Azam Jawad Butt

Relevant Coursework: Data Structures & Algorithms, Artificial Intelligence, Discrete Structures for Computing, Databases, Theory of Computation, Analysis of Algorithms

Intensive summer fellowship (2.5% acceptance rate) building expertise in DevOps & SRE under mentorship from senior engineers

Built a recurring automation workflow for fixed-income securities data retrieval and monitoring on a high-pressure trading floor, saving ~5 hours per week in delivering market-critical alerts across multiple Sales & Trading (S&T) teams

Designed and developed a centralized server management system with .NET (C#) and Vue.js for admin-level control over IIS application pools and SQL Server connections, deployed and used daily across 8+ servers

Leveraged .NET, Vue.js, and GraphQL to build ‘Coffee Connector,’ a bank-wide enterprise platform for initiating professional connections, developing a vector-based matching algorithm to connect users based on shared interests

Engineered an internal data ingestion tool using Angular, ASP.NET, and Apache Kafka, enabling non-technical project managers to update SQL Server data through Excel uploads and improving data intake efficiency by ~40%

Integrated a newly released Microsoft Fabric SDK within a .NET API, implementing OAuth 2.0 (Microsoft Entra ID) authentication to execute SQL queries and extract data from an Azure data lakehouse

Employed React and Spring Boot to build a full-stack software tool for organizations to identify and report cyber attacks, significantly improving application speed and enhancing scalability to handle a ∼ 50% increase in users

Built a REST API for JWT-based user authentication and secure data retrieval, implementing pagination, in-memory caching, and asynchronous request handling to reduce average response time by ~30%

Collaborated with researchers and physicians using Flutter to build and launch ‘SwitchWell,’ an evidence-based digital health platform enabling early intervention and real-time preventive mental health care for youth

Developed a progressive web application (PWA) with Flutter and Node.js for ethical surveillance and continuous monitoring of transmissible diseases across 30+ Indigenous communities, integrating a cloud architecture with AWS and Firebase

Led backend development for an AI-powered scheduling platform with Express.js and MySQL, designing secure RESTful endpoints and database schemas to support ~900 users in an AWS EC2 environment

Integrated the OpenAI API in a document-processing pipeline to analyze and infer scheduling details from unstructured text inputs, leveraging the Tesseract OCR engine to deliver a ~33% increase in text extraction accuracy

Successfully integrated OpenAI's API to analyze and interpret text extracted from PDF's using the Tesseract OCR engine

Built a production-grade application for hunger-relief nonprofit ‘Eayikes’ to automate volunteer coordination and optimize delivery routes, saving employees 25 hours a week in distributing ~60k meals annually across Southern California

Partnered with engineers and product managers to ideate and develop the app using Flutter, Figma, and Firebase, incorporating weekly stakeholder feedback to refine features based on evolving requirements

Helping first year students transition into university life by providing support and advice with social, academic, and other related topics, effectively acting as their 'first friend on campus'

Representing Western University as a positive role model and active member of the community, providing resources and guidance while using quick thinking to resolve conflicts

Led a team of directors in the development and application of financial strategies, delegating tasks to ensure optimal resource allocation in alignment with the clubs goals

Harnessed innovation and creativity in financial management to lower expenses by 30% and grow contingency funds

Conducted financial reviews, maintained a ledger of transactions, and prepared reports to highlight key metrics

Worked alongside peers to design, build, and deploy an AI-powered revenue prediction model, presented at the Canadian Undergraduate Conference on AI

Using Pandas, NumPy, and TensorFlow to construct a machine learning model that analyses industry trends and company metrics predicting future revenue for the next 10 years