José Cano

University of Glasgow — United Kingdom

Computer Science · Physical Sciences

11h-index451citations73works2.12yr avg
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Research Topics

Advanced Neural Network Applications(22), Parallel Computing and Optimization Techniques(16), Adversarial Robustness in Machine Learning(13), Interconnection Networks and Systems(8), Domain Adaptation and Few-Shot Learning(8)

Publications73 total

F-BFQ: Flexible Block Floating-Point Quantization Accelerator for LLMs
arXiv (Cornell University)·2025Open Access
Accelerating Transposed Convolutions on FPGA-based Edge Devices
arXiv (Cornell University)·2025Open Access
ICE-Pruning: An Iterative Cost-Efficient Pruning Pipeline for Deep Neural Networks
2025· 1 cited
ICE-Pruning: An Iterative Cost-Efficient Pruning Pipeline for Deep Neural Networks
arXiv (Cornell University)·2025Open Access
Exploring Robustness of Image Recognition Models on Hardware Accelerators
2025Open Access
Decoupling Structural and Quantitative Knowledge in ReLU-based Deep Neural Networks
2025· 1 citedOpen Access
Exploiting Unstructured Sparsity in Fully Homomorphic Encrypted DNNs
2025· 3 citedOpen Access
Exploiting Unstructured Sparsity in Fully Homomorphic Encrypted DNNs
arXiv (Cornell University)·2025Open Access
Biases in Edge Language Models: Detection, Analysis, and Mitigation
arXiv (Cornell University)·2025· 1 citedOpen Access
DQA: An Efficient Method for Deep Quantization of Deep Neural Network\n Activations
arXiv (Cornell University)·2024Open Access
Accelerating PoT Quantization on Edge Devices
2024Open Access
Accelerating PoT Quantization on Edge Devices
arXiv (Cornell University)·2024Open Access
Efficient Tiny Machine Learning for Human Activity Recognition on Low-Power Edge Devices
2024· 3 citedOpen Access
A survey on Ethereum pseudonymity: Techniques, challenges, and future directions
Journal of Network and Computer Applications·2024· 17 citedOpen Access
DLAS: A Conceptual Model for Across-Stack Deep Learning Acceleration
ACM Transactions on Architecture and Code Optimization·2024· 2 citedOpen Access
Designing Efficient LLM Accelerators for Edge Devices
arXiv (Cornell University)·2024· 4 citedOpen Access
AXI4MLIR: User-Driven Automatic Host Code Generation for Custom AXI-Based Accelerators
2024· 3 citedOpen Access
AXI4MLIR: User-Driven Automatic Host Code Generation for Custom AXI-Based Accelerators
arXiv (Cornell University)·2023· 1 citedOpen Access
DLAS: An Exploration and Assessment of the Deep Learning Acceleration Stack
arXiv (Cornell University)·2023· 2 citedOpen Access
Fault Localization for Buggy Deep Learning Framework Conversions in Image Recognition
2023· 5 citedOpen Access
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Frequent Co-authors

Perry Gibson(12), Michael O’Boyle(10), Elliot J. Crowley(9), Amos Storkey(9), Jack Turner(7), Nícolas Bohm Agostini(6), David Kaeli(6), Jude Haris(5), José Flich(5), Juan‐Carlos Cano(5), Carlos T. Calafate(5), Pietro Manzoni(5), Valentin Radu(4), José Luis Abellán(4), Vijay Nagarajan(4), J. Duato(4), Marcello Coppola(4), Alejandro Bordallo(3), Riccardo Locatelli(3), Miguel Delgado(2)