Apurv Vidhate
Development
texas, United States
Skills
Python
About
Apurv Vidhate's skills align with Programmers (Information and Communication Technology). Apurv also has skills associated with IT R&D Professionals (Information and Communication Technology). Apurv Vidhate appears to be an entry-level candidate, with 20 months of experience.
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Work Experience
Graduate Teaching Assistant
The University of Texas at Arlington
January 2024 - May 2024
- • Co-ordinated and guided hands-on lab sessions for CSE-1106, Introduction to Computer Science, providing 100 students with practical insights into programming languages, raspberry pi, circuits, and algorithms. • Worked closely with faculty to assist in formulating and updating lab exercises, grading criteria, and instructional materials, ensuring alignment with evolving course objectives • Served as a bridge between students and teachers by answering questions, sharing important information, and encouraging a friendly and helpful learning environment. Skills Languages: Python, C/C++, Java, Matlab, Scripting (Bash), HTML, JavaScript, XQuery, SQL Developer Tools: Git, Linux, TensorFlow, Pytorch, Docker, OpenCV, JIRA, Kubernetes Technical Skills: Data Structure and Algorithms, Internet of Things, Object Oriented Programming Projects
coordinator responsibilities
Distributed Transaction System
October 2023 - November 2023
- Oct 2023 - Nov 2023 • Orchestrated a robust distributed transaction system in Python, prioritizing efficiency and reliability. • Engineered a highly efficient client-server paradigm, leveraging a coordinator and two clients, resulting in a 40% reduction in data transfer latency and improved system response time by 50%. • Spearheaded coordinator responsibilities: initiated, managed, and concluded transactions, executing 3 critical operations such as preparation, committing, and aborting.
Visual Question Answering for Formula 1 Press Conferences
January 2023 - May 2023
- Developed Innovative VQA System: Created a cutting-edge Visual Question Answering (VQA) system tailored for Formula 1 press conference videos. • Applied 2 sophisticated computer vision methods, combining Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs), to process visual information in videos. • Analyzed Formula 1 press conference videos to identify drivers, teams, and racetracks; employed advanced video recognition algorithms resulting in a 40% increase in engagement from non-F1 viewers. • Conducted a comparative analysis against existing object detection and recognition methods, showcasing superior accuracy and efficiency in the conceived VQA system.
Visual Question Answering for Formula 1 Press Conferences
January 2023 - February 2023
- Created an interactive game using the minimax algorithm with alpha-beta pruning. Put into practice an AI player with a custom evaluation function, enabling strategic gameplay against a human opponent. • Utilized hash maps to store precomputed values, enhancing the minimax algorithm's efficiency by 25%. Enabled a custom gameplay by accepting command line arguments for initial marble configurations and calculating player scores based on removed marbles.
Visualization of Digital Elevation Model
August 2021 - July 2022
- Implemented precise visualization techniques for Digital Elevation Models (DEM) using GEOTIFF images, achieving an impressive accuracy rate of 92.68%. • Developed an intuitive and accessible front-end interface for seamless user interaction, enhancing the overall user experience. • Conducted comprehensive analysis of test cases, leading to the implementation of effective error detection mechanisms and improved visualization reliability.
Education
The University of Texas at Arlington
Master of Science in Computer Science
August 2022 - May 2024
