Arvind Sridhar's Projects
Abstractive text summarization using pointer-generated networks and coverage along with a baseline bi-directional RNN encoder/decoder model
Summer Internship 2018: Created ML/deep learning algorithms for large distributed datasets, along with associated utility functions, to enable parallel model training atop Pivotal's Greenplum database
Full stack web application to conduct online experiments detecting danger scenarios while driving. Built with Node.js, Angular, Python, MongoDB, HTML/CSS/JS
Full bash_it theme repo for iTerm2, includes themes such as bobby
Frontend prototype of app enabling students to order food from Bellarmine's cafeteria. Developed during high school.
CalHacks 2017: App that enables you to network with others at events using selfies, making it more memorable. React Native, Expo.io, Python (Flask)
Launchpad Fall 2018 Project: Detecting and responding to dangerous driving scenarios using deep CNN object detection/tracking, LSTM path prediction, & deep reinforcement learning; served as project leader
Exploring strategies to intelligently and efficiently train deep learning models on distributed datasets in parallel, merge/ensemble the results, and perform prediction on a test set. Inspired by my 2018 summer internship at Pivotal Software's Greenplum Advanced Analytics team.
Website that I created in high school for my nonprofit organization, Geography for Tomorrow Inc. Full stack, built with HTML, CSS, JS/jQuery, PHP on the backend, mySQL. Fully responsive for mobile/tablet form-factors.
TreeHacks 2018: App to determine the fair price of a medical procedure from a natural plain text description of the operation. Medical language parsing in Java, Python price scraper, Node.js web app
Basketball analytics challenge for the 2019 NBA Hackathon application
Placing the latest news on an interactive map, to visualize current events. Developed 2015-16 in collab. w/ the BCP App Dev Club & Geography for Tomorrow. Fully responsive PHP web-mobile app, iOS app
Launchpad Spring 2018 Project: Devised novel object tracking algorithms for path prediction of moving objects using YOLOnet v3, nearest neighbor clustering, regression techniques, LSTM models, OpenCV
Inference Code for Polygon-RNN++ (CVPR 2018)
ML@B Pytorch bootcamp, Aug. 25 2018
Read one-dimensional barcodes and QR codes from Python 2 and 3.
Scripts to automatically set up a machine for development the "Pivotal" way