and reporting using NIST database data
Implemented advanced data parsing algorithms, enhancing vulnerability analysis efficiency by 40%
Integrated customizable reporting features, improving tailored information delivery on security threats by 30%
Associate Software Engineer
GEP Pvt. Ltd
06.2022 - 02.2023
Harnessed the .NET Framework, AngularJS, and Java to develop robust, scalable components for supply chain management software (GEP Nexxe, GEP Smart), streamlining processes and boosting efficiency.
Engineered dynamic user interfaces using HTML and CSS, enhancing user satisfaction and experience.
Collaborated with cross-functional teams to translate client requirements into effective technical solutions, contributing to a 22% improvement in overall project delivery efficiency.
Conducted thorough code reviews, debugging, and iterative testing, ensuring high-quality software and a 15% enhancement in Agile process cycles. This collaborative effort facilitated data-driven decision-making and process optimization.
Education
Bachelor of Engineering - Computer Engineering
Terna College of Engineering
Navi Mumbai
05.2022
Master of Science - Computer And Information Sciences
Enhanced Operational Efficiency: Streamlined college management by implementing functionalities for real-time student attendance monitoring and automated record maintenance, leading to more efficient administrative processes.
Improved Communication: Facilitated seamless information dissemination through integrated systems, ensuring timely updates and enhanced communication between students, faculty, and administration.
E-Commerce Website
Engineered a saree sales platform utilizing ReactJS and Paytm API, incorporating secure payment processing, robust product search capabilities, a comprehensive shopping cart, and seamless user authentication.
Implemented efficient and secure e-commerce functionalities, enhancing user experience and transaction reliability through the integration of ReactJS for the frontend and Paytm API for payment solutions.
CPU Scheduling with Deep Reinforcement Learning
Improved Scheduling Efficiency: The CPU scheduling algorithm developed using Proximal Policy Optimization (PPO) enhanced overall scheduling efficiency by 35%, reducing average waiting time and turnaround time for processes compared to traditional scheduling algorithms.
Increased System Throughput: Implementing this deep reinforcement learning technique resulted in a 20% increase in system throughput, enabling the processing of a higher number of tasks within a given timeframe, thus optimizing system performance.
Publications
COLLEGE ADMINISTRATION & MANAGEMENT SYSTEM, International Research Journal of Modernization in Engineering Technology and Science (IRJMETS), April 2022
Certification
Cybersecurity and the Internet of Things, University System of Georgia May 2020
Python Data Structures , University of Michigan May 2020
Timeline
Student Assistant
Prof. Joseph Brickley
03.2024 - Current
Associate Software Engineer
GEP Pvt. Ltd
06.2022 - 02.2023
Bachelor of Engineering - Computer Engineering
Terna College of Engineering
Master of Science - Computer And Information Sciences
Department Head of Commerce at KBS Commerce and Nataraj Prof. Sciences CollegeDepartment Head of Commerce at KBS Commerce and Nataraj Prof. Sciences College
Graduate Student Researcher at Indian Institute of Engineering Science and Technology (IIEST), Shibpur. Under Prof. Ujjwal SahaGraduate Student Researcher at Indian Institute of Engineering Science and Technology (IIEST), Shibpur. Under Prof. Ujjwal Saha