Bosheng (Daniel) Zhang
AI/ML Engineer
Building intelligent automation systems that solve real-world business challenges. Specialized in computer vision, LLM-powered analytics, and domain-specific AI chatbots.
About Me
Hi, I'm Bosheng Zhang, but you can also call me Daniel. I'm an AI/ML Engineer based in Brisbane, Australia, with 4+ years of experience designing intelligent automation systems that solve real-world business challenges.
I specialize in building end-to-end AI solutions — from computer vision pipelines to LLM-powered analytics. Previously at Vision HQ, I built production AI systems for city-wide infrastructure monitoring and IoT telemetry analysis. Currently, I'm independently researching and developing domain-specific business chatbots, exploring the latest advances in LLM agents, RAG, and multi-modal AI.
I'm passionate about bridging the gap between research and production, writing high-performance Python code, and turning complex technical requirements into scalable, reliable systems.
Experience
AI Engineer & Researcher
Independent
- Researching and developing domain-specific business chatbots powered by LLMs, focusing on practical enterprise applications
- Tracking and experimenting with cutting-edge AI developments including agent frameworks, RAG architectures, and multi-modal models
- Building open-source tools and prototypes to explore emerging AI patterns and best practices
AI/ML Engineer
Vision HQ
- Built an AI-powered road monitoring system using waste truck-mounted cameras, enabling automated city-wide infrastructure defect detection across all serviced roads
- Developed a computer vision-based street waste detection system for urban cleanliness assessment, providing councils with actionable geospatial data for cleanup prioritization
- Built an LLM-powered IoT monitoring platform on GCP using function calling to orchestrate Elasticsearch data retrieval, anomaly detection, and automated daily report generation
Bachelor of Engineering (Honours) / IT
University of Queensland
- Specialized in machine learning, computer vision, and software engineering
- Completed research projects in medical image segmentation and reinforcement learning
Skills
AI / Machine Learning
Cloud & DevOps
Languages & Frameworks
Data & Tools
Featured Projects
Production AI/ML systems and selected research projects. Click any card to read the full case study.
AI-Powered Road Infrastructure Monitoring System
Computer vision system mounted on waste trucks for automated city-wide road defect detection, enabling proactive infrastructure maintenance.
AI-Powered Street Waste Detection & Cleanliness Index
Computer vision system that detects street-level waste and generates a city-wide Cleanliness Index, giving councils a data-driven view of urban cleanliness.
LLM-Powered IoT Device Monitoring Platform
Intelligent monitoring platform using LLM function calling to orchestrate data retrieval, analysis, and automated report generation for IoT device fleets.
Academic & Research Projects
Skin Lesion Segmentation with Improved U-Net
Deep learning model for melanoma detection achieving 0.8+ Dice score on the ISIC dataset, using an improved U-Net architecture.
GreenMiles - Sustainable Transportation App
React Native mobile app incentivizing public transportation through gamification, carbon footprint tracking, and social connectivity.
LaserTank AI Solver
AI solvers for the LaserTank puzzle game using A* search, MDP planning, and reinforcement learning algorithms.
CANADARM Motion Planning
Probabilistic Roadmap-based motion planning for the ISS Canadarm2 robotic arm, navigating obstacles in constrained 2D workspace.
RUSHB Network Protocol Suite
Custom network protocol implementation with server, adapter, and switch components for reliable data transmission across networks.
Blog
Thoughts on AI, engineering, and building things.
Let's Connect
I'm always open to discussing AI/ML projects, collaboration opportunities, or just connecting with fellow engineers. Feel free to reach out!
ddaniel.zhang0413@gmail.com