Ning Zhang | Signal & Image Processing | Research Excellence Award

Published on by Electrical Engineering

Dr. Ning Zhang | Signal & Image Processing | Research Excellence Award

Postdoctor | Beijing institute of technology | China

Ning Zhang is a researcher in deep learning and remote sensing at the Beijing Institute of Technology, with expertise in computer vision, real-time processing, and onboard intelligent systems. He holds bachelor’s, master’s, and doctoral degrees in electronic information and information and communication engineering, with specialized training in lightweight neural networks and FPGA-based algorithm–hardware co-design. His professional experience includes leading and contributing to nationally funded and institutional projects focused on airborne and satellite AI deployment, where he has played key roles in algorithm development, system architecture design, and technical leadership. His research centers on remote sensing scene classification, object detection, model compression, and energy-efficient neural network accelerators, resulting in high-impact publications in leading IEEE journals, multiple authorized and accepted patents, and a citation record of 337 citations with an h-index of 9 and an i10-index of 8. He has received numerous prestigious scholarships, graduate honors, national-level competition awards, and maintains active engagement in academic and professional communities.

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Featured Publications


UniGeoSeg: Towards Unified Open-World Segmentation for Geospatial Scenes
S. Ni, D. Wang, H. Chen, H. Guo, N. Zhang, J. Zhang
arXiv Preprint · Open-World Geospatial Segmentation


S2Net: Spatial-aligned and Semantic-discriminative Network for Remote Sensing Object Detection
J. Yao, H. Chen, Y. Xie, N. Zhang, M. Yang, L. Chen
IEEE Transactions on Geoscience and Remote Sensing · Top-Tier Journal


High-throughput Energy-efficient Accelerator with Collaborative-Trainable Sparse-Quantization Method for On-Board Remote Sensing Processing
T. Wang, H. Chen, N. Zhang, S. Ni, X. Zhang, L. Chen, W. Li
IEEE Transactions on Geoscience and Remote Sensing · Energy-Efficient AI Hardware


High-Throughput and Energy-Efficient FPGA-Based Accelerator for All Adder Neural Networks
N. Zhang, S. Ni, L. Chen, T. Wang, H. Chen
IEEE Internet of Things Journal · FPGA Acceleration


Q-A2NN: Quantized All-Adder Neural Networks for Onboard Remote Sensing Scene Classification
N. Zhang, H. Chen, L. Chen, J. Wang, G. Wang, W. Liu
Remote Sensing · Lightweight Neural Networks

Zhenghua Qian | Machine Learning | Research Excellence Award

Published on by Electrical Engineering

Prof. Dr. Zhenghua Qian | Machine Learning | Research Excellence Award

Professor | Nanjing University of Aeronautics and Astronautics | China

Professor Zhenghua Qian is a distinguished scholar in solid mechanics and aerospace engineering, serving as a Professor at the College of Aerospace Engineering, Nanjing University of Aeronautics and Astronautics, and a core member of the State Key Laboratory of Mechanics and Control of Aerospace Structures, with expertise spanning wave propagation, piezoelectric and smart structures, structural health monitoring, and machine learning–assisted nondestructive evaluation. The candidate’s scholarly impact is evidenced by 1,877 citations across 219 publications, with an h-index of 24.

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Qingguo Lü | Electrical Engineering  | Research Excellence Award

Published on by Electrical Engineering

Dr. Qingguo Lü | Electrical Engineering  | Research Excellence Award

Associate Researcher | Chongqing University | China

Qingguo Lü is an Associate Researcher at Chongqing University specializing in distributed optimization, privacy-preserving machine learning, and smart grid systems. He earned his doctoral degree in computer science and technology with a strong focus on optimization theory and networked systems and subsequently advanced his expertise through postdoctoral research and international academic collaboration.  His scholarly contributions have delivered both theoretical advances and practical engineering solutions, achieving strong international visibility and impact. His academic influence is reflected by 1,174 citations, an h-index of 18, and an i10-index of 26. In recognition of his expertise and service, he holds multiple editorial and guest editorial appointments in international journals, serves on conference program committees, contributes extensively to peer review, holds innovation patents, and maintains professional standing as an IEEE Senior Member, demonstrating sustained excellence in research, leadership, and academic service suitable for a prestigious research award.

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Featured Publications

Distributed projection subgradient algorithm over time-varying general unbalanced directed graphs
H. Li, Q. Liu, T. Huang – IEEE Transactions on Automatic Control · Citations: 115
Accelerated convergence algorithm for distributed constrained optimization under time-varying general directed graphs
H. Li, Q. Lü, X. Liao, T. Huang – IEEE Transactions on Systems, Man, and Cybernetics: Systems · Citations: 104
Achieving acceleration for distributed economic dispatch in smart grids over directed networks
Q. Liu, X. Liao, H. Li, T. Huang – IEEE Transactions on Network Science and Engineering · Citations: 100
Convergence analysis of a distributed optimization algorithm with a general unbalanced directed communication network
H. Li, Q. Liu, T. Huang – IEEE Transactions on Network Science and Engineering · Citations: 96
Privacy masking stochastic subgradient-push algorithm for distributed online optimization
Q. Lü, X. Liao, T. Xiang, H. Li, T. Huang – IEEE Transactions on Cybernetics · Citations: 80

Rémi Cogranne | Signal & Image Processing | Research Excellence Award

Published on by Electrical Engineering

Dr. Rémi Cogranne | Signal & Image Processing | Research Excellence Award

Troyes University of Technology | France

Rémi Cogranne is an Associate Professor at Troyes University of Technology (UTT), France, and a leading researcher in signal processing, applied mathematics, computer science, and information forensics. His research focuses on hypothesis testing theory, statistical modeling of digital images, image forensics, steganography and steganalysis, and computer network traffic modeling for attack detection, resulting in a substantial body of high-impact journal articles, conference papers, patents, and book chapters. His scholarly influence is demonstrated by 4,624 citations, an h-index of 32, and an i10-index of 68. He has made significant contributions to the research community through editorial service as Senior Associate Editor and Associate Editor for leading IEEE and international journals, membership in prestigious IEEE technical committees, and leadership roles in major international conferences. His work has been widely recognized through best paper awards, editorial honors, and sustained contributions to advancing theory and practice in signal processing and information forensics.

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Featured Publications

Content-adaptive steganography by minimizing statistical detectability
V. Sedighi, R. Cogranne, J. Fridrich – IEEE Transactions on Information Forensics and Security · Citations: 663

Selection-Channel-Aware Rich Model for Steganalysis of Digital Images
T. Denemark, V. Sedighi, V. Holub, R. Cogranne, J. Fridrich – IEEE WIFS · Citations: 469

Moving steganography and steganalysis from the laboratory into the real world
A. D. Ker et al., including R. Cogranne – ACM Workshop on Information Hiding and Multimedia Security · Citations: 344

Rich Model for Steganalysis of Color Images
M. Goljan, J. Fridrich, R. Cogranne – IEEE WIFS · Citations: 203

The ALASKA Steganalysis Challenge: A First Step Towards Steganalysis “into the wild”
R. Cogranne, É. Giboulot, P. Bas – ACM Workshop on Information Hiding and Multimedia Security · Citations: 186