Kangjie Wu
University of Toronto
Scarborough,ON
Summary
Dynamic and adaptable professional with a solid foundation in C/Linux development. Skilled in algorithmic optimization, full-stack system engineering, multi-redundancy robotics, and applied AI.
2
Languages
Work History
Intern
4 Months- Owned full‑stack driver development and validation for a dual‑OS conferencing board (Linux on domestic SoC + x86 Windows), tackling multi‑channel 4K AV streaming across heterogeneous platforms.
- Designed a data pipeline over hardware shared memory and DMA, collaborating with the Linux capture driver lead while developing the Windows AVStream minidriver as the sink endpoint.
- Resolved cross‑OS physical memory address mapping and optimized DMA descriptor chains / interrupt handling, achieving stable, tear‑free multi‑stream delivery with sub‑millisecond latency.
- Successfully delivered the solution into mass production, directly enabling high‑performance domestic SoCs to unlock high‑bandwidth media processing despite the lack of native Windows driver support.
Education
Bachelor of Science - Computer Science
- Completed Coursework: CSCC73H3 Algorithm Design and Analysis, 2025
- Completed Coursework: CSCD84H3 Artificial Intelligence, 2025
- Completed Coursework: CSCC69H3 Operating Systems, 2025
- Completed Coursework: CSCC85H3 Fundamentals of Robotics and Automated Systems, 2025
Skills
C/Java/Python/Linux Development
Multi-Redundancy Robotics
LLM
Convolutional Networks
Diffusion Models
Bayesian Networks
PostgreSQL
Timeline
Intern
University of Toronto
05.2024 - 09.2024
University of Toronto
Bachelor of Science from Computer Science