Thang Duong Quoc Le (CENTURI Multi-engineering platform)

Image processing and data analysis

His background

2023 – Present | Research Engineer in Image processing and data analysis, CENTURI
multi-engineering Platform, Aix-Marseille University, Marseille, France

2021 - 2022 | Postdoctoral Research Fellow in image processing and data analysis,
Mediterranean Institute of Oceanography, Marseille, France

2017 - 2020 | Ph.D. in Computer Science, BIA-BIBS platform, INRAE Nantes, Nantes, France

2014 - 2016 | MSc in Multimedia Information Technologies, EURECOM Institute, Sophia
Antipolis, France

2013 - 2014 | MSc in Information and Communication Technologies, John von Neumann Institute, Ho Chi Minh, Vietnam

2008 - 2012 | BSc degree in Information Technology, University of Science, Ho Chi Minh, Vietnam


Thang D.Q. Le is a research engineer in image processing and data analysis at CENTURI multi-engineering platform. Thang is in charge of setting up, carrying out and supporting projects concerning image / shape processing and analysis, machine learning and deep learning. Thang also supports code  implementation and transfer on common softwares and libraries such as Fiji, Icy, Matlab, Python, scikit-image, scikit-learn, and Tensorflow.


Thang has a great interest in machine learning, deep learning, data mining, image processing and data analysis. He is particularly interested in manipulating their applications in studying biological data.


Thang received his Master’s degree from EURECOM Institute, where he gained first-hand experience on biological data analysis from a research internship. The project was about tracking object motion and quantifying its characteristics from phase-contrast microscopy videos. After that, he did his dissertation work at INRAE Nantes. His doctoral dissertation was a study of wheat grain growth by applying quantitative morphological analysis and shape registration methods on 3D tomography images. His work allowed a detailed description of changes in grain shape and grain morphology over its development. Prior to joining CENTURI multi-engineering platform, he was a postdoctoral research fellow at Mediterranean Institute of Oceanography, Marseille. His research project consisted of developing an automatic classification system using deep learning methods for images of plankton acquired by ZooScan imaging devices.


Keywords: Deep Learning, Machine Learning, Image Processing and Analysis, Image Registration, Shape Processing and Analysis, Shape Registration, Morphological Analysis.