Resume

Professional experience and background

Languages: C/C++, Python, Java, Swift, JavaScript, HTML/CSS, Bash

Databases: SQL, NoSQL, MySQL, PostgreSQL, SQLite, MongoDB, Redis

Tools & Platforms: Git, SVN, Github, Postman, Linux, QNX, Yocto, GDB, Docker, Kubernetes, AWS EC2

Frameworks: Django, Flask, FastAPI, Bootstrap, React.js, MQTT, iOS (UIKit/SwiftUI)

Sep 2023 – Dec 2025 (Expected Graduation, Available: January 2026)

M.Eng. in Systems and Technology (Software), GPA 4.0/4.0, Academic Excellence ScholarshipHamilton, ON, Canada

Sep 2017 – Jun 2021

B.Sc. in Computer Science, Major GPA 3.42/4.0Beijing, China

Sep 2024 – Aug 2025

Software Engineer Intern — C++, Linux/QNX, Performance & QualityOttawa, ON, Canada

Optimized a polling-based timer manager in the Connectivity Manager into a condition-variable–driven scheduler, reducing CPU wakeups and improving idle behavior on Linux/QNX multi-ECU systems
Simplified VLAN and interface manager by streamlining containers and finite-state machines and replacing hard-coded flags with enums, cutting code size by 10% and reducing network interface setup time by 25%, improving maintainability
Investigated cross-ECU connectivity issues by correlating logs from central gateway, telematics, and infotainment ECUs, tracing message flows to separate application defects from network/configuration issues and document root causes
Increased unit test coverage for routing and fault-recovery logic from 83% to 90% using Google Test, and ran builds with AddressSanitizer and static analysis to catch iterator invalidation and uninitialized access in development
Reduced flash and regression test time by 40% by building a local multi-ECU bench, enabling on-bench Yocto/BitBake builds and Docker-based workflows, and doing local flashing and sanity tests before handing builds to the test team
Co-authored high-level design and data-flow documents and created UML class diagrams for the message-driven, multi-ECU connectivity architecture, improving codebase understanding, onboarding speed, and cross-team debugging efficiency

Jan 2024 – Aug 2024

Software Development Intern (Part-time) — Python, JavaScript/React, LLM, RAG, Fine-tuningToronto, ON, Canada

Developed a LLM-powered assistant for a physics and chemistry simulation platform (Next.js/React.js), enabling users to query experiment states, modify parameters, and create new objects through natural-language or voice commands
Designed an intent-to-action pipeline using structured XML prompts and a custom parser to route LLM outputs into UI behaviors and simulator APIs; improved experiment setup clarity and reduced manual steps for users
Implemented a RAG-based knowledge assistant for course- and platform-specific content, covering document ingestion, chunking, embedding, vector indexing, and retrieval-to-generation orchestration to reduce hallucinations in domain Q&A
Applied LoRA/PEFT to align an open-source LLM with lab terminology and instructional tone, enhancing response consistency
Organized experiment configuration files using Python and centralized them on AWS S3 to enable consistent parameter loading

Aug 2021 – Jul 2023

Software Engineer — Python/Django, iOS (Swift), DevOpsChongqing, China

Maintained and developed Python/Django/Flask microservices, collaborated with DevOps team to containerize services with Docker, implemented CI/CD automation using Jenkins, and standardized release/rollback procedures
Built an iOS autonomous parking app using Swift/Objective-C, UIKit and Alamofire, integrated MQTT for low-latency command/position updates and WebKit for rendering live 3D vehicle model for remote control
Contributed to app refactoring and componentization reducing codebase by 10%, delivered a SDK for third-party integration, and introduced TestFlight/crash analytics to reduce defect turnaround from 2 days to 1 hour
Led the end-to-end iOS app release pipeline for 2 million users, including build configuration, signing, packaging, internal distribution, and TestFlight releases; authored comprehensive technical documentation covering system architecture, data flow, and operational guides to support long-term team maintenance and onboarding

Aug 2020 – Jul 2021

Application Research Assistant — Python, React, Redis, Docker, LinuxBeijing, China

Built a full-stack literature management and discussion forum platform for 20+ researchers using Python (Flask/FastAPI), React, and MongoDB/MySQL, supporting search, tagging, versioning, and user authentication
Enhanced system performance and reliability through Redis caching and Docker containerization, enabling low-latency access and stable 7×24 operation, and documented architecture/data flows for future maintainers
Co-developed EEG sleep-staging models (GCN/CNN/Attention + domain generalization), achieving 3% improvement over state-of-the-art models on two public datasets; results published in IJCAI 2020 (conference) and IEEE TNSRE 2021 (journal)

Last Updated on 12/10/2025