Zilverling

A. Yousefzadeh PhD (Amir)

Assistant Professor
EEMCS-CS-CAES
Zilverling 5039
a.yousefzadeh@utwente.nl
+31534897988
Business card

I joined the University of Twente in February 2024 as an Assistant Professor in edge AI. My focus is on designing embedded AI and neuromorphic systems. 


Brief CV:

Expertise

  • Computer Science

    • Computer Hardware
    • Neural Network
    • Artificial Intelligence
    • Energy Efficient
    • Electronic Learning
    • Edge AI
    • Multicore

  • Engineering

    • Internet-Of-Things

Organisations

Research experiences:

  • Neuromorphic Sensing and processing
  • Embedded AI

I extensively use digital hardware design tools and gate-level simulations to co-optimize hardware architectures with neural network algorithms. Some of my technical experiences:

  • Design of programmable neuromorphic processors for embedded AI applications
  • On-device learning algorithms and hardware accelerators
  • Bio-inspired vision processing
  • Benchmarking and comparison of various algorithm optimizations in hardware

Looking for PhD or Postdoc positions: please check the UTwente career website. All the positions are advertised there, and applications should be submitted online. Please avoid sending your application via email.

Looking for master thesis or internship: Please send me an email with your CV and grades (both bachelor and master).

Publications

2025

Efficient 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

2024

EON-1: A Brain-Inspired Processor for Near-Sensor Extreme Edge Online Feature Extraction (2024)IEEE Transactions on Circuits and Systems for Artificial Intelligence, 1(2), 128-140. Article 10744412. Dobrita, A., Yousefzadeh, A., Thorpe, S., Vadivel, K., Detterer, P., Tang, G., Schaik, G.-J. v., Konijnenburg, M., Gebregiorgis, A., Hamdioui, S. & Sifalakis, M.https://doi.org/10.1109/TCASAI.2024.3491673Energy-efficient SNN Architecture using 3nm FinFET Multiport SRAM-based CIM with Online Learning (2024)In Proceedings of the 61st ACM/IEEE Design Automation Conference, DAC 2024 (pp. 1-6). Article 260 (Proceedings - Design Automation Conference). IEEE. Huijbregts, L., Liu, H. H., Detterer, P., Hamdioui, S., Yousefzadeh, A. & Bishnoi, R.https://doi.org/10.1145/3649329.3656514Invited: Neuromorphic Vision Modalities in the NimbleAI 3D Chip (2024)In Proceedings of the 61st ACM/IEEE Design Automation Conference, DAC 2024 (pp. 1-4). Article 358 (Proceedings - Design Automation Conference). IEEE. Iturbe, X., Linares-Barranco, B., Ieng, S. H., Erdmann, A., Peres, L., Rhodes, O., Tornero, R., Sifalakis, M., Van De Burgwal, M., Yousefzadeh, A., Kooli, M., Alidori, R. & Zaykov, P.https://doi.org/10.1145/3649329.3689622Multidie 3-D Stacking of Memory Dominated Neuromorphic Architectures (2024)IEEE transactions on very large scale integration (VLSI) systems, 32(11), 2144-2148. Giacomini Rocha, L. M., Bilgic, R., Naeim, M., Das, S., Oprins, H., Yousefzadeh, A., Konijnenburg, M., Milojevic, D., Myers, J., Ryckaert, J. & Biswas, D.https://doi.org/10.1109/TVLSI.2024.3421625Overcoming the Limitations of Layer Synchronization in Spiking Neural Networks (2024)[Working paper › Preprint]. ArXiv.org. Koopman, R., Yousefzadeh, A., Shahsavari, M., Tang, G. & Sifalakis, M.https://doi.org/10.48550/arXiv.2408.05098Event-based Optical Flow on Neuromorphic Processor: ANN vs. SNN Comparison based on Activation Sparsification (2024)[Working paper › Preprint]. ArXiv.org. Xu, Y., Tang, G., Yousefzadeh, A., de Croon, G. C. H. E. & Sifalakis, M.https://doi.org/10.48550/arXiv.2407.20421Co-optimized training of models with synaptic delays for digital neuromorphic accelerators (2024)In ISCAS 2024 - IEEE International Symposium on Circuits and Systems (Proceedings - IEEE International Symposium on Circuits and Systems). IEEE. Patiño-Saucedo, A., Meijer, R., Detteter, P., Yousefzadeh, A., Garrido-Regife, L., Linares-Barranco, B. & Sifalakis, M.https://doi.org/10.1109/ISCAS58744.2024.10558209Eon-1: A Brain-Inspired Processor for Near-Sensor Extreme Edge Online Feature Extraction (2024)[Working paper › Preprint]. ArXiv.org. Dobrita, A., Yousefzadeh, A., Thorpe, S., Vadivel, K., Detterer, P., Tang, G., van Schaik, G.-J., Konijnenburg, M., Gebregiorgis, A., Hamdioui, S. & Sifalakis, M.https://doi.org/10.48550/arXiv.2406.17285Trip: Trainable Region-of-Interest Prediction for Hardware-Efficient Neuromorphic Processing on Event-based Vision (2024)[Working paper › Preprint]. ArXiv.org. Arjmand, C., Xu, Y., Shidqi, K., Dobrita, A. F., Vadivel, K., Detterer, P., Sifalakis, M., Yousefzadeh, A. & Tang, G.https://doi.org/10.48550/arXiv.2406.17483

Research profiles

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: Embedded Neuromorphic Processor Architecture with On-Device Adaptation

Master students: 

  1. Bram Bremer: Real-time acoustic imaging on an FPGA using recurrent neural networks
  2. Arjan Blankestijn: Accelerating Transformers on ZynQ platforms
  3. Sharon Moolenaar: Optimizing Network on chip for neuromorphic processors
  4. Mattias Westerink: Designing co-processor for RISC-V-based neuromorphic system
  5. Wiebren Wijnstra: Optimizing RISC-V processor for neuromorphic workloads
  6. Wim Nijsink: Measuring the reliability of existing neuromorphic solutions
  7. Haoran Wolfgang: Low latency hardware accelerator for sparse convolutional recurrent network toward neuromorphic object detection
  8. Ivan Knunyants: Optimizing transformer neural networks for event-driven inference in hardware
  9. Yashwanth Gopinath: Open-source RISC-V-based neuromorphic processor
  10. Roel Koopman (2024): Overcoming the Limitations of Layer Synchronization in Spiking Neural Networks
  11. Cina Arjmand (2023): Trainable Region of Interest Prediction: Hard Attention Framework for Hardware-Efficient Event-Based Computer Vision Neural Networks on Neuromorphic Processors  
  12. Lucas Huijbregts (2023): Transposable Multiport SRAM-based In-Memory Compute Engine for Binary Spiking Neural Networks in 3nm FinFET
  13. Shenqi Wang (2023): Hardware Efficient Object Detection for High Spatial Resolution Event Camera
  14. Refik Can Bilgiç (2023):  Analytical Modelling of 3D System Partitioning
  15. Pietro Martinello (2023): Forging a Multimodal Dataset: Uniting Diverse Sensor Data for Enhanced Analysis
  16. Roy Meijer (2023): Efficient Synaptic Delay Implementation in Digital Event-Driven Neuromorphic Processors
  17. Kevin Shidqi (2022): Benchmarking and Algorithm Optimization for SENeCA, a RISC-V-based Neuromorphic Processor
  18. Alexandra-Florentina Dobrit (2022): Brain-inspired feature extraction for near sensor extreme edge processing with Spiking Neural Networks
  19. Prithvish Vijaykumar Nembhani (2022): Efficient mapping of large-scale SNN and rate-based DNN on SENeCA
  20. Preetha Vijayan (2021): Temporal Delta Layer: Exploiting Temporal Sparsity in Deep Neural Networks for Time-Series Data

Bachelor students:

  1. Mattijn Spitteler: Universal Software-Configurable Extender for Hydraulic Cylinder Controllers

Visiting students:

  1. Ethan Milon: Radar processing for smart office applications
  2. Mustafa Canitz: Event-based camera processing for smart office applications
  3. YingFu Xu (2022):  Implementation of bio-inspired Optimical flow algorithm in neuromorphic processor
  4. Alberto Patino-Saucedo (2022): Hardware-aware training of models with synaptic delays for digital event-driven neuromorphic processors

Address

University of Twente

Zilverling (building no. 11), room 5039
Hallenweg 19
7522 NH Enschede
Netherlands

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