Chang Gao

Position:	Postdoc -- ended Jul 2022
Email:	chang@ini.uzh.ch
Work phone:
Home page:	https://www.tudemi.com

My name is Chang Gao (高唱), and I am currently an Assistant Professor at the Department of Microelectronics, TU Delft, Netherland from August 2022.

I joined INI in 2017 as a Ph.D. student and started my postdoc in Jan 2022. My advisors are Prof. Dr. Shih-Chii Liu and Prof. Dr. Tobi Delbruck. My Ph.D. thesis was on designing energy-efficient accelerators of recurrent neural networks (RNNs) for real-time inference.

Major Works during my Ph.D.:
- The DeltaRNN accelerator (FPGA 2018)
- A spoken digit recognition system using DeltaRNN and the spiking cochlea (ISCAS 2019)
- The EdgeDRNN accelerator (AICAS 2020 & IEEE JETCAS, Best Paper Award)
- A real-time end-to-end robotic control system using EdgeDRNN (ICRA 2020)
- An ultra-low-power real-time keyword spotting chip (ISSCC 2022)
- The Spartus accelerator (IEEE TNNLS)

Supervisor

Tobi Delbruck

Publications

2024

Xi Chen, Chang Gao, Zuowen Wang, Longbiao Cheng, Sheng Zhou, Shih-Chii Liu, Tobi Delbruck Exploiting Symmetric Temporally Sparse BPTT for Efficient RNN Training, The AAAI Conference on Artificial Intelligence (AAAI), 2024

2023

Qinyu Chen, Zuowen Wang, Shih-Chii Liu, Chang Gao 3ET: Efficient Event-based Eye Tracking using a Change-Based ConvLSTM Network, 2023 IEEE Biomedical Circuits and Systems Conference (BioCAS), 2023 pdf
Xi Chen, Chang Gao, Zuowen Wang, Longbiao Cheng, Sheng Zhou, Shih-Chii Liu, Tobi Delbruck Exploiting symmetric temporally sparse BPTT for efficient RNN training, Advances in Neural Information Processing Systems (NeurIPS) 2023 Workshop, 2023

2022

Chang Gao, Tobi Delbruck, Shih-Chii Liu Spartus: A 9.4 TOp/s FPGA-based LSTM Accelerator Exploiting Spatio-temporal Sparsity, IEEE Transactions on Neural Networks and Learning Systems, 2022
Ilya Kiselev, Chang Gao, Shih-Chii Liu Spiking Cochlea with System-level Local Automatic Gain Control, IEEE Transactions on Circuits and Systems I - Regular Papers, 2022
Johanna Hedlund Lindmar, Chang Gao, Shih-Chii Liu Intrinsic Sparse LSTM using Structured Targeted Dropout for Efficient Hardware Inference, 2022 IEEE 4th International Conference on Artificial Intelligence Circuits and Systems (AICAS), 2022
Kwantae Kim*, Chang Gao*, Rui Graça, Ilya Kiselev, Hoi-Jun Yoo, Tobi Delbruck, Shih-Chii Liu A 23μW Solar-Powered Keyword Spotting ASIC with Ring-Oscillator-Based Time-Domain Feature Extraction, IEEE International Solid-State Circuit Conference (ISSCC), 2022
Kwantae Kim, Chang Gao, Rui Graça, Ilya Kiselev, Hoi-Jun Yoo, Tobi Delbruck, Shih-Chii Liu A 23-μW Keyword Spotting IC with Ring-Oscillator-Based Time-Domain Feature Extraction, IEEE Journal of Solid-State Circuits (JSSC), 2022
Liu, S-C., Gao, C., Kim, K., and Delbruck, T. Energy-efficient activity-driven computing architectures for edge intelligence, 2022 IEEE International Electron Devices Meeting (IEDM), 2022
Qinyu Chen*, Chang Gao*, Xinyuan Fang, Haitao Luan Skydiver: A Spiking Neural Network Accelerator Exploiting Spatio-Temporal Workload Balance, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, 2022
Qinyu Chen, Congyi Sun, Zhonghai Lu, Chang Gao Enabling Energy-Efficient Inference for Self-Attention Mechanisms in Neural Networks, 2022 IEEE 4th International Conference on Artificial Intelligence Circuits and Systems (AICAS), 2022

2021

Xi Chen, Chang Gao, Tobi Delbruck, Shih-Chii Liu EILE: Efficient Incremental Learning on the Edge, The International Conference on Artificial Intelligence Circuits and Systems (AICAS), 2021

2020

Gao, C*, Gehlhar, R.*, Ames, A., Liu, S-C., Delbruck, T., Recurrent Neural Network Control of a Hybrid Dynamic Transfemoral Prosthesis with EdgeDRNN Accelerator, the 2020 International Conference on Robotics and Automation (ICRA), 2020
Gao, C., Rios-Navarro, A., Chen, X., Delbruck, T., Liu, S-C., EdgeDRNN: Recurrent Neural Network Accelerator for Edge Inference, IEEE Journal on Emerging and Selected Topics in Circuits and Systems , 2020
Gao, C., Rios-Navarro, A., Chen, X., Delbruck, T., Liu, S-C., EdgeDRNN: Enabling Low-latency Recurrent Neural Network Edge Inference, 2020 IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS), 2020

2019

Gao, C., Braun, S., Kiselev, I., Anumula, J., Delbruck, T., Liu, S-C. Real-Time Speech Recognition for IoT Purpose Using a Delta Recurrent Neural Network Accelerator, 2019 IEEE International Symposium on Circuits and Systems (ISCAS), 2019
Gao, C., Braun, S., Kiselev, I., Anumula, J., Delbruck, T., Liu, S-C. Live Demonstration: Real-Time Spoken Digit Recognition Using the DeltaRNN Accelerator, 2019 IEEE International Symposium on Circuits and Systems (ISCAS), 2019

2018

Gao, C., Neil, D., Ceolini, E., Liu, S-C., Delbruck, T. DeltaRNN: A Power-efficient Recurrent Neural Network Accelerator, Proceedings of the 2018 ACM/SIGDA International Symposium on Field-Programmable Gate Arrays (FPGA 2018) 21-30, 2018

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