My notes
Security Challenges in Analog In-Memory Computing
How ADC power leakage can expose weights stored in analog in-memory-computing accelerators, and what that means for secure edge AI.
From Power Traces to Model Weights: P2W and TraceFormer
Two research methods for learning about embedded neural-network weights through physical power side channels.
Reinforcement Learning for Reliable Real-Time Fog Systems
How ReLIEF assigns primary and backup tasks while balancing deadlines, failures, communication delay, and fog-node workload.
Phase-Change Memory for Analog In-Memory Computing
A practical introduction to PCM conductance, neural-network acceleration, engineering trade-offs, and physical security.
My Journey from Bushehr to Leiden
Reflections on my academic path from Bushehr to the Netherlands.