Bo Shang

Robotics software engineer & ML researcher working at the intersection of multi-sensor perception, real-time data pipelines, and deep learning. I build and deploy LiDAR + camera systems for the real world — from city-scale highway monitoring to bridge inspection robots — with a focus on the unglamorous but critical layer underneath every perception model: temporal and spatial sensor synchronization, calibration, and high-throughput data capture.

I am a Postdoctoral Scholar at the AI & Mobility Research Lab, CUNY City College of New York. My production work spans ROS-based robotics stacks, NVIDIA Jetson edge inference, CNN-based 3D object detection, and AWS-backed inspection workflows deployed with New York City agencies.

Hire me as…

Same engineer, two role-targeted resumes:

• 🤖 Robotics Software Engineer — LiDAR + multi-camera pipelines, sensor synchronization & calibration, ROS, real-time data systems, DepthAI, MCAP/Protobuf.
• 🧠 Machine Learning Engineer — 3D/2D CNN object detection, multimodal fusion, model training and cloud deployment (AWS), computer vision for safety-critical infrastructure.
• 📚 Full Academic CV — complete record of publications, patents, teaching, and grants.

Start at the Resumes hub to pick the right view.

What I work on

• Multi-sensor pipelines for perception — fixed highway LiDAR + camera capture, temporal/spatial alignment, calibration workflows, multi-frame reconstruction, end-to-end ingestion to training-ready datasets.
• Robotics deployments in the wild — drone and climbing-robot platforms for bridge inspection, PID/visual-servoing controllers, autonomous clamping, ROS + Jetson + iOS control surfaces.
• Deep learning on point clouds and imagery — CNN-based 3D detection, vulnerable-road-user sensing, contrastive learning for defect mapping, models deployed on AWS for scalable inspection.
• AI-first developer tooling — using LLM agents (including this site, built with Claude Code) to keep documentation, resumes, and project pages aligned with what I’m actually shipping.

Selected publications

Recent highlights in roadside-LiDAR sensing, vulnerable-road-user safety, and robotic infrastructure inspection — kept in sync with Google Scholar.