CV
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Contact Information
| Name | M Ihsan Al Hafiz |
| Professional Title | PhD Student in Neuromorphic Accelerators |
| miahafiz@kth.se | |
| Phone | +46 76 156 86 96 |
| Location | Kungshamra 42B, Stockholm, |
| Website | https://ihsanalhafiz.github.io |
Experience
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Aug 2023 - Mar 2024 Stockholm, Sweden
Software Engineer
Atlas Copco
- Supported current MicroTorque tools and developed peripheral tests, mostly using C programming for microcontrollers.
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Jan 2018 - Aug 2021 Jakarta, Indonesia
Electronics Engineer
BPPT - Agency of Assessment and Application Technology
- Developed electronics systems and programmed microcontrollers with C and C++ to support Indonesia Tsunami Early Warning Systems.
Research and Project Experiences
- (EU-Project) Explainable Trustworthy AI for Data Intensive Applications (EXTRA-BRAIN), KTH Royal Institute of Technology (PhD), Stockholm. Apr 2024 - Present. The project is part of my PhD project; I am developing a neuromorphic hardware accelerator and implementing it in an FPGA.
- Visual-Inertial Localization implementation on FPGA, Atlas Copco & KTH Royal Institute of Technology (Master thesis), Stockholm. Jan 2023 - Jun 2023. Developed a Kalman Filter IP core and implemented it together with an AI model using a Deep-Learning Processor Unit IP core. Utilized Vitis AI to compile the AI model and implemented it in a Zynq UltraScale+ MPSoC FPGA.
Education
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Apr 2024 - Present Sweden
PhD
KTH Royal Institute of Technology
Neuromorphic Accelerator
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Sep 2021 - Sep 2023 Sweden
M.Sc
KTH Royal Institute of Technology
Embedded Systems
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Sep 2013 - Jun 2017 Indonesia
B.Eng
Universitas Gadjah Mada
Engineering Physics
- CGPA: 3.57/4.0
Publications
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2025 A Reconfigurable Stream-Based FPGA Accelerator for Bayesian Confidence Propagation Neural Networks
Applied Reconfigurable Computing. Architectures, Tools, and Applications. ARC 2025. Lecture Notes in Computer Science, vol 15594. Springer.
Authors: Muhammad Ihsan Al Hafiz, Naresh Ravichandran, Anders Lansner, Pawel Herman, and Artur Podobas.
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2025 Embedded FPGA Acceleration of Brain-Like Neural Networks: Online Learning to Scalable Inference
Preprint; accepted for oral presentation at the 18th IEEE MCSoC 2025.
Authors: Muhammad Ihsan Al Hafiz, Naresh Ravichandran, Anders Lansner, Pawel Herman, and Artur Podobas.
Skills
Hardware and Embedded: FPGA, Microcontroller, VHDL, GPU, Electronics Design
Programming and Systems: C/C++, Python, Linux
Software: Vivado Design Suite, Vitis HLS, CUDA, Matlab & Simulink
Honors and Awards
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Aug 2021 Satyalancana Wira Karya
The President of the Republic of Indonesia
Medal for Providing an Example of Meritorious Personality, issued for involvement in the Indonesia Tsunami Early Warning Systems project.
References
- Artur Podobas
Assoc. Professor at KTH Royal Institute of Technology (First Supervisor). Email: Podobas@kth.se.
- Pawel Herman
Professor at KTH Royal Institute of Technology (Second Supervisor). Email: paherman@kth.se.