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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 Dive into the research topics where Chen Feng is active. These topic labels come from the works of this person. Together they form a unique fingerprint.

Augmented reality Engineering & Materials Science
Cameras Engineering & Materials Science
Sensors Engineering & Materials Science
Robotics Engineering & Materials Science
Robots 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 2019

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

Camera marker networks for articulated machine pose estimation

Feng, C., Kamat, V. R. & Cai, H., Dec 1 2018, In : Automation in Construction. 96, p. 148-160 13 p.

Research output: Contribution to journalArticle

Uncertainty analysis
Computer vision
Global positioning system
Large scale systems

Compression of 3-D point clouds using hierarchical patch fitting

Cohen, R. A., Krivokuca, M., Feng, C., Taguchi, Y., Ochimizu, H., Tian, D. & Vetro, A., Feb 20 2018, 2017 IEEE International Conference on Image Processing, ICIP 2017 - Proceedings. IEEE Computer Society, Vol. 2017-September. p. 4033-4037 5 p.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Virtual reality

Direct multichannel tracking

Jaramillo, C., Taguchi, Y. & Feng, C., May 25 2018, Proceedings - 2017 International Conference on 3D Vision, 3DV 2017. Institute of Electrical and Electronics Engineers Inc., p. 347-355 9 p.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Neural networks

Fast resampling of three-dimensional point clouds via graphs

Chen, S., Tian, D., Feng, C., Vetro, A. & Kovacevic, J., Feb 1 2018, In : IEEE Transactions on Signal Processing. 66, 3, p. 666-681 16 p.

Research output: Contribution to journalArticle

Feature extraction
Filter banks
Mathematical operators