JunhaoYan
Backend & AI Engineer with experience in computer vision, industrial software, AI agents, and hardware-software integration.
Education
University of Ottawa
2018.09 — 2022.11Master of Engineering, Electrical and Computer Engineering
University of Shanghai for Science and Technology
2014.09 — 2018.09Bachelor of Engineering, Optical Information Science and Engineering
Experience
Independent / EntrepreneurshipFounder & AI Product Developer
2024.10 — Present- Explored B2B AI opportunities in manufacturing after leaving XKL, speaking with factory owners to identify practical AI adoption points and workflow bottlenecks.
- Built AICad, an AI-agent product for CNC manufacturing workflows including CAD drawing translation, drawing review, quotation assistance, and version comparison.
- Owned backend architecture and implementation end to end while coordinating outsourced frontend work, covering requirements, system design, coding, testing, and demo delivery.
- Designed a modular backend using Python, FastAPI, LangGraph, an API layer, business-processing layer, agent library, and persistence layer.
Shenzhen Xinkailai Technology (XKL)Software Development Engineer
2023.03 — 2024.10- Worked primarily on YMS, an AFM upper-computer software project targeting domestic replacement of atomic force microscope equipment.
- Led or independently completed requirement walkthroughs, design, implementation, integration, simulator testing, and clean-room real-machine validation for new features and version quality.
- Owned algorithm-module work, developing and integrating multiple data-analysis algorithms and validating them on both simulators and physical equipment.
- Implemented hardware adaptation and driver-layer integration in C++ for line-scan and area-scan workflows, improving device interaction stability and performance.
- Developed upper-computer service features with Java and Spring Boot, including API design, business logic, and system integration.
- Delivered dozens of requirements across 10+ version iterations with no rejected releases, supporting product milestones and customer acceptance.
National Research CanadaComputer Vision Research Intern
2020.10 — 2021.10- Led development of a deep-learning based inspection workflow for aircraft component testing, reducing manual inspection effort through automated image analysis.
- Collected RGB camera images, labeled and filtered data with LabelMe, and built a PyQt5 desktop UI for detection results, alerts, live camera view, and before/after image comparison.
- Trained and deployed PyTorch and scikit-learn models including DeepLabV3 with a ResNet18 backbone and a random-forest digit detector.
- Combined contrastive-learning pretraining, CNN refinement, Adam optimization, and exponential learning-rate scheduling to improve model performance.
Lavia SolutionComputer Vision Intern
2020.06 — 2020.09- Helped build an automatic acne annotation system in the R&D department, focusing on model training for acne recognition.
- Annotated image data with LabelMe and trained a Mask R-CNN based detector using Detectron, applying NMS to produce final candidate regions.
- Reduced repetitive manual work for skin analysts by automating part of the image-labeling and analysis workflow.
Projects
Domain Adaptation on Semantic Segmentation with Separate Affine Transformation in Batch NormalizationResearch Publication
2019.09 — 2021.09First Author
- Proposed Separate Affine Transformation (SEAT), replacing shared BatchNorm affine parameters with domain-specific affine parameters for source and target domains.
- Used DeepLabV3 with a ResNet101 backbone and adversarial training for unsupervised domain adaptation in semantic segmentation.
- Evaluated on GTA5 and SYNTHIA as source domains and Cityscapes as the target domain, improving performance by 4.0 mIoU in reported experiments.
- Published as arXiv:2110.07376 with co-author Woonsok Lee.
DeepLabV3 Defect Detection SystemComputer Vision Project
2020.10 — 2021.10- Built an automated defect/corrosion inspection system for high-temperature aircraft components.
- Implemented a two-stage detection pipeline: DeepLabV3 semantic segmentation for coarse corrosion-region detection, followed by multi-layer convolutional edge detection for boundary refinement.
- Reached precision and recall of at least 95% according to project records.
- Coordinated requirements and data collection with the client, decomposed tasks, assigned work to lab members, and delivered the project on schedule.
Embedded Aluminum Measurement SystemEmbedded Systems Internship
2016.06 — 2016.09- Developed an embedded measurement system for aluminum products at Huizhou Lichang Aluminum Products Co., Ltd.
- Used an STM32 development board to control motor-driven conveyor movement and infrared sensors.
- Calculated product length from conveyor speed and sensor timing, reducing manual measurement effort and improving measurement efficiency.
Unity Target-Seeking ProjectileCourse Project
2020.01 — 2020.04- Built a Unity simulation environment with vegetation, characters, buildings, and turret behavior.
- Implemented movement and action logic in C# and trained a target-seeking projectile with Q-learning.
AI-agent product for CNC manufacturing workflows, covering CAD drawing translation, drawing review, quotation support, and version comparison. Sole backend owner; delivered an end-to-end demo with Python, FastAPI, and LangGraph.
Industrial software project at XKL for an AFM product. Delivered algorithms, C++ driver-layer integration, Java/Spring Boot service features, simulator testing, and clean-room real-machine validation across 10+ releases.
First-author arXiv research proposing Separate Affine Transformation in Batch Normalization for unsupervised domain adaptation in semantic segmentation.
Skills
Backend & Systems:
Python, FastAPI, Java, Spring Boot, C++, REST APIs, Modular Architecture, Hardware Integration
AI & Computer Vision:
PyTorch, OpenCV, scikit-learn, DeepLabV3, ResNet, Mask R-CNN, YOLO, Detectron, Semantic Segmentation, Domain Adaptation
AI Agents:
LangGraph, Workflow Orchestration, Agentic Backend Design, Manufacturing AI, CAD Workflow Automation
Tools & Communication:
LabelMe, PyQt5, Unity, Git, English working communication, IELTS 6.5