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I am a recent graduate in Computer Science from the University of Colorado, Denver, with over two years of experience specializing in full-stack software engineering and machine learning systems. I am currently seeking new opportunities to apply my skills in impactful projects. During my graduate studies, I had the privilege of working under the guidance of Prof. Ashish Biwas in the field of machine learning. Additionally, I collaborated with Prof. Liang He on ARADISS (Adaptive Real-time Anomaly Detection and Identification for Space Systems), a project funded by NASA. My previous research includes Wind Turbine Anomaly Detection, where I focused on problem formulation and data-driven approaches, identifying the most correlated variables and building predictive models using SCADA data.
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Relevant Coursework: Machine Learning, Computer Vision, Big Data Science, Artificial Intelligence, Deep Learning, Advance Computer Architecture, Operating Systems and Algorithms.
• An end-to-end e-commerce website with 3 core functionalities like user identification, product creation, and cart functionality.
• Implemented features like user session management, checkout process, wishlist, and price filtering, enhancing the platform’s user
experience and serving over 1,000 users.
• Created a transaction system using Java and the Spring Framework, adhering to MVC architecture.
• Implemented CRUD operations to manage transaction data and integrated event logging capabilities to ensure 100% accurate tracking and auditing of all transactions.
• Trained 5 different models like Decision Tree, K-nearest neighbors, boosting, and bagging models, performed EDA, data transforma-
tion, and designed a data pipeline deployed on Microsoft Azure.
• Achieved optimal model selection using R-squared (R2) metrics to capture variability in student performance data
• Develop Web App for Traffic Signal recognition, employing a CNN model via Keras. Backend powered by Python, and Flask, enabling model interaction. Leveraged ReactJs for a responsive frontend.
• Used OpenCV for real-time video frame capture from a webcam, implementing image processing functions for preprocessing. Integrated Mediapipe for hand tracking, leveraging pre-trained models to extract 3D hand landmarks. Used Euclidean distance calculations between hand landmarks, enhancing finger point analysis.
• Conceptualized pricing reduction strategy using parameters like expiry dates to enhance sales and minimize discarded inventory.
• Generated a dataset with 1000+ different food products, did data mining, and data modeling using supervised learning (Linear
Regression).
• Designed a working prototype of a chain reaction game using a minimax algorithm with alpha-beta pruning.
• Technologies used: Python and Pygame libraries.
• A working prototype of a snake bot that was funded by the United Nations Development Programme and Navi Mumbai Municipal Corporation. Designed to find humans under any natural calamity. The technology used Arduino UNO, a C language to code and control the movement of the servo motor.
• Implemented an AI-based application for object detection.
• Technologies used: Caltech 101 dataset, OpenCV, TensorFlow, and Android Studio.
• Designed an IoT-based project for collecting cleanliness feedback from public toilets via a display system.
• Prototype included sensors to count entries and an automated system for the toilet.
• Technologies used: Arduino UNO, IR sensor, Relay Motor.