Henk Corporaal

Eindhoven University of Technology — Netherlands

Computer Science · Physical Sciences

40h-index7.3kcitations613works2.12yr avg
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Research Topics

Parallel Computing and Optimization Techniques(327), Embedded Systems Design Techniques(264), Interconnection Networks and Systems(170), Real-Time Systems Scheduling(78), Advanced Data Storage Technologies(56)

Publications613 total

Spike-based neuromorphic computing: An overview from bio-inspiration to hardware architectures and learning mechanisms
Microprocessors and Microsystems·2025Open Access
Flexible Hardware Accelerators for Ultra-Low Power Edge AI: The CONVOLVE Approach
2025
Sparse Convolutional Recurrent Learning for Efficient Event-based Neuromorphic Object Detection
2025· 1 cited
STEMS: Spatial-Temporal Mapping for Spiking Neural Networks
IEEE Transactions on Computers·2025· 1 cited
Sparse Convolutional Recurrent Learning for Efficient Event-based Neuromorphic Object Detection
arXiv (Cornell University)·2025Open Access
A Unified Framework for Mapping and Synthesis of Approximate R-Blocks CGRAs
arXiv (Cornell University)·2025Open Access
Multi-Partner Project: Securing Future Edge-AI Processors in Practice (CONVOLVE)
2025
Hardware/Software Co-Design Optimization for Training Recurrent Neural Networks at the Edge
Journal of Low Power Electronics and Applications·2025· 3 citedOpen Access
STEMS: Spatial-Temporal Mapping For Spiking Neural Networks
ArXiv.org·2025Open Access
Algorithm-Hardware Co-design for Accelerating Depthwise Separable CNNs
ACM Transactions on Design Automation of Electronic Systems·2025· 3 cited
POQ: Is There a Pareto-Optimal Quantization Strategy for Deep Neural Networks?
IEEE Access·2025· 1 citedOpen Access
Energy-efficient instruction compression with programmable dictionaries
Design Automation for Embedded Systems·2024Open Access
A Scalable Hardware Architecture for Efficient Learning of Recurrent Neural Networks at the Edge
2024· 2 citedOpen Access
Probabilistic inference in the era of tensor networks and differential programming
Physical Review Research·2024· 2 citedOpen Access
On the Importance of the Execution Schedule for Bayesian Inference
ACM transactions on probabilistic machine learning.·2024Open Access
Pushing the boundaries of probabilistic inference through message contraction optimization
2024
Invited: Achieving PetaOps/W Edge-AI Processing
2024· 2 citedOpen Access
Probabilistic Inference in the Era of Tensor Networks and Differential Programming
arXiv (Cornell University)·2024· 1 citedOpen Access
R-Blocks: an Energy-Efficient, Flexible, and Programmable CGRA
ACM Transactions on Reconfigurable Technology and Systems·2024· 8 citedOpen Access
RUBICON: a framework for designing efficient deep learning-based genomic basecallers
Genome biology·2024· 19 citedOpen Access
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Frequent Co-authors

Akash Kumar(7), Bart Mesman(6), Sander Stuijk(6), Gert-Jan van den Braak(5), Twan Basten(4), Francky Catthoor(4), Cedric Nugteren(4), V. Nollet(4), Stefan Valentin Gheorghita(3), Said Hamdioui(3), Lei Xie(3), Koen Bertels(3), Gagandeep Singh(3), Yajun Ha(3), Jan Hoogerbrugge(3), Ang Li(3), Maurice Peemen(2), Mottaqiallah Taouil(2), Hailong Jiao(2), Dirk J. Wouters(2)