♨️ SUMMARY
I obtained my Ph.D. degree in Computer Vision and Image Processing from Université Paris-Saclay, France. My research interests include semantic segmentation, object detection and tracking, unsupervised domain adaptation, and multi-modal visual data fusion. Recently, I am also interested in the application of multi-modal visual-language modeling for image understanding. In addition, I also have a rich experience in the field of industrial computer vision, including machine vision, deep learning, and robotics. I am passionate about applying my knowledge and skills to solve real-world problems.
You can check the selected projects and publications for more details.
🎓 EDUCATION
Postdoctoral Researcher, Computer Vision, Robotics, and Machine Learning
- Systems Analysis and Architecture Laboratory (LAAS), National Centre for Scientific Research (CNRS), France. From 2024
Ph.D., Computer Vision
School of Sciences and Technologies of Information and Communication, Université Paris-Saclay, France
Sept. 2020 - Oct. 2023School of Engineering Sciences, Arts et Métiers (ENSAM), ParisTech, France.
Sept. 2019 - Aug. 2020
M.Eng., Mechanical Engineering and Automation
- School of Mechanical Engineering, Hefei University of Technology, China.
Sept. 2014 - May. 2017
GPA: 3.62/4.0 (rank the top 5%)
B.Eng., Mechanical Engineering and Automation
- School of Mechanical Engineering, Anhui Agriculture University, China.
Sept. 2009 - Jul. 2013
GPA: 3.68/4.0 (rank the top 10%)
📚 RESEARCH EXPERIENCE
Université Paris-Saclay, STIC, Paris, France.
Sept. 2020 - present
Ph.D Student (IBISC Lab)- Research on the topic of multi-modal visual data fusion for outdoor scene understanding.
- Investigating the influence of multi-modal visual data on the domain adaptation for semantic segmentation.
- Studying the different fusion strategies and developing novel visual data fusion strategies for scene understanding.
- Exploring the potential of multi-modal visual data fusion for different computer vision tasks, such as object detection, semantic segmentation, and multiple object tracking.
Publications: [1], [2], [4], [5]
Arts et Métiers (ENSAM), ParisTech, Aix-en-Provence, France.
Sept. 2019 - Aug. 2020
Ph.D Student (LISPEN Lab)- Research on the topic of deep learning for multi-modal segmentation of point clouds for reverse engineering of mechanical assemblies.
- Investigating the pipeline of deep learning-based reverse engineering.
- Studying and designing novel algorithms for point cloud segmentation.
- Designing and developing automatic synthetic 3D CAD models and point clouds generation tools for reverse engineering.
Publications: [3]
National Institute of Informatics, Tokyo, Japan.
Nov. 2022 - Apr. 2023
Computer Vision Research Intern. (Prendinger Lab)- Investigating object detection and tracking algorithms with stereo camera from drone’s perspective.
- Developing drone collision avoidance system based on the designed multiple object tracking algorithm.
Publications: [6]
Hefei University of Technology, Hefei, China.
Sept. 2014 - May. 2017
M.Eng- Research on the application of various measurement methods in non-destructive testing, including laser triangulation, time-of-flight, spectral confocal, and monocular vision measurement methods.
- Developing DSP-based control platforms and systems, including the design of electrical schematics, development of detection algorithms, software development for the control system, porting of communication protocols, and user interface design.
💼 WORK & LEADERSHIP EXPERIENCE
Cognex, Beijing, China.
Jun. 2017 - Aug. 2019
Machine Vision Software Engineer.- Responsible for over 5 industrial projects, involving the development and maintenance of applications related to vision positioning and defect detection.
- Developed machine vision algorithms to guide robotic arms in object grasping. (A patent was filed)
- Trained collaborative clients on artificial intelligence and its industrial applications.
Achievements: Obtained a software copyright and an invention patent in China.
School of Mechanical Engineering, Hefei University of Technology, Hefei, China.
Sept. 2015 - Jun. 2016
Header of Party Branch.- Organizing discussion group (30+ members) focusing on sharing events and ideas.
- Leading and organizing volunteer activities to foster community engagement and social responsibility.
Achievements: Excellent Student Leaders, Hefei University of Technology, 2016
Hefei University of Technology, Hefei, China.
Mar. 2014 - Sept. 2014
CIMS Institute Intern.- 3D modeling from 2D sketch and finite element analysis.
More details please check Projects.
💻 TECHNICAL SKILLS
- Programming Languages:
Python, C#, LaTeX, C++, C - Deep Learning Frameworks:
PyTorch, TensorFlow - Robotics Frameworks: ROS2
- Software:
OpenCV, Git, VSCode, PyCharm, Microsoft Office, SolidWorks,
FreeCAD, AutoCAD, MATLAB - Operating Systems:
Windows, Linux, MacOS
📝 PUBLICATIONS
Get more details on Publications page.
Drone-based airborne object tracking using a stereo camera for collision avoidance, IEEE Trans. on Intelligent Transportation Systems, (Q1, IF: 9.5). Sijie Hu, Desire Sidibe, Helmut Prendinger.
Rethinking Self-Attention for Multispectral Object Detection, IEEE Trans. on Intelligent Transportation Systems, (Q1, IF: 9.5).
Sijie Hu, Fabien Bonardi, Samia Bouchafa, Helmut Prendinger, Desire Sidibe.Multi-modal unsupervised domain adaptation for semantic image, Pattern Recognition 2023, (Q1, IF: 8.5).
Sijie Hu, Fabien Bonardi, Samia Bouchafa, Desire Sidibe.SMA-Net: Deep learning-based identification and fitting of CAD models from point clouds, Enginnering with Computers 2022, (Q1, IF: 8.7).
Sijie Hu, Arnaud Polette, Jean-Philippe PernotA Hybrid Multi-modal Visual Data Cross Fusion Network for Indoor and Outdoor Scene Segmentation, ICPR 2022.
Sijie Hu, Fabien Bonardi, Samia Bouchafa, Desire Sidibe.A General Two-Branch Decoder Architecture for Improving Encoder-Decoder Image Segmentation Models, VISAPP 2022.
Sijie Hu, Fabien Bonardi, Samia Bouchafa, Desire Sidibe.
📣 TALKS & PRESENTATIONS
The 26th International Conference on Pattern Recognition, (Aug. 2022.)
Topic: A Hybrid Multi-modal Visual Data Cross Fusion Network for Indoor and Outdoor Scene Segmentation.IBISC Lab Seminar, Université Paris-Saclay, (Jul. 2022.)
Topic: Multi-modal Unsupervised Domain Adaptation for Semantic Segmentation.The 17th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications. (Feb. 2022.)
Topic: A General Two-Branch Decoder Architecture for Improving Encoder-Decoder Image Segmentation Models.
🌐 LANGUAGES
🇨🇳 Mandarin: Native 🇬🇧 English: Fluent
🏆 AWARDS
- “Doctoral students” Prize, Université Paris Saclay & Institut Polytechnique de Paris, 2023
- Outstanding Graduates, Hefei University of Technology, 2017
- First -class scholarship, Hefei University of Technology, 2016
- Enterprise scholarship of Anhui HELI, Hefei University of Technology, 2016
- Excellent Student Leaders, Hefei University of Technology, 2016
- Advanced individual, Hefei University of Technology, 2015
- First -class scholarship, Hefei University of Technology, 2015
- First -class scholarship, Hefei University of Technology, 2014