Asal Kiazadeh
Professor of Nanoelectronics, Memristive Devices and Neuromorphic Systems
CENIMAT | i3N and CEMOP-UNINOVA, Faculdade de Ciências e Tecnologia Universidade NOVA de Lisboa Campus de Caparica, 2829-516 Caparica, Portugal (email)
CENIMAT | i3N and CEMOP-UNINOVA, Faculdade de Ciências e Tecnologia Universidade NOVA de Lisboa Campus de Caparica, 2829-516 Caparica, Portugal (email)
Asal Kiazadeh received her PhD degree with highest distinction in Electronics and Optoelectronics from the University of Algarve in December 2013, within a collaborative project with Philips Research Laboratories. Her doctoral research focused on resistive switching memories based on nanoparticles.
She is currently an Assistant Professor at NOVA University of Lisbon (NOVA FCT) and a Senior Researcher of Distinction at i3N/CENIMAT, a position awarded through the highly competitive CEEC individual call. She is also Team Leader of the research group “Resistive Switching Technologies for Neuromorphic and RF Solutions” at CENIMAT | i3N.
Her research focuses on the electrical properties of flexible amorphous oxide materials for memristors and thin-film transistors, covering device physics, circuit integration, and system-level architectures for IoT, neuromorphic computing, and RF/THz applications.
She actively supervises MSc and PhD students and leads an independent research team. She is Principal Investigator (PI) of several national and European-funded research projects, and regularly coordinates multidisciplinary collaborations with academic and industrial partners.
In education, she developed and coordinates a Master-level course entitled “Recording Electronic Information”, offered to students in Micro- and Nanotechnology, Material engineering, Electronics, and Informatics (IT) and Physics. The course provides a comprehensive overview of modern memory and computing technologies, from materials and device physics to circuit-level design.
Memristive devices and resistive switching technologies (RRAM)
Amorphous oxide semiconductors and thin-film transistors (TFTs)
Neuromorphic computing hardware and in-memory computing
Physical Reservoir computing and bio-inspired systems
RF and THz memristor-based devices and switches
Printed, flexible, and sustainable electronics
Hardware platforms for edge AI and IoT systems
(Last updated: January 30, 2026)