卢英豪，目前就读于宁波大学信息科学与工程学院，攻读计算机技术硕士学位，在王翀老师的指导下开展计算机视觉研究。我的求职方向是 AI 应用开发与视觉算法开发。

我熟悉 PyTorch 深度学习框架，掌握 CLIP、ViT、DETR、ResNet 等视觉模型的实现与应用，能够完成数据处理、模型训练、效果评估、结果可视化和工具开发的完整流程。项目上曾负责盖板玻璃缺陷检测，完成算法路线评估、块级缺陷分类定位、PyQt 标注工具和检测结果可视化；也在乐歌机器人实验室参与 AGV 多镜头货架图像拼接与一维码去模糊模块，面向仓储场景提升成像质量、定位能力和识别鲁棒性。

我可以承担视觉算法验证、检测识别方案开发、数据标注与结果可视化工具实现，也能基于 Qwen3-14B等模型搭建大模型应用原型，完成模型调用、推理服务、业务流程接入和可演示 Demo 开发，帮助团队更快验证 AI 功能在具体场景中的可用性。

Hello, I am Yinghao Lu, an Master. student in Computer Technology at the Faculty of Electrical Engineering and Computer Science, Ningbo University, advised by Prof. Chong Wang. I am seeking AI application development and vision algorithm roles.

I work with PyTorch and vision models including CLIP, ViT, DETR, and ResNet, and can handle the full workflow from data processing, model training, evaluation, visualization, and tool development. I led a cover-glass defect detection project covering method selection, patch-level classification and localization, PyQt annotation tools, and result visualization. I also interned at Loctek Robotics Lab, building AGV multi-camera shelf stitching and barcode deblurring modules for warehouse imaging, localization, and recognition robustness.

I can contribute to vision algorithm validation, detection and recognition solutions, data annotation and result visualization tools, and LLM application prototypes based on models such as Qwen3-14B-AWQ. I can help with model invocation, inference services, workflow integration, and deliverable demos so teams can quickly validate AI features in concrete scenarios.