Projects per year
Personal profile
Personal profile
Dr. Pascal Lefèvre is an Assistant Professor in the School of AI and Advanced Computing. He received a Master's Degree in Cryptography and Computer Security from Bordeaux University, France, and then his Ph.D. from Poitiers University and XLIM Laboratory, France. He joined Shenzhen University as a Post-Doctoral researcher and later, worked in AI and Computer Vision in the tech industry. His past research involved multiple fields such as Cryptography, Error-Correcting Codes, Signal and Image Processing, Multimedia Security, and Artificial Intelligence. Some of his research interests include computer vision and interpretable deep learning.
Research interests
Neural Network Compression
Computer Vision / Machine Learning / Deep Learning
Multimedia Security / Error-Correcting Codes / Cryptography
Linear Algebra / Arithmetic
The Lean Proof Assistant / Lean 4
Experience
Assistant Professor, School of AI and Advanced Computing, Xi’an Jiaotong-Liverpool University, 2023 - now
AI R&D, Shenzhen Tech Industry, 2021 - 2023
Post-Doctoral Researcher, Shenzhen University, 2019 - 2021
Teaching
DTS203TC - Design of Algorithms and Analysis
Awards and honours
Best student paper award, CORESA 2017, France
Education/Academic qualification
Ph.D., Signal and Image Processing, Poitiers University and XLIM Laboratory, France, 2018
Msc, Cryptology and Computer Security, Bordeaux University, 2014
BSc, Mathematics and Computer Science, French Polynesia University, 2012
Person Types
- Staff
Fingerprint
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Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
Projects
- 1 Active
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RDF-A: Research on a new paradigm for neural network compression
1/01/25 → 31/12/27
Project: Internal Research Project
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Halfway Escape Optimization: A Quantum-Inspired Solution for Complex Optimization Problems
Li, J., PP Majeed, A. & LEFEVRE, P., 1 Sept 2024, (Submitted) In: Evolving Systems.Research output: Contribution to journal › Article › peer-review
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Randomness and Interpolation Improve Gradient Descent: A Simple Exploration in CIFAR datasets
Li, J., LEFEVRE, P. & PP Majeed, A., Sept 2024, Randomness and Interpolation Improve Gradient Descent: A Simple Exploration in CIFAR datasets. IEEE TCCC CyberCResearch output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review
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Codes and watermarks
Lefevre, P., Carré, P. & Gaborit, P., 4 Mar 2022, Multimedia Security 1: Authentication and Data Hiding. Wiley Blackwell, p. 77-127 51 p.Research output: Chapter in Book or Report/Conference proceeding › Chapter › peer-review
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Efficient image tampering localization using semi-fragile watermarking and error control codes
Lefèvre, P., Carré, P., Fontaine, C., Gaborit, P. & Huang, J., Jan 2022, In: Signal Processing. 190, 108342.Research output: Contribution to journal › Article › peer-review
Open Access -
Invisibility
Lefevre, P., Carré, P. & Alleysson, D., 4 Mar 2022, Multimedia Security 1: Authentication and Data Hiding. Wiley Blackwell, p. 129-160 32 p.Research output: Chapter in Book or Report/Conference proceeding › Chapter › peer-review
Activities
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Deep Learning Model Compression Algorithms and Applications
Pascal LEFEVRE (Speaker)
30 Oct 2024Activity: Talk or presentation › Presentation at conference/workshop/seminar
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2024 13th International Conference on Computing and Pattern Recognition
Pascal LEFEVRE (Participant)
26 Oct 2024Activity: Participating in or organising an event › Organising an event e.g. a conference, workshop, …
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A Brief Tour on Deep Learning Model Compression
Pascal LEFEVRE (Speaker)
26 Oct 2024Activity: Talk or presentation › Invited talk