Software Engineering
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I am a Master of Applied Science student in Electrical and Computer Engineering at the University of Waterloo. My experience includes research on deep learning and software engineering internships at eBay and Huawei Technologies Canada.
Research Assistant May 2025 – April 2026
◦ Optimized deep learning models for audio reconstruction in reverberant environments, reducing the loss to 10−9
◦ Proposed a dual-path temporal-frequency model combining convolutional and attention modules for multi-point sound field control, achieving up to 10 dB noise reduction while maintaining spatial selectivity.
Software Development Engineer Intern January 2024 – April 2024
◦ Developed a full-stack e-commerce web application, serving over a million users. Implemented 10+ functionalities allow sellers to manage multiple stores’ information, product listings, and order processing.
◦ Implemented the back-end architecture in Spring Boot with RESTful APIs utilize HTTP methods. Created reusable UI components using React.js. Achieved 95% test coverage using JUnit for APIs tests.
◦ Integrated PostgreSQL for data storage and optimized database performance through parallel processing and indexing techniques, achieving a 40% improvement in query response time.
Software Development Engineer Intern May 2023 – December 2023
◦ Designed and implemented a network automation toolchain including Yang model compiler into structured configuration data, integrating gRPC-based microservices, Datastore management, and protocol support (NETCONF, RESTCONF) to automate device configuration generation and validation across network systems.
◦ Designed service using Protocol Buffers to serialize and deserialize data structures defined in Yang.
◦ Refactored data source loading procedures, reducing software testing runtime by 70%. Achieved 100% unit test coverage with Google Test and JUnit for both the C++ server and Java client.
Master of Applied Science; Electrical and Computer Engineering
Bachelor of Science; Honour Specialization in Computer Science (cGPA: 4.0)
