Dr. Chen Chen has multiple funded Ph.D. positions (Spring/Fall 2020) in the Department of
Electrical and Computer Engineering at the University of North Carolina at Charlotte (https://www.uncc.edu/).
The research work focuses on computer vision and machine learning techniques.
Dr. Chen Chen's main research interests are in the area of computer vision, image and video processing, and machine learning.
He had published ~70 papers in top-tier venues, including CVPR, ICCV, ICLR, AAAI, IJCAI, TIP, TCSVT, TNNLS.
He has more than 3500 citations since 2014.
He is an Area Chair of WACV 2019 and ACM Multimedia 2019.
He is an Associate Editor for the following journals:
• Neurocomputing
• Journal of Real-Time Image Processing
• Signal, Image and Video Processing
• Sensors Journal
The students will work on the following Research Topics:
(1) Computer vision tasks (object/action detection/recognition, semantic segmentation, etc.) ;
(2) Remote sensing (hyperspectral image analysis, aerial imagery analysis);
(3) Multi-modality learning (ML+NLP+CV+IMU);
(4) AutoML, deep learning model compression for edge computing;
(5) Interpretable machine learning.
Requirements:
(1) Undergraduate or MS students with degrees in Computer Science/Engineering, Electrical Engineering, Mathematics or related majors.
(2) Strong programming and/or mathematical skills.
(3) Candidates with research experience in image processing, computer vision, and machine learning, are preferred.
(4) Proficiency in English reading and writing (through GRE and TOEFL/IELTS scores).
(5) Strong motivation and passion for conducting research and solving challenging problems.
Interested individuals are encouraged to contact Dr. Chen Chen (chen.chen@uncc.edu) with the following documentation:
(1) A current CV;
(2) Transcripts if applicable;
(3) Representative publications if applicable.
======== 关于夏洛特 (Charlotte)的简介, 以下内容来自维基百科 =========
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For non-native English language holders: official and satisfactory English language proficiency scores on the Test of English as a Foreign Language (TOEFL) or the International English Language Testing System (IELTS) are required. A minimum score of 83 on the Internet-based TOEFL or a minimum overall band score of 6.5 on the IELTS is required.