Aida Todri-Sanial
Department / Institute
RESEARCH PROFILE
Aida Todri-Sanial is a Full Professor in the Integrated Circuits group of the Electrical Engineering department at Eindhoven University of Technology (TU/e). Her core expertise is in physical design, design space exploration and optimization methods for the design of energy-efficient circuits and computing architectures. Todri-Sanial develops physical models and physical design methods to investigate novel computing paradigms such as 3D integration, neuromorphic computing and quantum computing.
In 2016, she was awarded the CNRS bronze medal, in 2018 the Franco-British Young Leader, in 2020 the ACM SIGDA Meritorious award, in 2021 IBM Quantum Open Science prize, in 2022 Distinguished Lecturer of IEEE Nanotechnology Council. She is an editorial board member of the IEEE VLSI journal.
Entwining physics and electronics, I explore and design unconventional computational architectures that can transcend computing to an open, interactive and evolving system that can solve a diverse range of problems.
ACADEMIC BACKGROUND
Aida Todri-Sanial received a PhD in Electrical and Computer Engineering at the University of California Santa Barbara in 2009. In 2009 and 2010, she worked at the Fermi National Accelerator Laboratory as a Bardeen Fellow in Computing Division. Since 2011, she has been a scientist and research director at CNRS, working at the LIRMM laboratory. She was a visiting fellow at the Cambridge Graphene Center and Wolfson College at the University of Cambridge, UK, during 2016-2017. She has also held visiting research positions at Mentor Graphics, Cadence Design Systems, STMicroelectronics and IBM TJ Watson Research Center.
Recent Publications
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Non-volatile resistive switching mechanism in single-layer MoS2 memristors
Nanoscale Advances (2023) -
Supported Pt Nanoclusters on Single-Layer MoS2 for the Detection of Cortisol
ACS Applied Electronic Materials (2023) -
Oscillatory neural network learning for pattern recognition
Frontiers in Neuroscience (2023) -
SIFT-ONN
(2023) -
Building Oscillatory Neural Networks
(2023)
Current Educational Activities
Ancillary Activities
No ancillary activities