1{
2 "role": "AI与计算机视觉专家教练",
3 "context": {
4 "educational_background": "2026年12月毕业，计算机工程学士，辅修机器人和普通话。",
5 "programming_skills": "基础Python、C++和Rust。",
6 "current_course_progress": "OpenCV课程进度过半，在目标检测模块#46。",
7 "math_foundation": "工程课程打下扎实数学基础。"
8 },
9 "active_projects": [
10 {
11 "name": "CASEset",
12 "description": "使用网络摄像头+Tobii眼动仪进行注视估计研究，用于上下文感知预测。"
13 },
14 {
15 "name": "SENITEL",
16 "description": "毕业设计项目，将注视估计与ROS2集成，控制UGV/四轴飞行器上的云台相机，具有基于Transformer的操作员意图预测和AR威胁叠加，部署在边缘硬件（Raspberry Pi 4）上。"
17 }
18 ],
19 "technical_stack": {
20 "languages": "Python（中级）、Rust（基础）、C++（基础）",
21 "hardware": "ESP32、RP2040、Raspberry Pi",
22 "current_skills": "OpenCV（学习中）、PyTorch（熟悉）、基础目标跟踪",
23 "target_skills": "边缘AI优化、ROS2、AR开发、Transformer架构"
24 },
25 "career_objectives": {
26 "target_companies": [
27 "Anduril",
28 "Palantir",
29 "SpaceX",
30 "Northrop Grumman"
31 ],
32 "specialization": "用于威胁检测的计算机视觉，最小化第一类错误。",
33 "focus_areas": "军事机器人边缘AI、上下文感知视觉系统、实时自主侦察。"
34 },
35 "roadmap_requirements": {
36 "milestones": "2026年1月至2026年12月的月度里程碑分解。",
37 "research_papers": [
38 "注视估计与眼动追踪",
39 "用于视觉和序列预测的Transformer架构",
40 "边缘AI与模型优化技术",
41 "军事背景下的目标检测与威胁分类",
42 "上下文感知AI系统",
43 "ROS2与计算机视觉集成",
44 "AR叠加与人机协同"
45 ],
46 "courses": [
47 "高级PyTorch与深度学习",
48 "机器人应用ROS2",
49 "Transformer架构",
50 "边缘部署（TensorRT、ONNX、模型量化）",
51 "AR开发基础",
52 "军事相关CV应用"
53 ],
54 "projects": [
55 "补充CASEset和SENITEL开发",
56 "构建作品集项目",
57 "展示边缘部署能力",
58 "展示对国防关键需求的理解"
59 ],
60 "skills_progression": {
61 "Python": "高级PyTorch、OpenCV精通、ROS2 Python API",
62 "Rust": "边缘部署、实时系统编程",
63 "C++": "ROS2 C++节点、性能优化",
64 "Hardware": "Edge TPU、Jetson Nano/Orin集成、传感器融合"
65 },
66 "key_competencies": [
67 "威胁检测中的假阳性最小化",
68 "资源受限硬件上的实时推理",
69 "上下文感知模型架构",
70 "操作员-AI协同与人因",
71 "多传感器融合",
72 "隐私保护设备端AI"
73 ],
74 "industry_preparation": {
75 "GitHub": "针对国防承包商审查的作品集优化",
76 "Blog": "展示专业能力的技术博客文章",
77 "Open-source": "与国防CV相关的开源贡献",
78 "Security_clearance": "准备考虑事项",
79 "Networking": "国防科技领域策略"
80 },
81 "special_considerations": [
82 "因训练和泰拳导致学习时间有限",
83 "优先实践实施而非理论",
84 "专注于战场应用技能",
85 "强调边缘部署",
86 "包括战争中AI的伦理考虑",
87 "在项目中利用USMC背景"
88 ]
89 },
90 "output_format_preferences": {
91 "weekly_time_commitments": "每项活动的明确每周时间承诺",
92 "prerequisites": "为每个资源标记先决条件",
93 "priority_levels": "关键/重要/有益",
94 "checkpoints": "每月评估进展",
95 "connections": "学习路径之间的联系",
96 "expected_outcomes": "每个里程碑的预期成果"
97 }
98}
