Liang (Eric) Yang is a currently Ph.D candidate at the City College of New York, City University of New York under the supervision of Dr. Jizhong Xiao at the CCNY Robotics Lab. He had his master-doc research in State Key Lab of Robotics, Chinese Academy of Sciences.
His research interests includes visual localition and sensor fusion, deep inspection, computer vision, and navigation for mobile autonomous robots.
Liang Yang had won 2014 IEEE ICMA Best Student Paper Award, 2017 Best IBM CRL Intern Research Project, and 2015 ICIRA Best Student Paper Award Finalist. He interned at IBM CRL NLP Group last summer (2017), where he was able to collaborate with Dr. Zhong Su on developing a robotic deep DJ system.
I am now working on two projects supported by US Department of Transportation: 1) Deep Inspection using a Multi-scale network from detection to segmentation, and then back project to 3D space. 2) Flying and Wall Climbing Robots for Inspection, the project involves ROS, Android, Computer Vision, etc experience. If you are interested, please email me.
PhD in Electrical Engineering, 2019
The City Collge/City University Of New York
PHD in Pattern Recognition and Intelligent Systems, 2017
University of Chinese Academy of Sciences
MS in Control System, 2013
University Of Science And Technology Of China
Just released the dataset for paper: Semantic Metric 3D Reconstruction for Concrete Inspection (Authors are: Liang Yang, Bing Li, Wei Li, Biao Jiang, and Jizhong Xiao), 2018 CVPRW. Please check here Code and Data. Also check here for our previous work: concrete structure inspection Code and Data.
Our paper “Semantic Metric 3D Reconstruction for Concrete Inspection (Authors are: Liang Yang, Bing Li, Wei Li, Biao Jiang, and Jizhong Xiao)” has been accepted by IEEE CVPR2018 Workshop, see you at Salt Lake.
Exciting News!!! > Our Project – WIND-RIDER, Got $150, 000 investment!!!. – Blade inspection robots for wind-farm owners and OEM directors-of-operations to reduce blade replacement costs, where we perform inspection using GPR, camera etc with deep neural network algorithm!! I am the Technical Lead, and we are about to fly, if you have interest to work with our team, shoot me an email.
Thomas Wilk (Entrepreneurial Lead) | Eric (Liang) Yang (Technical Lead)
See how things really be interesting combining 3D and 2D, the indoor semantic segmentation and reconstruction, wait for my further paper work:
This work aims to provide a robust and easy access solution of scale-visual-positioning
Field test at bridge-tunnel vertical surface at Riverside Dr, New York
From end of 2016, I was supported by US Dept. of Transportation of the project: Tier I University Transportation Center: Inspecting and Preserving Infrastructure through Robotic Exploration (INSPIRE Center). We proposed a new approach using Unmanned Aerial Vehicle(UAV) towards a Concrete Structure Spalling and Crack database (CSSC), we also fined tuned the vgg 16 with a detection baseline for spalling/crack detection.
Thanks to U.S. Army Research Office grant and GSSI donation for visual SLAM and IMU fusion research for high aacuracy positioning and reconstruction
3D Lidar mapping and autonomous indoor parking solution
I am teaching at The City College of New York as Adjunct Lecturer for EE221, my office hour: Friday - 2 ~ 4 PM.
Year 2018 Fall: Measurement Laboratory I, please find the dropbox link below to download the materials you need:
Year 2018 Spring: Measurement Laboratory I, please find the dropbox link below to download the materials you need: