Zilverling

A. Yousefzadeh PhD (Amir)

Universitair docent
EEMCS-CS-CAES
Zilverling 5090
a.yousefzadeh@utwente.nl
+31534897988
Visitekaartje

Ik ben in februari 2024 bij de Universiteit Twente begonnen als universitair docent edge AI. Mijn focus ligt op het ontwerpen van embedded AI en neuromorfische systemen.


Kort CV:


Ph.D. in neuromorfische engineering bij IMSE, proefschrift: Digital Design For Neuromorphic Bio-Inspired Vision Processing

2018-2020: Bij de startup GrAI Matter Labs, later overgenomen door SNAP, heb ik voornamelijk gewerkt aan de architectuur van de NeuronFlow-processor

2020-2024: Bij imec, bij de Hardware Efficient AI-groep, heb ik voornamelijk gewerkt aan de architectuur van de SENECA-processor

2024-heden: universitair docent, Computer Architecture for Embedded Systems

Expertises

  • Computer Science

    • Neural Network
    • Computer Hardware
    • Energy Efficient
    • Artificial Intelligence
    • Electronic Learning

  • Engineering

    • Internet-Of-Things
    • Artificial Neural Network
    • Sensor System

Organisaties

Mijn onderzoeksinteresses:

  • Neuromorphic Sensing and processing
  • Low Power / Scalable AI processos
  • Hardware aware algorithm design

Ik gebruik uitgebreid digitale hardware-ontwerptools en gate-level simulaties om hardware-architecturen te co-optimaliseren met neurale netwerkalgoritmen. Enkele van mijn technische ervaringen:

  • Ontwerp van programmeerbare neuromorfische processoren voor ingebedde AI-toepassingen
  • On-device leeralgoritmen en hardwareversnellers
  • Bio-geïnspireerde visuele verwerking
  • Benchmarking en vergelijking van verschillende algoritme-optimalisaties in hardware

Op zoek naar PhD- of postdoc-posities: kijk op de UTwente-carrièrewebsite. Alle posities worden daar geadverteerd en sollicitaties moeten online worden ingediend. Stuur uw sollicitatie niet per e-mail.

Op zoek naar masterscriptie of stage: stuur me een e-mail met uw cv en cijfers (zowel bachelor als master).

Publicaties

2025

Spike-based neuromorphic computing: An overview from bio-inspiration to hardware architectures and learning mechanisms (2025)Microprocessors and microsystems. Article 105240 (E-pub ahead of print/First online). Gebregiorgis, A., Yousefzadeh, A., Eissa, S., Siddiqi, M. A., Frenkel, C., Zenke, F., Bohte, S., Mahmoud, A. N., Das, A., Hamdioui, S., Corporaal, H. & Corradi, F.https://doi.org/10.1016/j.micpro.2025.105240Editorial: Algorithm-hardware co-optimization in neuromorphic computing for efficient AI (2025)Frontiers in Neuroscience, 19, 01-03. Article 1746610. Yousefzadeh, A., Patiño-Saucedo, A., De Croon, G. & Sifalakis, M.https://doi.org/10.3389/fnins.2025.1746610From RISC-V Cores to Neuromorphic Arrays: A Tutorial on Building Scalable Digital Neuromorphic Processors (2025)[Working paper › Preprint]. ArXiv.org. Yousefzadeh, A.https://doi.org/10.48550/arXiv.2512.00113Overcoming the Limitations of Layer Synchronization in Spiking Neural Networks (2025)[Working paper › Preprint]. ArXiv.org. Koopman, R., Yousefzadeh, A., Shahsavari, M., Tang, G. & Sifalakis, M.https://doi.org/10.48550/arXiv.2408.05098TrackCore-F: Deploying Transformer-Based Subatomic Particle Tracking on FPGAs (2025)[Working paper › Preprint]. ArXiv.org. Blankestijn, A., Odyurt, U. & Yousefzadeh, A.https://doi.org/10.48550/arXiv.2509.26335Memory Wall is not gone: A Critical Outlook on Memory Architecture in Digital Neuromorphic Computing (2025)In IEEE Computer Society Annual Symposium on VLSI, ISVLSI 2025 - Conference Proceedings (Proceedings of IEEE Computer Society Annual Symposium on VLSI, ISVLSI). IEEE. Yousefzadeh, A., Sohail, S. & Varbanescu, A. L.https://doi.org/10.1109/ISVLSI65124.2025.11130262Event-based optical flow on neuromorphic processor: ANN vs. SNN comparison based on activation sparsification (2025)Neural networks, 188. Article 107447. Xu, Y., Tang, G., Yousefzadeh, A., de Croon, G. C. H. E. & Sifalakis, M.https://doi.org/10.1016/j.neunet.2025.107447Sparse Convolutional Recurrent Learning for Efficient Event-based Neuromorphic Object Detection (2025)[Working paper › Preprint]. ArXiv.org. Wang, S., Xu, Y., Yousefzadeh, A., Eissa, S., Corporaal, H., Corradi, F. & Tang, G.https://doi.org/10.48550/arXiv.2506.13440Senmap: Multi-objective data-flow mapping and synthesis for hybrid scalable neuromorphic systems (2025)[Working paper › Preprint]. ArXiv.org. Nembhani, P. V., Rhodes, O., Tang, G., Dobrita, A. F., Xu, Y., Vadivel, K., Shidqi, K., Detterer, P., Konijnenburg, M., van Schaik, G.-J., Sifalakis, M., Al-Ars, Z. & Yousefzadeh, A.https://doi.org/10.48550/arXiv.2506.03450Efficient Synaptic Delay Implementation in Digital Event-Driven AI Accelerators (2025)[Working paper › Preprint]. ArXiv.org. Meijer, R., Detterer, P., Yousefzadeh, A., Patino-Saucedo, A., Tang, G., Vadivel, K., Xu, Y., Gomony, M.-D., Corradi, F., Linares-Barranco, B. & Sifalakis, M.https://doi.org/10.48550/arXiv.2501.13610

Onderzoeksprofielen

Funded projects: 

  1. NeAIxt (2025): Next Generation of edge AI crossing technology fields
  2. TIRAMISU(2024): Training and Innovation in Reliable and Efficient Chip Design for Edge AI
  3. NEUROKIT2E(2023): Open-source deep learning platform dedicated to Embedded hardware and Europe
  4. REBECCA(2023): Reconfigurable Heterogeneous Highly Parallel Processing Platform for safe and secure AI
  5. NimbleAI(2022): Ultra-energy efficient and secure neuromorphic sensing and processing at the endpoint

PhD Students: 

  1. Sameed Sohail(2024-Present): Embedded Neuromorphic Processor Architecture with On-Device Adaptation

Master students: 

  1. Kaushik Narayan (2026): Compressed sensing for neuromorphic processor pre-processing (with Innatera)
  2. Mohammed Huzaifa (2026): Accelerator design for learning in neuromorphic processors
  3. Sjoerd van der Plaat (2026): Optimizing off-chip memory access through dynamic inference, applied on Jetson Nano.
  4. Stefan den Haan (2026): Asynchronous inference on SparkRV neuromorphic processor
  5. Lennart Jensen (2026): Improving reliability of neuromorphic processor for space applications
  6. Peter Kingma (2026): Error correction for a fast asynchronous neuromorphic link
  7. Ada Dotsika (2026): Analog implementation of GRU unit for keyword spotting applications
  8. Douwe Vries (2026): Post-synthesis power optimization for digital neuromorphic processors
  9. Pratik Phadte (2026): Near sensor processing for smart lighting application (with Signify)
  10. Arjan Blankestijn(2026): Accelerating Transformers on ZynQ platforms (work in progress conference presentation)
  11. Belal Elshinnawey (2026): Embedded FPGA design for neuromorphic processors
  12. Bram Bremer(2025, cum-laude): Real-time acoustic imaging on an FPGA using recurrent neural networks
  13. Mattias Westerink(2025, cum-laude): Designing co-processor for RISC-V-based neuromorphic system
  14. Wiebren Wijnstra(2025): Optimizing RISC-V processors for neuromorphic workloads
  15. Wim Nijsink(2025): Measuring the reliability of existing neuromorphic solutions
  16. Sharon Moolenaar(2025): Optimizing Network on chip for neuromorphic processors
  17. Haoran Wolfgang(2024): Low-latency hardware accelerator for sparse convolutional recurrent network toward neuromorphic object detection
  18. Ivan Knunyants(2024): Optimizing transformer neural networks for event-driven inference in hardware
  19. Yashwanth Gopinath(2024): Open-source RISC-V-based neuromorphic processor
  20. Roel Koopman (2023): Overcoming the Limitations of Layer Synchronization in Spiking Neural Networks
  21. Cina Arjmand (2023): Trainable Region of Interest Prediction: Hard Attention Framework for Hardware-Efficient Event-Based Computer Vision Neural Networks on Neuromorphic Processors  
  22. Lucas Huijbregts (2023): Transposable Multiport SRAM-based In-Memory Compute Engine for Binary Spiking Neural Networks in 3nm FinFET
  23. Shenqi Wang (2023): Hardware Efficient Object Detection for High Spatial Resolution Event Camera
  24. Refik Can Bilgiç (2023):  Analytical Modelling of 3D System Partitioning
  25. Pietro Martinello (2023): Forging a Multimodal Dataset: Uniting Diverse Sensor Data for Enhanced Analysis
  26. Roy Meijer (2023): Efficient Synaptic Delay Implementation in Digital Event-Driven Neuromorphic Processors
  27. Kevin Shidqi (2022): Benchmarking and Algorithm Optimization for SENeCA, a RISC-V-based Neuromorphic Processor
  28. Alexandra-Florentina Dobrit (2022): Brain-inspired feature extraction for near sensor extreme edge processing with Spiking Neural Networks
  29. Prithvish Vijaykumar Nembhani (2022): Efficient mapping of large-scale SNN and rate-based DNN on SENeCA
  30. Preetha Vijayan (2021): Temporal Delta Layer: Exploiting Temporal Sparsity in Deep Neural Networks for Time-Series Data

Bachelor students:

  1. Emiel de Vries (2026): LLM-assisted RTL generation for a pretrained deep neural network
  2. Bas Reterink (2025): Person detection using an event-based camera on STM32
  3. Pierluigi Gatt(2025): Person detection using an event-based camera on STM32
  4. Mattijn Spitteler(2025): Improving the analogue section of IO extenders for a hydraulic cylinder controller

Visiting students:

  1. Mohamed Saber (MSc, 2026): Nano LLMs mapping for neuromorphic systems
  2. Harinandanan Ajith Maya (BSc, 2026): ChipLet-based neuromorphic processing platform
  3. Omar Mansour (MSc, 2025): NERVE: A Neuromorphic Vision and Radar Ensemble for Multi-Sensor Fusion Research (FAIR Data Fund project)
  4. Ege Tan (BSc, 2025): neuromorphic processor external communication 
  5. Ethan Milon(MSc, 2024): Radar processing for smart office applications
  6. Mustafa Canitz(BSc, 2024): Event-based camera processing for smart office applications
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