Chao-Han Huck Yang received his Ph.D. degree in the school of electrical and computer engineering at the Georgia Institute of Technology, Atlanta, GA, USA.

He received a B.S. degree from National Taiwan University, Taipei, Taiwan, in 2016. His recent research interests focus on data privacy and robustness on speech processing, robust reinforcement learning, variational causal inference, and language modeling.

His PhD advisor at Georgia Tech is Prof. Chin-Hui Lee (ISCA Fellow and IEEE Fellow).

Academic Service

  • Technical Program Commettie and Chair for Special Session: ICASSP 2022

  • Conference Reviewer: NeurIPS (2020-22), AAAI (2020-22), ICASSP (2019-22), CVPR 2020-21, KDD 2020, MICCAI (2019-22), AISTATS 2021

ICCV 2019, ICDM (2019-21), IEEE Big Data 2019, IEEE GlobalSIP 2019 … more

  • Journal Reviewer: Neurocomputing (since 2018), IEEE Trans. Audio, Speech, and Language Proc. (since 2020), IEEE Signal Proc. Letter (since 2020)

Bio

CHH Yang was a student member of IEEE Society and the recipient of the Wallace H. Coulter Fellowship from Georgia Institute of Technology in 2017-18 advised by Prof. Chin-Hui Lee. He received NeurIPS Outstanding reviewer award 2021, NSF travel grant for ICASSP 2020, Xanadu Quantum AI Competition Research Track, 1st Place Award 2019, and DeepMind travel award for NeurIPS 2019. He joined Amazon Alexa Team as an applied scientist II intern in 2020 and 2021 with Dr. Ivan Bulyko and Dr. Andreas Stolcke for language modeling. He worked with Prof. Xiaoli Ma on research projects related to reinforcement learning in 2018 to 2019.

In 2018, he took a research intern on deep video processing at the Image and Visual Representation Lab (IVRL), Ecole Polytechnique Federale de Lausanne (EPFL), Switzerland. He was participating in the EPFL summer research intern fellowship program and worked with Prof. Sabine Susstrank and Dr. Sami Arpa on intelligent movie processing for violence detection.

Between 2017 and 2018, he has visited KAUST twice at Prof. Jesper Tegner’s group and started the causality of the complex network and deep EyeNet project.

In 2017, he worked as a research intern with the design and innovation platform (DIP) at Taiwan Semiconductor Manufacturing Company (TSMC) for reinforcement learning and dynamic programming. He took peace and historical study at Hiroshima University in 2017. During his undergraduate, he worked on designing wearable device with strain-sensor (IEEE Transducer 2017).

Huck was a visiting student for numerical optimization on wearable electronics at NC State University, NC, and took a summer program at Utrecht on nanomaterial in 2016. He was working on nanoscale and microscale numerical simulation for fabrication during his B.S. study at NTU from 2013 to 2016.

Honors & Selected Awards

  • CSIP Outstanding Service Award, 2022 Spring
  • AAAI Travel Grant, 2022
  • NeurIPS Outstanding Reviewer Award (top 8%), 2021
  • ICML Travel Grant, 2021
  • Judges’ Award, Audio-Visual Classification, DCASE 2021
  • 2nd Place, Low-Complexity Device-Robust Acoustic Scene Classification, DCASE 2021
  • 2nd Place, Audio-Visual Acoustic Scene Classification, DCASE 2021
  • Best Reproducible System, Acoustic Modeling, DCASE 2020
  • 2nd Place, Low-Complexity Acoustic Scene Classification, DCASE 2020
  • 2nd Place, Device-Robust Acoustic Scene Classification, DCASE 2020
  • NSF ICASSP Travel Grant, 2020
  • DeepMind NeurIPS Robot Learning Travel Grant, 2019
  • IEEE SPS Student ICIP Travel Grant, 2019
  • Xanadu AI Quantum ML Research 1st Award, 2019
  • EFPL Summer Research Intern Fellowship, 2018
  • KAUST Visiting Student Research Program, 2017
  • Wallace H. Coulter Fellowship, Georgia Tech ECE, 2017

Open Source

huckiyang's github stats