Wei-cheng Tseng
Attending Physician At Division Of Nephrology at National Yang Ming Chiao Tung University
Taipei, Taiwan
Summary
🤩
Rockstar🎓
Top SchoolWei-cheng Tseng is an attending nephrologist and clinician-scientist based in Taipei with over a decade of frontline experience and five years since earning his PhD in clinical medicine. He balances patient care at Taipei Veterans General Hospital with academic roles at National Yang Ming Chiao Tung University, bringing clinical insight to medical education and research. His publication record (linked) underscores active scholarship, and he has cross-disciplinary technical contributions as an ML engineer to the prominent s3prl speech representation toolkit—showing an uncommon blend of nephrology expertise and practical machine-learning work. Comfortable moving between wards, lecture halls, and open-source codebases, he applies rigorous clinical thinking to data-driven problems and translational research.
5 years of coding experience
Doctor of Medicine - MD, Medicine, Doctor of Medicine - MD, Medicine at National Yang Ming UniversityDoctor of Philosophy - PhD, Institute of Clinical Medicine, Doctor of Philosophy - PhD, Institute of Clinical Medicine at National Yang Ming Chiao Tung University
English, Chinese, Japanese
Github Skills (11)
pytorch10
machine-learning10
self-supervised-learning10
python10
wafv210
modeling9
model-driven-development9
model-driven9
datasets9
model-building9
representation-learning9
Programming languages (2)
Github contributions (5)
s3prl/s3prl
Dec 2020 - Feb 2022
Self-Supervised Speech Pre-training and Representation Learning Toolkit
Role in this project:
ML Engineer
ML EngineerContributions:61 commits, 4 PRs, 5 pushes in 1 year 1 month
Contributions summary:Wei-cheng primarily worked on adding and modifying downstream tasks for self-supervised speech pre-training and representation learning. Their contributions involve integrating new downstream tasks such as ATIS and adapting existing ones like audio-snips, and VCC2018 to the s3prl toolkit. They also made changes to models, datasets, and expert files, indicating an involvement in the model development and evaluation pipeline. The user's work seems focused on enhancing the toolkit's capabilities by incorporating new speech-related downstream tasks for assessment of upstream representations.
vq-apcspeech-representationdecoarrepresentation-learningspeech-recognition
RayTzeng/s3prl
Jul 2021 - Apr 2024
Self-Supervised Speech Pre-training and Representation Learning Toolkit.
Contributions:2 PRs, 97 pushes, 4 branches in 2 years 10 months
pytorchrepresentationsupervisedrepresentation-learningspeech-recognition
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