A. Yousefzadeh PhD (Amirreza)

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:

• Ph.D. in neuromorphic engineering at IMSE, Thesis: Digital Design For Neuromorphic Bio-Inspired Vision Processing
• 2018-2020 (Netherlands): In the GrAI Matter Labs startup, later acquired by Snap, I mainly worked on the architecture of the NeuronFlow processor
• 2020-2024 (Netherlands): In imec, at the Hardware Efficient AI group, I mainly worked on the architecture of the SENECA processor
• 2024-Present: Assitant professor, Computer Architecture for Embedded Systems

Expertise

• Computer Science

  • Neural Network
  • Synaptic Weight
  • Computer Hardware
  • Design-Space Exploration
  • Hardware Accelerator
  • Memory Footprint
  • Hardware Structure
  • Convolutional Neural Network

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

Publications

Research profiles

Affiliated study programs

Courses academic year 2024/2025

Courses in the current academic year are added at the moment they are finalised in the Osiris system. Therefore it is possible that the list is not yet complete for the whole academic year.

Courses academic year 2023/2024

Funded projects: 

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

PhD Students: 

1. Sameed Sohail: Embedded Neuromorphic Processor Architecture with On-Device Adaptation

Master students: 

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

Bachelor students:

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

Navigate to location

Organisations