Guoyu Lu Headshot

Guoyu Lu

Assistant Professor
Chester F. Carlson Center for Imaging Science
College of Science

585-475-6518
Office Location
Office Mailing Address
54 Lomb Memorial Dr., NY, 14623

Guoyu Lu

Assistant Professor
Chester F. Carlson Center for Imaging Science
College of Science

Education

BE, Nanjing University of P&T (China); MS, University of Trento (Italy); MS, RWTH Aachen University (Germany); MS, Ph.D., University of Delaware

Bio

Biography

I am an Assistant Professor at the Chester F. Carlson Center for Imaging Science of Rochester Institute of Technology (RIT). Prior to joining RIT, I was a research scientist on autonomous driving at Ford Research and computer vision engineer at ESPN Advanced Technology Group. I finished my PhD and MS in Computer Science at the University of Delaware. Before coming to UD, I was in European Master in Informatics (EuMI) Erasmus Mundus program. I obtained Master degree in Computer Science at University of Trento and Master degree in Media Informatics at RWTH Aachen University. I also finished an academic visiting in Auckland University of Technology in 2012. I was a research intern at Siemens Corporate Research in Princeton and Bosch Research in Palo Alto. I finished my Bachelor degree in Software Engineering at Nanjing University of Posts & Telecommunications, with a minor in Business Administration and Management.

I have board research interests spreading across computer vision, machine/deep learning, multimedia, and robotics.

585-475-6518

Personal Links
Areas of Expertise

Currently Teaching

IMGS-890
1 - 6 Credits
Doctoral-level research by the candidate on an appropriate topic as arranged between the candidate and the research advisor.
IMGS-790
1 - 6 Credits
Masters-level research by the candidate on an appropriate topic as arranged between the candidate and the research advisor.
IMGS-712
3 Credits
Images are 2D projections gathered from scenes by perspective projection. By making use of multiple images it is possible to construct 3D models of the scene geometry and of objects in the scene. The ability to derive representations of 3D scenes from 2D observations is a fundamental requirement for applications in robotics, intelligence, medicine and computer graphics. This course develops the mathematical and computational approaches to modeling of 3D scenes from multiple 2D views. After completion of this course students are prepared to use the techniques in independent research.

In the News

  • February 24, 2021

    environmental portrait of Guoyu Lu.

    RIT faculty using smartphones and artificial intelligence to help assess crop roots

    An RIT faculty member is creating new artificial intelligence systems that could empower agricultural researchers, breeders, nurseries, and other users to analyze the roots of their crops with the power of their smartphones. Assistant Professor Guoyu Lu is receiving a $450,000 New Investigator grant from the U.S. Department of Agriculture to conduct the research.