Resume

Professional experience and background

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Education

McMaster University

Sep 2023 – Dec 2025 (Expected)
M.Eng. in Systems and Technology, GPA 4.0/4.0, 4-12 months Co-opHamilton, ON, Canada
  • Core Courses: Machine Learning (A+), Deep Learning (A+), Cloud Computing (AWS, A+), Natural Language Process (A+)

Beijing Jiaotong University

Sep 2017 – Jun 2021
B.Eng. in Computer Science and Technology, Major GPA 3.42/4.0Beijing, China

Work Experience

Ford Motor Company

Sep 2024 – Aug 2025
Networking Software Development Intern — C/C++, Linux/QNX, Embedded NetworkingOttawa, ON, Canada
  • Resolved 100+ verified defects (Jira) across Connectivity Manager and related ECUs; reproduced, triaged, and patched C++ concurrency issues (thread pools, pub/sub) to stabilize soak tests under production-like loads and reduce latency.
  • Delivered 10+ stories end-to-end within sprints, collaborating with senior engineers on design reviews and rollouts.
  • Refactored timing logic to an event-driven approach, reducing CPU wake-ups and improving runtime efficiency.
  • Performed gdb core-dump analysis to trace crashes to root cause, isolating code paths and unblocking fixes.
  • Set up the Linux/QNX dev environment and wrote BitBake recipes for test agents; fixed C++ build issues, added VS Code launch/debug configs, and maintained recipes—cutting on-bench validation time by ~40%.
  • Automated quality checks (CodeChecker, coverage, cppcheck); added unit-tests/PlantUML, raising coverage 85→90%.

LABonWEB

Jan 2024 – August 2024
Software Development Intern; Python, LLMs, Javascript, HTML/CSS, React, Next.js, TypeScriptToronto, ON, Canada
  • Spearheaded the development of an AI assistant for a web-based lab simulation platform using Large Language Models (such as Llama3), JavaScript, React, and Next.js, which reduced manual input errors by 25%.
  • Designed and implemented comprehensive unit and integration tests, reducing bug rates by 20% over previous iterations.

Changan Automobile

Aug 2021 – Jul 2023
Software Engineer; Swift, Linux, Objective-C, UIKit, CocoaPod, MQTT, Python, Django, FlaskChongqing, China
  • Managed and improved the Python microservice architecture for the mobile app Question-Answer system.
  • Collaborated with the DevOps team to strategize and execute service migration and redeployment to upgraded servers.
  • Integrated TestFlight for beta/crash analytics; cut bug resolution from 2 days to 1 hour.
  • Implemented an innovative iOS interface for a car self-parking system using Swift, UIKit, Alamofire, live video streaming and a web-based dynamic 3D car model and map, enabling real-time car parking control and monitoring.
  • Co-led iOS refactor/componentization; cut code 10%, sped 3rd-party integration, improved reuse/maintainability.

Institute of Network Science and Intelligent Systems, Beijing Jiaotong University

Sep 2019 – Sep 2020
Research Assistant; Python, Pytorch, GCN, CNN, KGCN, LSTM, Java, Redis, MySQLBeijing, China
  • Collaborated with a research team to develop a state-of-the-art sleep stage classification model using GCN, CNN, Attention Mechanism, and Domain generalization for EEG data to extract dynamic graph features.
  • Achieved a nearly 3% improvement in two popular public datasets compared to previous methods.
  • Developed a Literature Management and Forum System for academic research, enabling users to manage and share academic papers and discuss research topics for a team of 20+ researchers, reducing paper management time by 50%.
  • Published two papers on Int'l Joint Conf. on AI 2020 (IJCAI '20) and IEEE Trans. Neural Syst. Rehabil. Eng. 2021.

Projects

AI-Powered Flashcard Learning System (iOS • RAG • IoT)

Nov 2024 – Apr 2025
Swift, SwiftUI, Python (FastAPI), PyTorch/Transformers, LlamaIndex, LangChain, Firebase, AWS, Raspberry Pi, MQTT
  • Shipped an iOS app that auto-generates flashcards from notes/PDFs using Retrieval-Augmented Generation (chunking, embeddings retrieval, LLM reformatting) for spaced-repetition study and targeted mastery progress tracking.
  • Built backend in Python on AWS (FastAPI, PyTorch/Transformers) and integrated Firebase for auth and real-time sync.
  • Added IoT progress display: Raspberry Pi pulls metrics from cloud via MQTT to show cards completed vs. remaining.

AI Teaching Assistant with LLMs and Retrieval Augmented Generation (RAG)

Jan 2024 – Apr 2024
Python, Pytorch, Transformers, LlamaIndex, LangChain, Hugging Face, LLM, RAG, NLP, BERT, GPT-3
  • Developed an AI Teaching Assistant with Large Language Models (LLMs, such as GPT-3, Llama3) and Retrieval-Augmented Generation, improving response accuracy by 25% and bypassing the need for QA pairs.
  • Enhanced user interaction with the AI system, achieving a 50% increase in student engagement.

Last Updated on 9/17/2025