Dr. Yung-Chun Chang specializes in text mining, natural language processing, and related machine learning and speech recognition technologies. He excels in applying these technologies to address various domain-specific challenges, with primary research interests spanning intelligent healthcare, bioinformatics, business intelligence, and language comprehension. In 2016, Professor Chang was honored with the Outstanding Postdoctoral Research Award from the Academia Sinica and the Doctoral Dissertation Award from the Association for Computational Linguistics. Beginning in 2017, he embarked on an academic career at Taipei Medical University, where he has authored numerous papers published in prestigious international journals and conferences, including TKDE, ACL, I&M, TM, HICSS, Bioinformatics, and JAMIA. His recent achievements in Clinical Natural Language Processing (ClinicalNLP) earned him the prestigious 2023 Future Technology Award. Furthermore, Professor Chang is passionate about teaching and has received several teaching awards. He has also guided his students to win numerous domestic and international awards, including second place in two tracks of the BioCreative 2022 International Biomedical Literature Text Mining Competition, a gold medal in the Taiwan AI EXPO competition, second place in the Coding101 competition, first place in the NTCIR FinArg 2023 competition, and the Innovation Award in the National Science Council's Undergraduate Research Program.
Work Experience
- Visiting Professor, National Taipei University of Nursing and Health Sciences. (2024/2–present)
- Deputy Director, TMU Research Center for AI in Medicine. (2023/8–present)
- Deputy Chief Data Officer, Office of Data Science. (2020/8–present)
- Associate Professor, Taipei Medical University, Graduate Institute of Data Science, Taiwan (2020/8–present)
- Assistant Professor, Taipei Medical University, Graduate Institute of Data Science, Taiwan (2017/8–2020/07)
- Academia Sinica Postdoctoral Research Fellow, Academia Sinica, Institute of Information Science, Taiwan (2017/1–2017/7)
- Postdoctoral Research Fellow, Academia Sinica, Institute of Information Science, Taiwan (2016/8–2016/12)
- Research Assistant, Academia Sinica, Institute of Information Science, Taiwan (2010/1–2016/7)
- Software Engineer, Academia Sinica, Institute of Physics, Taiwan (2008/1–2009/12)
The NLP Lab at Taipei Medical University, under the leadership of Professor Yung-Chun Chang, focuses on cutting-edge research in natural language processing, text mining, machine learning, and the latest advancements in large language models. Our research is diverse, covering areas such as intelligent healthcare, bioinformatics, business intelligence, and language comprehension. We have earned notable accolades, including the Future Tech Award 2023, and have made impactful contributions to ClinicalNLP. Additionally, our lab’s work has been featured in well-known publications, and we have mentored students to achieve success in prominent national and international competitions.
- Intelligent Healthcare: Leveraging NLP and machine learning for improved medical diagnostics and patient care.
- Bioinformatics: Analyzing biological data using advanced language processing techniques.
- Business Intelligence: Extracting insights from business data to drive strategic decisions.
- Language Comprehension: Developing models for better understanding and generation of human language.
- Large Language Models (LLMs): Exploring applications of LLMs in various domains, including clinical settings.
- Excellent Teacher Award of TMU (2024)
- Taiwan Patent: Patent No. I815411.
- Future Tech Awards (2023)
- Best Paper Award in NCS 2023 (2023)
- TMU Annual Teacher Teaching Performance Award (2023)
- 2021 Top 2 of JISE ANNUAL BEST REVIEWER AWARD (https://jise.iis.sinica.edu.tw/pages/jise/index.html#Announcements)
- TMU Annual Teacher Teaching Performance Award (2020)
- Best Paper Award in the domestic track of TAAI 2019 (2019)
- Academia Sinica Postdoctoral Fellowship (acceptance rate: 6/181 = 3.31%) (2016/08–2017/07)
- 2016 ACLCLP Doctoral Dissertation Award (2016)
- Bronze medal 5x5 Shogi in TCGA 2016 computer game tournaments (2016)
- Ph.D. in Information Management: National Taiwan University, Taiwan (2010/07 – 2016/07)
- Master's in Information Management: Chang Jung Christian University, Taiwan (2005/09 – 2007/07)
- Bachelor's in Information Management: Leader University, Taiwan (2001/09 – 2005/06)
2 Vacancies
Job Description
Qualifications:
- Solid Foundation in Machine Learning: Candidates should possess a robust background in machine learning and deep learning frameworks, demonstrating a thorough understanding of the theoretical underpinnings and practical applications.
- Technical Proficiency: Experience with advanced machine learning architectures is essential, including proficiency with Vision Transformers and Convolutional Neural Networks (CNNs). Additionally, experience with NLP frameworks such as BERT, including the ability to fine-tune pre-trained models like Llama for specialized applications, is highly valued.
- Commitment to Healthcare Innovation: A strong passion for healthcare and a keen interest in interdisciplinary research are crucial. We are looking for individuals driven by the desire to make significant contributions to medical advancements through AI.
Internship Offer:
This internship presents a unique opportunity to engage in groundbreaking projects in the field of medical AI. Interns will contribute to the development of innovative models and applications that enhance diagnostic processes, improve clinical decision-making, and advance patient care. Join us to be at the forefront of transforming healthcare through artificial intelligence.
Preferred Intern Education Level
Eligible candidates may be currently enrolled as Master’s or Ph.D. students in Computer Science, Biomedical Engineering, Data Science, or related fields. However, exceptional undergraduate students with relevant experience and a strong interest in healthcare technologies are also encouraged to apply.
Skill sets or Qualities
Technical Skills:
- Medical Imaging:
- Basic experience with Vision Transformers (ViT), CNNs, or other deep learning models.
- Familiarity with image processing and augmentation techniques.
- Clinical NLP:
- Experience with foundational NLP frameworks (e.g., BERT, GPT, T5) or basic text analysis methods.
- Interest in clinical text mining or information extraction from medical narratives.
- Programming:
- Proficiency in Python with basic knowledge of deep learning libraries (e.g., TensorFlow, PyTorch).
- Familiarity with data processing tools like Pandas and NumPy.
- Machine Learning:
- Fundamental understanding of training and fine-tuning deep learning models.
- Willingness to explore transfer learning and domain adaptation techniques.
Soft Skills and Qualities:
- Willingness to learn and explore new AI techniques.
- Strong problem-solving mindset and curiosity for healthcare challenges.
- Ability to communicate ideas effectively and collaborate in a team.
- Attention to detail and eagerness to contribute to impactful research projects.