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Personal profile

Research interests

Robotic Vision and Machine Learning, Photogrammetry and Remote Sensing, Augmented and Virtual Reality, with applications in Civil and Mechanical Engineering.


Dr. Chen Feng earned his Bachelor degree in geospatial engineering from Wuhan University in China. Then he went to the University of Michigan at Ann Arbor and earned a master degree in electrical engineering and a Ph.D. in civil engineering in 2015, where he studied robotic vision and learning and attempted to apply them in civil engineering. After graduation, he became a research scientist in the computer vision group at the Mitsubishi Electric Research Labs (MERL), focusing on visual SLAM and deep learning. In 2018 August, he became an assistant professor jointly in the Department of Mechanical and Aerospace Engineering and the Department of Civil and Urban Engineering in NYU Tandon School of Engineering, where his lab AI4CE aims to advance the robotic vision and learning with applications in civil/mechanical engineering.

Professional Affiliations


Fingerprint Weighted list of dominant concepts in the person's research.

Augmented reality Engineering & Materials Science
Cameras Engineering & Materials Science
Sensors Engineering & Materials Science
Robots Engineering & Materials Science
Robotics Engineering & Materials Science
Semantics Engineering & Materials Science
Edge detection Engineering & Materials Science
Experiments Engineering & Materials Science

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Research Output 2010 2020

A scene-adaptive descriptor for visual SLAM-based locating applications in built environments

Xu, L., Feng, C., Kamat, V. R. & Menassa, C. C., Apr 2020, In : Automation in Construction. 112, 103067.

Research output: Contribution to journalArticle

Optical radar
Neural networks

An Occupancy Grid Mapping enhanced visual SLAM for real-time locating applications in indoor GPS-denied environments

Xu, L., Feng, C., Kamat, V. R. & Menassa, C. C., Aug 1 2019, In : Automation in Construction. 104, p. 230-245 16 p.

Research output: Contribution to journalArticle

Global positioning system
Motion planning
Position measurement

Primitive fitting using deep geometric segmentation

Li, D. & Feng, C., Jan 1 2019, p. 780-787. 8 p.

Research output: Contribution to conferencePaper

Reverse engineering
Neural networks

Through-wall object recognition and pose estimation

Wang, R., Xiang, S., Feng, C., Wang, P., Ergan, S. & Fang, Y., Jan 1 2019, p. 1176-1183. 8 p.

Research output: Contribution to conferencePaper

Object recognition
Electric wire
Learning algorithms

Towards mobile projective AR for construction co-robots

Xiang, S., Wang, R. & Feng, C., Jan 1 2019, p. 1106-1113. 8 p.

Research output: Contribution to conferencePaper

Augmented reality
Construction industry