Hao-Chun (Chad) Yang

Ph.D Candidate

Ph.D. Candidate (EE) @NTHU | Machine Learning Research Scientist | Affective Computing, Health Informatics, Computational Neuroscience | pytorch, tensorflow

  Room 315, General Building III, No. 101, Section 2, Kuang-Fu Road, 30013 Hsinchu City, Taiwan

       

Skills

Programming


  • ML&DL: sklearn, pytorch, tensorflow
  • CI/CD: git, Docker
  • Platform: Linux, AWS, GCP

Special Honors


  • 2021 - Best Challenge Poster - Physionet/CINC Challenge
  • 2019 - Travel Grants - IEEE SPS Society
  • 2017 - President Scholarship - NTHU

Education


  • National Tsing Hua University
    Ph.D. in Electrical Engineering
    (Sep. 2016 - Present)
  • National Tsing Hua University
    B.S. in Electrical Engineering
    (Sep. 2012 - July 2016)

Research Projects

Sep 2018 - Present

Affective Physiological Responses under Multimedia Stimuli

- Improve physiological emotion recognition by 3.5% UAR using Transformer-based User-Centered modeling.
- Improve physiological personality recognition by 8% UAR through Auditorial-Visual guided Graphical Attention Networks.

Sep 2018 - Present

The Effects of Task and Social Reflexivity on Group Performance

- Study on Acoustic/Linguistic and Physiological signals fusion algorithms for group dynamics modeling.
- Design a Multi-modality Multi-subjects group interaction dataset.

Sep 2016 - Present

Study of The Alzheimer using Brain Imaging

- Propose a Privacy-aware learning strategy FedCM improving heterogeneity Federated Learning on Medical Images.
- Brought neuroscientific insights into the brain’s functional connectivity and the mechanism of face processing and memory.
- Modeling differential brain functions between subjects with high or low scoring ability to face identification from memory.

Enterprise Corporation

Jan 2020 - Present

Machine Learning Engineer Lead  | C-Media Electronics

- Develop real-time deep CRNN AI de-reverberation engine with SRNR 4.774.
- Lead development of speech cloning from unseen sources using Generative Adversarial Networks.

Mar 2020 - Nov 2020

Machine Learning Engineer Lead  | Institute for Information Industry (III)

- Lead the development of deep video retrieval system speeding up the fake news screening using Pytorch and Ranking algorithm.
- Build the system with Flask and Docker with Retrieval Precision 95.1%.
- The system would be deployed by two NGO fake news checkersTaiwan FactCheck Center and MyGoPen.

Jan 2018 - Jan 2019

Machine Learning Researcher  | beBit, Inc.

- Shopping conversion prediction based on user website traversal graph.
- Customer pattern recognition for automatically clustering user groups for precise marketing.

Sep 2016 - Sep 2018

Machine Learning Engineer  | Gamania Digital Entertainment Co., Ltd.

- Develop deep Speech/Face/Gesture Multi-modal behavior profiling system for AI hiring recommendation.
- Construct a Multi-person Multi-modal real-time data collection system.

Selected Publications (Google Scholar Profile)

JOURNAL

1. Hao-Chun Yang and Chi-Chun Lee, “A Media-Guided Attentive Graphical Network for Personality Recognition Using Physiology” IEEE Transactions on Affective Computing (IF 10.5)

PEER-REVIEWED CONFERENCE/WORKSHOP PAPER

1. Ya-Lin Huang, Hao-Chun Yang, and Chi-Chun Lee, “Federated Learning via Conditioned Mutual Learning for Alzheimer Disease Classification on T1w MRI” 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, EMBC 2021, (Virtual), Nov 1-5, 2021

2. Hao-Chun Yang, Wan-Ting Hsieh, and Pei-Chun Chen, “A Mixed-Domain Self-Attention Network for Multilabel Cardiac Irregularity Classification Using Reduced-Lead Electrocardiogram” Computing in Cardiology, CinC 2020, Brno, Czech Republic, September 12-15

3. Woan-Shiuan Chien, Hao-Chun Yang, and Chi-Chun Lee, “Cross Corpus Physiological-based Emotion Recognition Using a Learnable Visual Semantic Graph Convolutional Network” MM ’20: The 28th ACM International Conference on Multimedia, ACMMM 2020, Virtual Event / Seattle, WA, USA, October 12-16, 2020

4. Wan-Ting Hsieh, Jeremy Lefort-Besnard, Hao-Chun Yang, Li-Wei Kuo, and Chi-Chun Lee, “Behavior Score-Embedded Brain Encoder Network for Improved Classification of Alzheimer Disease Using Resting State fMRI” 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, EMBC 2020, Montreal, QC, Canada, July 20-24, 2020

5. Ya-Lin Huang, Wan-Ting Hsieh, Hao-Chun Yang, and Chi-Chun Lee, “Conditional Domain Adversarial Transfer for Robust Cross-Site ADHD Classification Using Functional MRI” 2020 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2020, Barcelona, Spain, May 4-8, 2020
6. Hao-Chun Yang and Chi-Chun Lee, “A Siamese Content-Attentive Graph Convolutional Network for Personality Recognition Using Physiology” 2020 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2020, Barcelona, Spain, May 4-8, 2020

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