The Newton Polygon Method for Differential Equations. - José Cano 001 (IWMM/GIAE, 2004)

On the Design of Spontaneous Networks Using a P2P Approach and Bluetooth. - José Cano 001; Juan-Carlos Cano; Pietro Manzoni; David Ferrández-Bell (ISCC, 2005)

A MANET Autoconfiguration System based on Bluetooth Technology. - José Cano Reyes; Eduardo Burgoa; Carlos T. Calafate; Juan-Carlos Cano; Pietro Manzoni (ISWCS, 2006)

Solving the user-to-host binding problem in ad hoc networks through photo-ids. - José Cano 001; Juan-Carlos Cano; Carlos Miguel Tavares Calafate; Pietro Manzoni (PE-WASUN, 2007)

EasyMANET: an extensible and configurable platform for service provisioning in MANET environments. - José Cano 001; Juan-Carlos Cano; Chai-Keong Toh; Carlos Miguel Tavares Calafate; Pietro Manzoni (IEEE Commun. Mag., 2010)

Efficient routing implementation in complex systems-on-chip. - José Cano 001; José Flich; José Duato; Marcello Coppola; Riccardo Locatelli (NOCS, 2011)

Spidergon STNoC design flow. - Florentine Dubois; José Cano 001; Marcello Coppola; José Flich; Frédéric Pétrot (NOCS, 2011)

Transient and Permanent Error Control for High-End Multiprocessor Systems-on-Chip. - Qiaoyan Yu; José Cano 001; José Flich; Paul Ampadu (NOCS, 2012)

Seamless MANET autoconfiguration through enhanced 802.11 beaconing. - MaJosé Villanueva; Carlos Miguel Tavares Calafate; Alvaro Torres; José Cano 001; Juan-Carlos Cano; Pietro Manzoni (Mob. Inf. Syst., 2013)

Efficient Routing in Heterogeneous SoC Designs with Small Implementation Overhead. - José Cano 001; José Flich; Antoni Roca 001; José Duato; Marcello Coppola; Riccardo Locatelli (IEEE Trans. Computers, 2014)

Dynamic process migration in heterogeneous ROS-based environments. - José Cano 001; Eduardo J. Molinos; Vijay Nagarajan; Sethu Vijayakumar (ICAR, 2015)

Quantitative characterization of the software layer of a HW/SW co-designed processor. - José Cano 001; Rakesh Kumar 003; Aleksandar Brankovic; Demos Pavlou; Kyriakos Stavrou; Enric Gibert; Alejandro Martínez; Antonio González 001 (IISWC, 2016)

Automatic configuration of ROS applications for near-optimal performance. - José Cano 001; Alejandro Bordallo; Vijay Nagarajan; Subramanian Ramamoorthy; Sethu Vijayakumar (IROS, 2016)

Task Variant Allocation in Distributed Robotics. - José Cano 001; David Robert White; Alejandro Bordallo; Ciaran McCreesh; Patrick Prosser; Jeremy Singer; Vijay Nagarajan (Robotics: Science and Systems, 2016)

HW/SW co-designed processors: Challenges, design choices and a simulation infrastructure for evaluation. - Rakesh Kumar 003; José Cano 001; Aleksandar Brankovic; Demos Pavlou; Kyriakos Stavrou; Enric Gibert; Alejandro Martínez; Antonio Gonzalez (ISPASS, 2017)

Characterising Across-Stack Optimisations for Deep Convolutional Neural Networks. - Jack Turner; José Cano 001; Valentin Radu; Elliot J. Crowley; Michael F. P. O'Boyle; Amos J. Storkey (IISWC, 2018)

Automatic Parameter Tuning of Motion Planning Algorithms. - José Cano 001; Yiming Yang; Bruno Bodin; Vijay Nagarajan; Michael F. P. O'Boyle (IROS, 2018)

Solving the task variant allocation problem in distributed robotics. - José Cano 001; David Robert White; Alejandro Bordallo; Ciaran McCreesh; Anna Lito Michala; Jeremy Singer; Vijay Nagarajan (Auton. Robots, 2018)

HAKD: Hardware Aware Knowledge Distillation. - Jack Turner; Elliot J. Crowley; Valentin Radu; José Cano 001; Amos J. Storkey; Michael F. P. O'Boyle (CoRR, 2018)

Performance Aware Convolutional Neural Network Channel Pruning for Embedded GPUs. - Valentin Radu; Kuba Kaszyk; Yuan Wen; Jack Turner; José Cano 001; Elliot J. Crowley; Björn Franke; Amos J. Storkey; Michael F. P. O'Boyle (IISWC, 2019)

Optimizing Grouped Convolutions on Edge Devices. - Perry Gibson; José Cano 001; Jack Turner; Elliot J. Crowley; Michael F. P. O'Boyle; Amos J. Storkey (ASAP, 2020)

Orpheus: A New Deep Learning Framework for Easy Deployment and Evaluation of Edge Inference. - Perry Gibson; José Cano 001 (ISPASS, 2020)

Design Space Exploration of Accelerators and End-to-End DNN Evaluation with TFLITE-SOC. - Nicolas Bohm Agostini; Shi Dong 002; Elmira Karimi; Marti Torrents Lapuerta; José Cano 001; José L. Abellán; David R. Kaeli (SBAC-PAD, 2020)

Accelerating Deep Learning Applications in Space. - Martina Lofqvist; José Cano 001 (CoRR, 2020)

SECDA: Efficient Hardware/Software Co-Design of FPGA-based DNN Accelerators for Edge Inference. - Jude Haris; Perry Gibson; José Cano 001; Nicolas Bohm Agostini; David R. Kaeli (SBAC-PAD, 2021)

Optimizing Data Processing in Space for Object Detection in Satellite Imagery. - Martina Lofqvist; José Cano 001 (CoRR, 2021)

Spartan: A Sparsity-Adaptive Framework to Accelerate Deep Neural Network Training on GPUs. - Shi Dong 002; Yifan Sun 002; Nicolas Bohm Agostini; Elmira Karimi; Daniel Lowell; Jing Zhou; José Cano 001; José L. Abellán; David R. Kaeli (IEEE Trans. Parallel Distributed Syst., 2021)

Transfer-Tuning: Reusing Auto-Schedules for Efficient Tensor Program Code Generation. - Perry Gibson; José Cano 001 (PACT, 2022)

Bifrost: End-to-End Evaluation and optimization of Reconfigurable DNN Accelerators. - Axel Stjerngren; Perry Gibson; José Cano 001 (ISPASS, 2022)

Reusing Auto-Schedules for Efficient DNN Compilation. - Perry Gibson; José Cano 001 (CoRR, 2022)

Productive Reproducible Workflows for DNNs: A Case Study for Industrial Defect Detection. - Perry Gibson; José Cano 001 (CoRR, 2022)

Exploring Effects of Computational Parameter Changes to Image Recognition Systems. - Nikolaos Louloudakis; Perry Gibson; José Cano 001; Ajitha Rajan (CoRR, 2022)

DeltaNN: Assessing the Impact of Computational Environment Parameters on the Performance of Image Recognition Models. - Nikolaos Louloudakis; Perry Gibson; José Cano 001; Ajitha Rajan (ICSME, 2023)

Improving Robustness Against Adversarial Attacks with Deeply Quantized Neural Networks. - Ferheen Ayaz; Idris Zakariyya; José Cano 001; Sye Loong Keoh; Jeremy Singer; Danilo Pau; Mounia Kharbouche-Harrari (IJCNN, 2023)

Fault Localization for Buggy Deep Learning Framework Conversions in Image Recognition. - Nikolaos Louloudakis; Perry Gibson; José Cano 001; Ajitha Rajan (ASE, 2023)

MutateNN: Mutation Testing of Image Recognition Models Deployed on Hardware Accelerators. - Nikolaos Louloudakis; Perry Gibson; José Cano 001; Ajitha Rajan (CoRR, 2023)

Fault Localization for Framework Conversions of Image Recognition Models. - Nikolaos Louloudakis; Perry Gibson; José Cano 001; Ajitha Rajan (CoRR, 2023)

A Differential Testing Framework to Evaluate Image Recognition Model Robustness. - Nikolaos Louloudakis; Perry Gibson; José Cano 001; Ajitha Rajan (CoRR, 2023)

DLAS: An Exploration and Assessment of the Deep Learning Acceleration Stack. - Perry Gibson; José Cano 001; Elliot J. Crowley; Amos J. Storkey; Michael F. P. O'Boyle (CoRR, 2023)

Fix-Con: Automatic Fault Localization and Repair of Deep Learning Model Conversions. - Nikolaos Louloudakis; Perry Gibson; José Cano 001; Ajitha Rajan (CoRR, 2023)

SECDA-TFLite: A toolkit for efficient development of FPGA-based DNN accelerators for edge inference. - Jude Haris; Perry Gibson; José Cano 001; Nicolas Bohm Agostini; David R. Kaeli (J. Parallel Distributed Comput., 2023)

AXI4MLIR: User-Driven Automatic Host Code Generation for Custom AXI-Based Accelerators. - Nicolas Bohm Agostini; Jude Haris; Perry Gibson; Malith Jayaweera; Norm Rubin; Antonino Tumeo; José L. Abellán; José Cano 001; David R. Kaeli (CGO, 2024)

Efficient Tiny Machine Learning for Human Activity Recognition on Low-Power Edge Devices. - Vinamra Sharma; Danilo Pau; José Cano 001 (RTSI, 2024)

Data Transfer Optimizations for Host-CPU and Accelerators in AXI4MLIR. - Jude Haris; Nicolas Bohm Agostini; Antonino Tumeo; David R. Kaeli; José Cano 001 (CoRR, 2024)

Designing Efficient LLM Accelerators for Edge Devices. - Jude Haris; Rappy Saha; Wenhao Hu; José Cano 001 (CoRR, 2024)

Accelerating PoT Quantization on Edge Devices. - Rappy Saha; Jude Haris; José Cano 001 (CoRR, 2024)

A survey on Ethereum pseudonymity: Techniques, challenges, and future directions. - Shivani Jamwal; José Cano 001; Gyu Myoung Lee; Nguyen Hoang Tran; Nguyen Truong 001 (J. Netw. Comput. Appl., 2024)

Decoupling Structural and Quantitative Knowledge in ReLU-based Deep Neural Networks. - José Duato; José I. Mestre; Manuel F. Dolz; Enrique S. Quintana-Ortí; José Cano 001 (EuroMLSys, 2025)

Exploiting Unstructured Sparsity in Fully Homomorphic Encrypted DNNs. - Aidan Ferguson; Perry Gibson; Lara D'Agata; Parker McLeod; Ferhat Yaman; Amitabh Das; Ian Colbert; José Cano 001 (EuroMLSys, 2025)

Exploring Robustness of Image Recognition Models on Hardware Accelerators. - Nikolaos Louloudakis; Perry Gibson; José Cano 001; Ajitha Rajan (ICSTW, 2025)

Biases in Edge Language Models: Detection, Analysis, and Mitigation. - Vinamra Sharma; Danilo Pietro Pau; José Cano 001 (CoRR, 2025)

Quantitative Analysis of Deeply Quantized Tiny Neural Networks Robust to Adversarial Attacks. - Idris Zakariyya; Ferheen Ayaz; Mounia Kharbouche-Harrari; Jeremy Singer; Sye Loong Keoh; Danilo Pau; José Cano 001 (CoRR, 2025)

DLAS: A Conceptual Model for Across-Stack Deep Learning Acceleration. - Perry Gibson; José Cano 001; Elliot Crowley; Amos J. Storkey; Michael F. P. O'Boyle (ACM Trans. Archit. Code Optim., 2025)

Accelerating Transposed Convolutions on FPGA-based Edge Devices. - Jude Haris; José Cano 001 (CoRR, 2025)