C++, Python, Java, C, JavaScript, HTML, SQL, Flask, CSS, Typescript;
AWS Lambda DynamoDB, API Gateway, NoSQL, jQuery, Git, Agile, Spread, Gradle;
Practiced infrastructure as code by creating and maintaining > 10+ cloud application resources such as Lambda Functions and Dynamo DB tables via AWS Cloud Development Kit in TypeScript and deploying through AWS CloudFormation
Built a serverless application that identifies and keeps track of 50+ types of missing CloudWatch alarms in any resource deployed via AWS CloudFormation(CFN) using Lambda Functions(Python) by scanning customers' CFN stacks
The application built to lower service's teams mean time to resolution (MTTR) and the amount of COE's accross the platform
Designed and implemented a website in React and Typescript and deployed via CloudFront that provides access control , onboards customers to the service and displays missing CloudWatch alarms data with filtering and aggregation;
Used AWS Step Functions to provide scalability and reliability to the system and optimize execution time by over 50% ;
Used Microsoft Azure Cognitive Services to extract information of any photo and incorporated it into a WeChat program that can perform landmark recognition in seconds with high accuracy;
Built the project’s website through HTML/CSS and connected the front and back-end via JavaScript;
Implemented a revised version of anti-entropy algorithm to ensure that the states of all five servers will eventually be consistent and used knowledge matrix to solve network partition and merging problems;
Used csv files to store the logs and states of the server to deal with server crashing and recovery;
Implemented the overlaid heatmap layer that displays the severity of each incident based on its crime code and added individual markers to represent each incident with the reported location and description;
Implemented the observer pattern by sending out emails to all subscribed users when an incident is reported;
Created tables to store incidents and users’ information and used SQL queries to interact with the database system;
Used React.js to connect the front-end and back-end applications which allow users to safely upload and retrieve their genetic data to/from a fully distributed blockchain system;
Applied Ganache , TruffleFramework (Solidity) and MetaMask to setup a blockchain network, write and deploy smart contracts to the blockchain and allow different accounts to interact on the blockchain;
Used Support Vector Machine with linear and gaussian kernel methods to predict the result of major soccer leagues;
Applied neural networks to the data set with a 90/10 split ratio, 8 hidden and 1 output layers, binary cross-entropy for the loss function and sigmoid activation function and obtained an improved performance from the SVM model;
Implemented Ukkonen’s algorithm in Python for linear time and space construction of a suffix tree;
Applied this implementation to find overlaps for strands of DNA sequences (ACTGs);