Haixi Zhang

Hi, I’m Haixi Zhang, an ML / Computer Vision / Robotics Engineer based in San Jose, CA. I hold an M.Eng. in Electrical & Computer Engineering from Cornell University and a B.S. in Electrical & Computer Engineering from the University of Rochester.

I specialize in production perception systems that combine multimodal sensor data, 3D geometry, deep learning, and accelerated onboard inference. At Tensor Auto, I serve as the sole technical owner of three company-level ML/CV systems: I translate high-level product direction into concrete requirements and independently carry the core technical work from data and model development through validation and integration. Two systems have been delivered to onboard production; the third remains under active development.

FEATURED INDUSTRY WORK Production Perception Systems—Built from Data to Deployment Ownership from initial requirements and data contracts through system design, scalable distributed training, production validation, TensorRT optimization, and onboard C++ deployment. 3 systems owned end to end 2 production deployments 500+ GB multimodal sensor data 10° → <1° calibration recovery LCCNet · Deployed LiLiNet · Deployed In-Cabin Perception · Active Development Explore selected work →

Technical Focus

Multimodal Perception & Geometry

Building learning systems around physical sensor relationships, including camera–LiDAR calibration, cross-LiDAR alignment, occupant perception, and SE(3) / SO(3) geometry.

Production ML Engineering

Engineering world-size-configurable PyTorch DDP / NCCL training runtimes, then carrying models through ONNX / TensorRT optimization, performance profiling, and production C++ integration.

Data & Evaluation Systems

Developing fleet-scale sensor pipelines, automatic labeling, session-isolated evaluation, hard-case analysis, and regression testing for defensible deployment decisions.

I enjoy working across the full perception lifecycle—from data and modeling to runtime integration and benchmarking—and collaborating with cross-functional teams to improve end-to-end system quality.

Outside engineering, I’m fascinated by world history from the Renaissance through the Second Industrial Revolution, and I remain an enthusiastic fan of Yes, Prime Minister.

Interested in production perception, autonomous systems, or applied computer vision? I’d love to connect.