Electronic Instrumentation (EI), Department of Microelectronics
Expertise: Digital IC design, neuromorphic engineering and spiking neural networks, neuroscience-inspired machine learning, hardware-algorithm co-design.Themes: Cognitive sensor nodes and systems
Charlotte Frenkel received the M.Sc. degree (summa cum laude) in Electromechanical Engineering and the Ph.D. degree in Engineering Science from Université catholique de Louvain (UCLouvain), Louvain-la-Neuve, Belgium, in 2015 and 2020, respectively. In February 2020, she joined the Institute of Neuroinformatics, University of Zurich and ETH Zurich, Switzerland, as a postdoctoral researcher. In July 2022, she started as an assistant professor in the Electronic Instrumentation group at Delft University of Technology.
Her current research aims at bridging the bottom-up (bio-inspired) and top-down (engineering-driven) design approaches toward neuromorphic intelligence, with a focus on digital and mixed-signal spiking neural network processor design, embedded machine learning, and on-chip training algorithms. Direct applications cover adaptive internet of things (IoT) devices, autonomous robotic agents, and wearables for biosignal processing.
Dr. Frenkel received a best paper award at the IEEE International Symposium on Circuits and Systems (ISCAS) 2020 conference and her Ph.D. thesis was awarded the Nokia Bell Labs Scientific Award 2021, the IBM Innovation Award 2021 and the UCLouvain/ICTEAM Best Thesis Award 2021. In 2023, she received the prestigious AiNed Fellowship and Veni grants from the Dutch Research Council (NWO). She is an Associate Editor for the IEEE Transactions on Biomedical Circuits and Systems journal, is the chair of the tinyML initiative on neuromorphic engineering, serves as a program co-chair for the tinyML Research Symposium 2024, as a program co-chair for the Neuro-Inspired Computational Elements (NICE) neuromorphic conference since 2023, as a TPC member for the IEEE European Solid-State Circuits Conference (ESSCIRC) since 2022, as a member of the neuromorphic systems and architecture technical committee of the IEEE CAS society since 2021, and as a reviewer for various conferences and journals, including the IEEE JSSC, IEEE TNNLS, IEEE TCAS I/II, Nature, Nature Electronics, and Nature Machine Intelligence. She presented several invited talks, including keynotes at the tinyML EMEA technical forum 2021, at the NICE neuromorphic conference 2021, and at Neuromorphic Computing Netherlands (NCN) 2022.
Prospective self-motivated BSc/MSc/PhD students are always welcome to send an e-mail to discuss research opportunities in my lab, both for their main academic curriculum and for open curiosity-driven side projects.
For more information on the CogSys research team, please follow this link.
ET4351 Digital VLSI Systems on Chip
How to design, connect and implement large macro IP blocks that constitutes a system on chip
Last updated: 6 Dec 2023