Machine learning & AI for data with complex structure.
Dr. Daniel L. Lau is the Databeam Professor of Electrical & Computer Engineering at the University of Kentucky. His research develops machine learning and artificial intelligence for data with complex relational structure — centered on graph and hypergraph neural networks and geometric deep learning.
Learning on graphs, hypergraphs, and beyond
Much of the world's most important data — power grids, brain connectomes, molecules, sensor networks — is fundamentally relational. Dr. Lau builds machine learning models that learn directly on those structures, with applied work extending deep learning to 3D vision and computational imaging. See the research →
Graph & hypergraph neural networks
Tensor-based hypergraph neural networks (T-HyperGNNs, HyperNATE) and hypergraph U-Nets that capture higher-order relationships beyond pairwise edges.
Geometric deep learning & GSP
Deep models and signal processing on non-Euclidean domains — including graph learning for power-distribution networks and neural connectomes.
AI for 3D vision & imaging
Deep learning applied to structured-light 3D capture, computational and multispectral imaging, and the science behind the FM Halftone Screening plugin.
FM Halftone Screening for Photoshop
Where the imaging research lands in practice — a career's worth of halftoning, delivered as a Photoshop plugin.
Press-ready 1-bit separations, screened inside Photoshop
Two FM / stochastic screening engines — Platesetter and Inkjet — turn continuous-tone CMYK artwork into true 1-bit-per-channel separations, plus light-ink separations tuned for modern Epson photo printers. No separate RIP required.
From the lab to the field
Dr. Lau has co-founded companies that carried university research into industry.
FlashScan3D
A company specializing in non-contact fingerprint scanning using structured light — capturing, analyzing, and searching fingerprint evidence without touch.
Seikowave
Developed 3D scanners for non-destructive evaluation of corrosion in pipelines, born from cutting-edge research at the University of Kentucky.
An active leader in the machine-vision community
Dr. Lau serves on the Association for Advancing Automation (A3) Technical Board for Imaging and Sensing, and has presented webinars on 3D imaging for Vision Systems Design for over a decade.
Patent & IP expertise
With over 40 patents in imaging and related technologies, Dr. Lau also provides subject-matter expertise in patent law — including patent claim evaluation, claim-chart preparation, and expert testimony.
Decades of experience, ready for your hardest problems
Bridging academic and industry R&D — machine learning, graph & hypergraph neural networks, and AI for imaging to solve complex challenges and drive innovation.
Contact Dr. Lau →