Gridbot: An autonomous robot controlled by a Spiking Neural Network mimicking the brain's navigational system. - Guangzhi Tang; Konstantinos P. Michmizos 001 (CoRR, 2018)

Spiking Neural Network on Neuromorphic Hardware for Energy-Efficient Unidimensional SLAM. - Guangzhi Tang; Arpit Shah; Konstantinos P. Michmizos 001 (IROS, 2019)

Introducing Astrocytes on a Neuromorphic Processor: Synchronization, Local Plasticity and Edge of Chaos. - Guangzhi Tang; Ioannis E. Polykretis; Vladimir A. Ivanov; Arpit Shah; Konstantinos P. Michmizos 001 (CoRR, 2019)

Deep Reinforcement Learning with Population-Coded Spiking Neural Network for Continuous Control. - Guangzhi Tang; Neelesh Kumar; Raymond Yoo; Konstantinos P. Michmizos 001 (CoRL, 2020)

An Astrocyte-Modulated Neuromorphic Central Pattern Generator for Hexapod Robot Locomotion on Intel's Loihi. - Ioannis Polykretis; Guangzhi Tang; Konstantinos P. Michmizos 001 (ICONS, 2020)

Reinforcement co-Learning of Deep and Spiking Neural Networks for Energy-Efficient Mapless Navigation with Neuromorphic Hardware. - Guangzhi Tang; Neelesh Kumar; Konstantinos P. Michmizos 001 (IROS, 2020)

Real-time Mapping on a Neuromorphic Processor. - Guangzhi Tang; Konstantinos P. Michmizos 001 (NICE, 2020)

BioGrad: Biologically Plausible Gradient-Based Learning for Spiking Neural Networks. - Guangzhi Tang; Neelesh Kumar; Ioannis Polykretis; Konstantinos P. Michmizos 001 (CoRR, 2021)

Decoding EEG With Spiking Neural Networks on Neuromorphic Hardware. - Neelesh Kumar; Guangzhi Tang; Raymond Yoo; Konstantinos P. Michmizos 001 (Trans. Mach. Learn. Res., 2022)

Empirical study on the efficiency of Spiking Neural Networks with axonal delays, and algorithm-hardware benchmarking. - Alberto Patiño-Saucedo; Amirreza Yousefzadeh; Guangzhi Tang; Federico Corradi; Bernabé Linares-Barranco; Manolis Sifalakis (ISCAS, 2023)

Open the box of digital neuromorphic processor: Towards effective algorithm-hardware co-design. - Guangzhi Tang; Ali Safa; Kevin Shidqi; Paul Detterer; Stefano Traferro; Mario Konijnenburg; Manolis Sifalakis; Gert-Jan van Schaik; Amirreza Yousefzadeh (ISCAS, 2023)

NeuroBench: Advancing Neuromorphic Computing through Collaborative, Fair and Representative Benchmarking. - Jason Yik; Soikat Hasan Ahmed; Zergham Ahmed; Brian Anderson; Andreas G. Andreou; Chiara Bartolozzi; Arindam Basu; Douwe den Blanken; Petrut Bogdan; Sander M. Bohté; Younes Bouhadjar; Sonia M. Buckley; et al. (CoRR, 2023)

TRIP: Trainable Region-of-Interest Prediction for Hardware-Efficient Neuromorphic Processing on Event-Based Vision. - Cina Arjmand; Yingfu Xu; Kevin Shidqi; Alexandra F. Dobrita; Kanishkan Vadivel; Paul Detterer; Manolis Sifalakis; Amirreza Yousefzadeh; Guangzhi Tang (ICONS, 2024)

SENSIM: An Event-driven Parallel Simulator for Multi-core Neuromorphic Systems. - Prithvish Nembhani; Kanishkan Vadivel; Guangzhi Tang; Mohammad Tahghighi; Gert-Jan van Schaik; Manolis Sifalakis; Zaid Al-Ars; Amirreza Yousefzadeh (IJCNN, 2024)

EON-1: A Brain-Inspired Processor for Near-Sensor Extreme Edge Online Feature Extraction. - Alexandra F. Dobrita; Amirreza Yousefzadeh; Simon Thorpe; Kanishkan Vadivel; Paul Detterer; Guangzhi Tang; Gert-Jan van Schaik; Mario Konijnenburg; Anteneh Gebregiorgis; Said Hamdioui; Manolis Sifalakis (CoRR, 2024)

Overcoming the Limitations of Layer Synchronization in Spiking Neural Networks. - Roel Koopman; Amirreza Yousefzadeh; Mahyar Shahsavari; Guangzhi Tang; Manolis Sifalakis (CoRR, 2024)

Benchmarking of hardware-efficient real-time neural decoding in brain-computer interfaces. - Paul Hueber; Guangzhi Tang; Manolis Sifalakis; Hua-Peng Liaw; Aurora Micheli; Nergis Tomen; Yao-Hong Liu (Neuromorph. Comput. Eng., 2024)

Predicting the Lifespan of Industrial Printheads with Survival Analysis. - Dan Parii; Evelyne Janssen; Guangzhi Tang; Charalampos Kouzinopoulos; Marcin Pietrasik (ICPS, 2025)

Event-based optical flow on neuromorphic processor: ANN vs. SNN comparison based on activation sparsification. - Yingfu Xu; Guangzhi Tang; Amirreza Yousefzadeh; Guido C. H. E. de Croon; Manolis Sifalakis (Neural Networks, 2025)

Explore Activation Sparsity in Recurrent LLMs for Energy-Efficient Neuromorphic Computing. - Ivan Knunyants; Maryam Tavakol; Manolis Sifalakis; Yingfu Xu; Amirreza Yousefzadeh; Guangzhi Tang (CoRR, 2025)

VFL-RPS: Relevant Participant Selection in Vertical Federated Learning. - Afsana Khan; Marijn ten Thij; Guangzhi Tang; Anna Wilbik (CoRR, 2025)

Adaptively Pruned Spiking Neural Networks for Energy-Efficient Intracortical Neural Decoding. - Francesca Rivelli; Martin Popov; Charalampos S. Kouzinopoulos; Guangzhi Tang (CoRR, 2025)

SteelBlastQC: Shot-blasted Steel Surface Dataset with Interpretable Detection of Surface Defects. - Irina Ruzavina; Lisa Sophie Theis; Jesse Lemeer; Rutger de Groen; Leo Ebeling; Andrej Hulak; Jouaria Ali; Guangzhi Tang; Rico Mockel (CoRR, 2025)

SENMAP: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems. - Prithvish Nembhani; Oliver Rhodes; Guangzhi Tang; Alexandra F. Dobrita; Yingfu Xu; Kanishkan Vadivel; Kevin Shidqi; Paul Detterer; Mario Konijnenburg; Gert-Jan van Schaik; Manolis Sifalakis; Zaid Al-Ars; et al. (CoRR, 2025)

Sparse Convolutional Recurrent Learning for Efficient Event-based Neuromorphic Object Detection. - Shenqi Wang; Yingfu Xu; Amirreza Yousefzadeh; Sherif Eissa; Henk Corporaal; Federico Corradi; Guangzhi Tang (CoRR, 2025)

A Segmented Robot Grasping Perception Neural Network for Edge AI. - Casper Bröcheler; Thomas Vroom; Derrick Timmermans; Alan van den Akker; Guangzhi Tang; Charalampos S. Kouzinopoulos; Rico Mockel (CoRR, 2025)