* Collaborated with Disney+ to design, develop, and debug their streaming platform, enhancing user engagement and experience

Project Contributions : 1) Financial Clientele Management Solution* Developed an enterprise-level web application of an international investment group, using AWS, GraphQL, Node, React, Javascript* Implemented scalable APIs so that the company can manage their user information from all over the world seamlessly* Ideated and built out an extensible search module to handle over a million clients from the final dataset2) Transformer Analysis and Quality Assurance System* Enriched system metrics by integrating the platforms with Command Query Responsibility Segregation (multi-module) to enhance the performance metrics during heavy measurement calculation* Automated and optimized business logic for the core calculation experiments, including A/B, Auto-Targeting, and Multivariate TestingLeadership : * Provided guidance and mentorship to several junior developers, focusing on best practices, code troubleshooting, and navigating repositories* Played a crucial role in onboarding new team members, ensuring a smooth transition and integration into the workplace* Regularly conducted technical learning sessions, sharing my knowledge and insights with the team. These sessions not only helped in skill enhancement but also fostered a culture of continuous learning within the team

1) HR Management Software* Designed and implemented an enterprise HR application, generating a monthly revenue of $17 million, utilizing Angular, Node, Redis, Typeorm, Postgres, and AWS* Continuous Integration/Deployment Pipeline Integration, pull requests, code review, unit/integration testing2) Asset, Retirement, and Risk Management Platform* Engineered an enterprise FinTech application, using Typescript, Angular, .Net, Entity Framework, AWS and Postgres, which facilitated a transition to a fully digital system, achieving 12% cost reduction* Executed microservice strategies utilizing Docker, which improves system efficiency by 25%

1) Cross-Province Corporation Name Reservation System* Contributed to the development of a full-stack application, leveraging C#, .Net, MSSQL, Prism, and WPF* Refactored 30-year-old legacy codes in order to optimize performance and decouple dependencies on razor code within the application* Upgraded a Manitoba-exclusive system into a multi-provincial platform serving Manitoba, Saskatchewan, Quebec, and British Columbia

1) Predictive Algorithms for Stock Prices:Innovated and executed predictive algorithms specifically designed to forecast stock prices. Applied these sophisticated algorithms to real-world stock data, delivering actionable insights that significantly informed and influenced investment strategies.2) Research and Development in Machine Learning:Pioneered in-depth research in the realm of machine learning technologies, leading to the development of advanced neural networks. These efforts resulted in significant technological advancements and contributed to the overall growth of the company's technical prowess.3) Neural Network Implementation for Behaviour Prediction:Implemented an integrated neural network designed to predict human behaviour. This system, which was based on the analysis of individual activity records, provided valuable insights into behaviour patterns, aiding in the development of targeted business strategies and decision making.

1) AI Software for Emotion Detection:Developed an AI software designed to discern human emotions. This state-of-the-art software leveraged facial, voice, and behaviour recognition technologies, utilizing a Convolutional Neural Network in tandem with Reinforcement Learning. This breakthrough innovation significantly advanced our understanding and interpretation of human emotion cues.2) Recurrent Neural Network for News Analysis:Trained a sophisticated Recurrent Neural Network to analyze news articles and discern their potential impact on specific stocks. Utilizing NLTK (Natural Language Toolkit), this system could gauge whether the information in an article would have a positive or negative effect on the stocks in question. This project showcased the power of AI in financial market analysis and prediction.3) Collaborative Research and Analysis:Collaborated closely with Ph.D. students on a research endeavour to analyze the quantitative and qualitative results of various neural networks. This collaboration not only enhanced the quality of the research but also fostered a rich learning environment, contributing to the academic and professional growth of all participants.