Emma Fu | Software Developer

Hi, I'm Emma Fu.

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Self-driven, quick starter, passionate programmer with a curious mind who enjoys solving a complex and challenging real-world problems.

About

I am a 4th Year Electrical & Computer Engineering Student at the University of Toronto. I enjoy problem-solving and coding. Always strive to bring 100% to the work I do. I have worked on technologies like Python, Machine Learning, C++, C, PostgreSQL, Flask, HTML5, CSS during my degree. I have 16 months of professional work experience which helped me strengthen my experience in Python programming, Machine Learning, software infrastructure and Agile project management. I am passionate about developing complex applications that solve real-world problems impacting millions of users.

Languages: Python, C, C++, MATLAB
Databases: PostgreSQL, MongoDB
Libraries: NumPy, Pandas, OpenCV
Frameworks: TensorFlow, PyTorch, Flask, Keras
Tools & Technologies: Git, JIRA, Confluence, Docker, Figma

Looking for an opportunity to work in a challenging position combining my skills in Software Engineering, which provides professional development, interesting experiences and personal growth.

Experience

University of Toronto: Enterprise Applications & Solutions Integration

Project Coordinator

Coordinated project activities and scoped out clear project roadmaps and initiatives with cross-functional teams
Applied Agile management principles for increased productivity, team learning and risk mitigation
Adapted project plans and priorities based on changing business needs and client feedback to ensure advancement
Tools: Agile, JIRA, Confluence, ServiceNow, Sharepoint

May 2023 - Present | Ontario, Canada

Advanced Micro Devices

Software Engineer

Expanded software infrastructure in Python to execute automated script testing for 70+ power firmware features
Integrated 15+ CPU/GPU workloads into software infrastructure to conduct power management feature testing and long-duration stress test during silicon bringup
Developed a data analysis & visualization program via pandas, NumPy & Matplotlib to assess chip performance
Initiated machine learning project to predict chip performance scores based on test parameters and system setup
Collaborated closely with hardware, firmware and software teams to root-cause issues for a complex chip design
Tools: Python, Scikit-learn, Docker, MongoDB

May 2022 - April 2023 | Ontario, Canada

University of Toronto: Engineering Student Recruitment & Retention Office

Engineering Student Ambassador

Organized and facilitated recruitment events with 300+ prospective students globally
Conducted research, and gathered and analyzed data to identify and present solutions for gaps in student resource
Facilitated support programs for prospective students, including advising appointments and material preparation
Tools: Sharepoint, Microsoft Office

Sep 2021 - April 2022 | Ontario, Canada

Projects

Face-2-Face

A Machine Learning application that performs multi-class classification on human emotions using images and overlays corresponding emotion's emoji onto live video-feed

Accomplishments

Tools: Python, PyTorch, OpenCV
Developed machine learning models for image multi-class classification on human emotions with 70% validation accuracy using PyTorch and transfer learning with AlexNet and ResNet18
Implemented real-time video capture and overlay predicted emotion's emoji on live camera feed using OpenCV
Increased accuracy by 15% by applying data balancing, normalization, and augmentation on the dataset

Mappy-Boi

An interactive Geographical Information System with features such as: path finding, point of interest filters, map display and more.

Accomplishments

Tools: C++, Git, Glade Interface Designer, GTK Toolkit, OpenStreetMap Database
Developed a Geographic Information System program with map display, pathfinding, location search and filtering
Implemented greedy and Dijkstra's algorithm to find the optimal path between multiple intersections
Created GUI using Glade Interface Designer and GTK Toolkit to allow user interaction with application features