Peer to Peer Replicated and Fault Toleratant File System
Developed with Python sockets, and an algorithm was developed to replicate the file over nodes in the system to provide a failure resilient architecture
Hi! I'm Ambrose Tuscano, a Computer Science Graduate and a Software Engineer at Amazon Advertising.
Ambrose is a talented Backend Developer with a strong academic background in Computer Science. Currently excelling as a Software Engineer at Amazon, Ambrose demonstrates proficiency in Java, Python, JavaScript and SQL, along with expertise in developing distributed backend software, building REST-based APIs, and working with databases like DynamoDB and PostgreSQL.
He has a track record of optimizing application performance, implementing efficient data pipelines, and consistently delivering high-quality code. Additionally, he showcases versatility and the ability to meet diverse client requirements through a proven history of freelancing for web development and data analysis projects. He is committed to continuous learning and staying updated with emerging technologies in the field.
To connect over a cup of coffee email at ambrosetuscano@gmail.com
Major Life Events
Events that shaped my career to date.
-
Graduated with a Bachelor of Engineering in Computer Science from University of Mumbai
-
Vice Chair For UMBC ACM Team
-
Teaching Assistant for CMSC 455 : Numerical Computations
-
Research Assistant for AI-SSGL Lab at UMBC researching on Fake News Detection. Profile at: https://ai-ssgl.umbc.edu/ambrose-tuscano/
-
Teaching Assistant for CMSC 676 : Information Retrieval
-
Teaching Assistant for CMSC 203 : Discrete Structures
-
Machine Learning Intern at NXP Semiconductors
-
Teaching Assistant for CMSC 626 : Principles of Computer Security
-
Graduated with a Masters of Science in Computer Science from University of Maryland, Baltimore County
-
Software Engineer at Openprise
-
Software Engineer at Amaazon Advertising
Projects
Document Retreival System
Actualized a document similarity methodology to query documents usining keywords and find the most relevant documents to a search. Created GUI to work with it.
TV series Recommendation
Created Flask Api which used content based and collaborative methods to recommend users TV series, on a Android app with 86% accuracy.
How Fake Hate News affected politics
Analyzed news sources using BERT and other sentimental Analysis techniques to see how hate based news were used by fake sources to try and manipulate the 2020 US Election.
Diabetes Detection
Created a Heroku based service to detect Retinopathy by means of using Resnet, with an accuracy of 89% and used ResUNet to localize the detection.