Vineet Agarwal

Created a CRUD GUI application for downloading and processing satellite images. Implemented an API wrapper for USGS datasets and improved application responsiveness through RabbitMQ.

Developed LLM-based agents for a game engine, enhancing NPC behavior through memory and environmental changes. Improved NPC lifelikeness with advanced AI architectures.

Developed a REST API and frontend application for generating patient treatment reports. Implemented scheduling algorithms to optimize patient visit times, increasing accommodation by 10%. Designed a relational database schema for managing patient details using SQLite.

Analyzed use-cases for JupySQL, designed software architecture for complex query expansion, and developed an optimized flow in the expansion engine. Implemented deduplication mechanisms to enhance functionality and performed extensive unit testing.

Engineered a mobile-first Angular web application and an Android app for event searching. Developed a custom backend API integrating Ticketmaster and Spotify APIs.

Constructed and analyzed L1-penalized SVM and k-means models, applying cross-validation and visualizing performance metrics. Conducted comparative analysis of various machine learning methods.

Trained vision transformer architectures for image classification using PyTorch. Preprocessed datasets of histopathological images and fine-tuned models to improve accuracy by over 6%. Collaborated on internal deep learning infrastructure.

Designed a blockchain system with backend servers for transaction storage. Established TCP and UDP communication for client-server interactions, enabling account balance queries and transfers.

Architected CNN-based segmentation models for brain imaging, achieving 99% accuracy. Utilized GANs for image harmonization and developed a Quality Control system for model validation, awarded Best Website at DataFest '21.

Automated processing of satellite images and implemented a reprocessing pipeline for atmospheric distortion correction. Enhanced time series analysis capabilities and developed a software stack for geospatial analysis.

Grade: 3.52/4.0

Pursued a Master of Computer Science with a GPA of 3.52/4.0. Relevant courses included Advanced Web Technologies, Advanced Database Systems, Advanced Algorithms and Data Structures, Operating Systems, Machine Learning for Data Science, and Advanced Programming Languages.

Grade: 9.02/10.0

Completed a Bachelor of Technology in Mechanical Engineering with a GPA of 9.02/10.0. Relevant courses included Computer Programming and Embedded Systems.