dr. C Gao
Electronic Circuits and Architectures (ELCA), Department of Microelectronics
Expertise: Digital Circuit Design, AI Hardware, Neuromorphic Computing, Artificial Intelligence
Themes: RF electronicsBiography
Dr. Chang Gao is an assistant professor at the Department of Microelectronics, TU Delft, where he leads the Lab of Efficient circuits & systems for Machine Intelligence (EMI). He obtained his PhD with distinction from the Institute of Neuroinformatics, University of Zurich and ETH Zurich.
His research focuses on designing energy-efficient digital AI hardware for edge computing, emphasizing wireless communication, video/audio processing, and healthcare applications. He applies brain-inspired neuromorphic principles to bridge the gap between artificial neural networks (ANNs) and spiking neural networks (SNNs), achieving massive acceleration and competitive accuracy on real-world tasks. He has published in journals including TNNLS, JSSC, JETCAS, TCAS-I, TVLSI, etc., and conferences including FPGA, ISSCC, IEDM, ISCAS, AICAS, ICRA, AAAI, etc., and received the Best Paper Award at the 2020 IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS).
He is a co-recipient of the 2020 Misha Mahowald Prize for Neuromorphic Engineering and the 2022 Mahowald Early Career Award in Neuromorphic Engineering. He recently secured the 2022 Marie Skłodowska-Curie Postdoctoral Fellowship and was named a 2023 MIT Technology Review Innovator Under 35.
Links:
Courses
EE4C13 Wireless systems for electrical engineering applications
Commonly used RF electronics architectures in wireless systems, with the requirements on their building blocks.
Last updated: 9 Apr 2024
Chang Gao
- Chang.Gao@tudelft.nl
- Room: HB 19.280
- Personal webpage
- Google Scholar profile
- Download CV
MSc students
MSc project proposals
- [2024] An FPGA Accelerator of OpenAI Whisper Speech Recognizer
- [2024] A Real-Time Neural Audio Denoising Chip
- [2024] AI4RF: Artificial Intelligence for 6G RF Signal Processing
- [2024] Digital VLSI Accelerator for Ultra-Low-Latency Event-Driven Eye-Tracking
- [2024] OpenWiFi-DPD: An Open-Source Digital Pre-distortion In-the-loop Wi-Fi Demonstrator