Name: Shreyas Muralidhara
Type: User
Company: Amazon
Bio: Data Engineer at AWS - DBS RedShift. Computer Science Graduate Student, NC State University. Fields of interest Software Development, ML, NLP, Systems.
Location: Palo Alto, California
Blog: https://www.linkedin.com/in/shreyas-muralidhara-a77b8b70/
Shreyas Muralidhara's Projects
A lightweight server clone of Azure Storage that simulates most of the commands supported by it with minimal dependencies
Implementation of LSTM time series tuned with GRU.
Application developed as a part of curriculum project CSC540, using Maven for managing the university parking system
A priority based email queue solution to address this problem. Also, further extended this feature with an automatic response recommendation that would help in cleaning mails faster.
Highly performant data storage in C++ for importing, querying and transforming variant data with C/C++/Java/Spark bindings. Used in gatk4.
Fault Detection in Distributed System using Gossip Protocols. Team: Ritesh Ghorse, Shreyas Muralidhara, Tanvi Pandit.
Summer Internship 2020 - Proof of Concept demonstrates the FHIR API implementation for the HAPI endpoint, along with Oauth2 implementation.
Kubernetes Course Files
A ResNet50 based model to tackle the multi-class classification problem of detecting leaf wilting levels from plant images.
Implementation of basic machine learning algorithms and Artificial neural network models, from my coursework.
A bot designed to handle github issues, hosted on Mattermost platform.
Artificial Neural Network in R
Implementing Feature Engineering and Response classification on crowd sourced Reddit feed
classify sentences based on the sentiment they express, emphasizing on long sentences
🕵️♂️🍞 Sanity checking containers, vms, and servers
Predict the type of arrhythmia based on Electro-cardiogram (ECG) tool using machine learning models and algorithms.
Implemented Demand Paging on XINU using backing store descriptors, with scope of implementing Second Chance(SC) and Least Frequently Used(LRU) replacement policies
Getting Acquinted with XINU Call Stack, Stack Pointer and Base Pointer. Also implemented two new scheduling policies, which avoid the starvation problem in process scheduling.
Implementation of readers/writer locks with priority inheritance mechanism to prevent the priority inversion problem when using locks.