Kaison Lau Mingxuan Liu

Vehicle Engineering (Major) + Accounting (Minor) · Dual Bachelor (B.Eng. + B.Mgmt.)

CET-4 English proficiency; capable of professional English communication and international reception.

Delivery Service Dept. — After-sales Operations · Operations Data Management / AI Productization

Key Responsibilities

• Responsible for regional after-sales business data statistics and monitoring, covering key metrics such as workshop visits, revenue, gross margin, first/second maintenance / renewal / new insurance, accessories / parts profit, NSS, etc.
• Built the "One-Store-One-File" digital inspection system, designing inspection indicators and evaluation logic, integrating DMS core metrics to form store scoring and issue diagnosis framework.
• Led AI-driven complaint governance: consolidated weekly VOC / complaint data, using the What-Why-How three-layer analysis + 5M1E fishbone diagram to prioritize issues, covering sales, delivery, after-sales, and finance across all business domains.
• Led the SkyEye / OEM public-domain public opinion monitoring system, independently designed the accident vehicle repair overdue alert system (DMS data collection + rule engine + Feishu notification), and advanced the WeCom customer retention platform from 0 to 1 requirement design.
• Led a service capability survey of 120 authorized stores, driving store position analysis and staffing, and supporting regional travel and on-site inspection.

Key Achievements

1. SkyEye / SkyAI · Dongfeng Eye was presented as the Dongfeng Group AI Competition entry, completing a 7-minute 10-slide PPT presentation on 2026.07.07, and was awarded Dongfeng Group "Young Role Model" and "1st Place in Youth Skills Competition".
2. SkyEye system built a 27-table data layer, covering public content collection, AI Agent post-level sentiment / risk judgment, brand health dashboard, and the full pipeline.
3. The accident vehicle repair overdue alert system is in production, pushing store / regional alerts daily at 10:00 and national KPI reports at 17:00 based on 7/10/14-day tiered rules.
4. 120 authorized store capability survey covered 29 provinces, identifying a tire repair self-service rate of only 25.8% (the biggest gap), 38 stores (31.7%) with 2+ capability gaps, and 15 stores with less than 15 maintenance items covered, and output short / medium / long-term improvement plans.
5. Complaint governance solution defined P0 (auto-structuring + intelligent triage + major risk alert) / P1 (knowledge base + handling suggestion generation) / P2 (monthly root cause review) three-tier priorities, and completed project kickoff presentations to business leaders and data / IT / AI teams.
6. Mapped 158 independent DMS system pages, identified 114 data pages, establishing reusable access points for subsequent business analysis, complaint scraping, and accident vehicle monitoring.
7. Designated English receptionist for overseas VIP clients at the Experience Center, responsible for international reception at the 26th World Youth Congress and the 2026 HUST International Summer School.

After-sales Service Dept. — Dealer Management · Business Support / After-sales Data Analysis

Key Responsibilities

• Responsible for after-sales business data analysis for 600+ dealers nationwide, covering workshop visits, orders, revenue, profit, CSI, regional operations, and customer churn, supporting after-sales target setting and regional supervisor improvement.
• Independently developed data tools for dealer daily revenue tracking, customer churn heat map, and closed-store customer transfer analysis.
• Participated in recall lead tracking APP requirement design and WeCom customer retention project pre-launch.

Key Achievements

1. Daily revenue tracking tool deployed nationwide for 600+ dealers, upgrading regional operations data review from manual exports to a daily dashboard, improving supervisor efficiency.
2. Customer churn heat map and closed-store transfer analysis tools supported regional supervisors in quickly identifying churn risk areas and formulating customer retention strategies.
3. Recall lead tracking APP and WeCom customer retention pre-launch project won Dongfeng Honda 2025 "Value Creation" Bronze Award.

New Energy Factory Body Welding Project Team · Digital Project Lead

Key Responsibilities

• Responsible for the full lifecycle of IT / digital projects in body welding: procurement, supplier evaluation, requirement specification, planning, risk management, system acceptance, and on-site training.
• Led the WIMP (Welding Intelligent Management Platform) construction, covering production execution, VIN traceability, project management, process quality, and equipment monitoring.
• Responsible for AGV intelligent transport system implementation and commissioning.

Key Achievements

1. WIMP platform covered 5 major modules: production execution, VIN traceability, project management, process quality, and equipment monitoring, supporting digital management of the welding line.
2. Commissioned 30+ AGVs, achieving 500+ parts flexible daily transport capacity.
3. Independently completed the full delivery from supplier evaluation to on-site training, ensuring the new energy factory welding line was commissioned on schedule.

Product Design / Full-stack Implementation / Presenter

An intelligent public-domain public opinion monitoring system for automotive OEMs, transforming content from platforms like Douyin and Xiaohongshu into brand risk signals and handling suggestions, addressing the problem of OEMs being unable to discover negative sentiment, competitor volume, and real user feedback in a timely manner.

• Built a 27-table data layer; AI Agent completes post-level sentiment, risk, brand, and topic analysis, outputting a risk matrix and brand health dashboard.
• Presented as a "working product" at the Group AI Competition, winning Dongfeng Group "Young Role Model" and "1st Place in Youth Skills Competition".

Stack: TikHub API / PostgreSQL / Fastify / Vue3 / ECharts / DeepSeek Agent / Docker

Requirement Analysis / Rule Engine / Web Console

An abnormal work order monitoring tool for stores and regional supervisors nationwide, addressing the problem of long accident vehicle repair cycles, late anomaly detection, and regional follow-up relying on manual checks.

• Automatically logs into DMS to fetch repair data, identifies overdue risks using 7/10/14-day tiered rules, and pushes Feishu cards and Excel reports to the relevant personnel.
• Already in production, stably supporting daily 10:00 store/regional alerts and 17:00 national KPI report pushes, generating continuously traceable operational data.

Stack: Python / DMS Scraper / Rule Engine / Web Console / Feishu Bot

Field Mapping / Analysis Standard Design / Report Output

Transforms complaint details into AI summaries, risk tags, attribution analysis, and handling suggestions, covering sales, delivery, after-sales, and finance across all business domains, addressing the problem of scattered complaint data, slow manual summarization, and difficulty forming a closed-loop governance cycle.

• Used the What-Why-How three-layer analysis + 5M1E fishbone diagram to define P0/P1/P2 tiered priorities, forming a project kickoff presentation for business leaders and data/IT/AI teams.
• Supports continuous output of complaint governance, inspection review, and quarterly analysis reports; already consolidated Jan–May complaint/service lists by store and matched with inspection results.

Stack: DMS Scraper / Bailian AI Summary / Risk Tag System / Feishu Bitable