Chad Yang

Hey, thanks for stopping by! 👋 I’m from Taiwan and I’m currently a PostDoc in University of Tübingen, Germany (MHM-Lab, PI: Thomas Wolfers).

My interests lie broadly at the intersection of developing robust and reliable ML techniques, including Large-scale Self-Supervised Learning, Adversarial Attacks/Privacy, and Continuous Learning methods. I specialize in developing ML models from Multi-Modality signals, such as Electrical Physiologies (ECG/EDA/EEG), Medical Images (MRI), and Speech Processing. Before joining the MHM-Lab, I received my PhD in Electrical Engineering from National Tsing Hua University, Taiwan supervised by Prof. Chi-Chun, Lee.

News

Mar 1, 2023	After three months of making friends with the immigration office, I have finally embarked on my postdoc journey in Tübingen! Guten Tag! 🍺
Oct 15, 2022	Completed military service. I’m happy to have gained a some weight 🪖
Apr 7, 2022	👨‍🎓 Survived from thesis defense “Physiological-based Affective Computing using Personality Invariant Learning”
Sep 5, 2021	🎉 Best Challenge Poster in 2021 PhysioNet/CinC Challenge (with InventecAI, preprint).
Jul 16, 2021	1 paper accepted for robust Federated Learning in Multi-Site Alzheimer in EMBC 2021.

Selected publications

TAFFC

A Media-Guided Attentive Graphical Network for Personality Recognition Using Physiology

*Hao-Chun Yang, and Chi-Chun Lee

IEEE Transactions on Affective Computing, 2021

Bib HTML PDF

@article{yang-personality/taffc,
  author = {Yang, Hao-Chun and Lee, Chi-Chun},
  journal = {IEEE Transactions on Affective Computing},
  title = {A Media-Guided Attentive Graphical Network for Personality Recognition Using Physiology},
  year = {2021},
  volume = {},
  number = {},
  pages = {1-1},
  doi = {10.1109/TAFFC.2021.3090040},
  booktitle = {IEEE Transactions on Affective Computing},
}

CINC

A Mixed-Domain Self-Attention Network for Multilabel Cardiac Irregularity Classification Using Reduced-Lead Electrocardiogram

*Hao-Chun Yang, Wan-Ting Hsieh, and Pei-Chun Chen

In Computing in Cardiology, CinC 2020, Brno, Czech Republic, September 12-15, 2021

Bib HTML PDF Poster Patent

@inproceedings{DBLP:conf/cinc/Yaang21,
  author = {Yang, Hao-Chun and Hsieh, Wan{-}Ting and Chen, Pei{-}Chun},
  title = {A Mixed-Domain Self-Attention Network for Multilabel Cardiac Irregularity Classification Using Reduced-Lead Electrocardiogram},
  booktitle = {Computing in Cardiology, CinC 2020, Brno, Czech Republic, September 12-15},
  pages = {x--x},
  publisher = {{IEEE}},
  year = {2021},
}

EMBC

Federated Learning via Conditioned Mutual Learning for Alzheimer Disease Classification on T1w MRI

Ya-Lin Huang, *Hao-Chun Yang, and Chi-Chun Lee

In 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, EMBC 2021, (Virtual), Nov 1-5, 2021, 2021

Bib HTML PDF

@inproceedings{DBLP:conf/embc/Yalin21,
  author = {Huang, Ya{-}Lin and Yang, Hao-Chun and Lee, Chi{-}Chun},
  title = {Federated Learning via Conditioned Mutual Learning for Alzheimer Disease Classification on T1w MRI},
  booktitle = {43rd Annual International Conference of the {IEEE} Engineering in
                 Medicine {\&} Biology Society, {EMBC} 2021, (Virtual),
                 Nov 1-5, 2021},
  pages = {2427-2432},
  doi = {10.1109/EMBC46164.2021.9630382},
  pmid = {34891771},
  publisher = {{IEEE}},
  year = {2021},
}

ACMMM

Cross Corpus Physiological-based Emotion Recognition Using a Learnable Visual Semantic Graph Convolutional Network

Woan-Shiuan Chien, *Hao-Chun Yang, and Chi-Chun Lee

In MM ’20: The 28th ACM International Conference on Multimedia, ACMMM 2020, Virtual Event / Seattle, WA, USA, October 12-16, 2020, 2020

Bib HTML PDF

@inproceedings{DBLP:conf/mm/ChienYL20,
  author = {Chien, Woan-Shiuan and Yang, Hao-Chun and Lee, Chi-Chun},
  editor = {Chen, Chang Wen and Cucchiara, Rita and Hua, Xian-Sheng and Qi, Guo-Jun and Ricci, Elisa and Zhang, Zhengyou and Zimmermann, Roger},
  title = {Cross Corpus Physiological-based Emotion Recognition Using a Learnable
                 Visual Semantic Graph Convolutional Network},
  booktitle = {{MM} '20: The 28th {ACM} International Conference on Multimedia, {ACMMM} 2020, Virtual
                 Event / Seattle, WA, USA, October 12-16, 2020},
  pages = {2999--3006},
  publisher = {{ACM}},
  year = {2020},
  url = {https://doi.org/10.1145/3394171.3413552},
  doi = {10.1145/3394171.3413552},
}