Dr. Tsung-Lu Michael Lee is a visionary researcher and educator at the forefront of artificial intelligence and its applications in healthcare and bioinformatics. As an Assistant Professor in the Department of Computer Science and Information Engineering at Southern Taiwan University of Science and Technology, Dr. Lee leads the cutting-edge Generative AI Lab, where he and his team are pushing the boundaries of what's possible with large language models and AI-driven biomedical research.

With a Ph.D. from National Cheng Kung University and extensive international experience, including research at the prestigious Institute for Systems Biology in Seattle, Dr. Lee brings a wealth of knowledge and a global perspective to his work. His research interests span a wide range of exciting fields, including generative AI, deep learning, medical image recognition, and mixed reality applications.

Dr. Lee's publication record speaks to his innovative approach and impactful research. He has contributed to high-impact journals such as Nature Communications, Gastroenterology, and the Journal of Medical Internet Research, tackling complex challenges in cancer research, protein interaction prediction, and machine learning for medical imaging. His work on using histopathology images to predict multi-omics aberrations in colorectal cancer patients, published in Nature Communications, demonstrates the potential of AI to revolutionize personalized medicine.

As a mentor, Dr. Lee offers interns the opportunity to work on cutting-edge projects at the intersection of AI and healthcare. Current research in his lab includes developing advanced large language models, creating AI chatbots for healthcare applications, and applying deep learning techniques to medical image analysis. Interns will have the chance to contribute to projects that have real-world impact, potentially improving patient outcomes and advancing our understanding of complex diseases.

Dr. Lee's commitment to education is evident in his development of multiple Ministry of Education-certified digital learning courses in subjects like machine learning, mobile UI design, and computer networks. This dedication to teaching ensures that interns will receive top-notch guidance and support throughout their research experience.

Furthermore, Dr. Lee's extensive network of collaborations with leading institutions and his active participation in international conferences provide interns with valuable opportunities for professional growth and exposure to the global research community.

Joining Dr. Lee's lab as part of the IIPP offers a unique chance to be at the cutting edge of AI research in healthcare, working with state-of-the-art technologies and contributing to projects that have the potential to transform medical practice and improve lives. Under his mentorship, interns will develop not only technical skills but also the critical thinking and problem-solving abilities essential for success in the rapidly evolving field of AI and bioinformatics.

The Generative AI Lab, led by Dr. Tsung-Lu Michael Lee at Southern Taiwan University of Science and Technology, is at the forefront of exploring cutting-edge artificial intelligence technologies and their diverse applications, with a particular focus on healthcare and bioinformatics. Our research spans several key areas:

Generative AI and Conversational Agents:
Building on Dr. Lee's expertise in AI and healthcare, students engage with state-of-the-art large language models to develop AI chatbots and conversational interfaces tailored for medical applications. Key focus areas include:
* Developing AI-powered medical assistants for patient care and clinical decision support
* Creating educational chatbots for medical training and patient education
* Exploring the potential of generative AI in biomedical literature mining and knowledge synthesis
* Evaluating and ensuring the safety and reliability of AI-generated medical content

Large Language Model Development:
Leveraging Dr. Lee's experience in bioinformatics and systems biology, the lab focuses on training domain-specific large language models for specialized medical and biological applications. This includes:
* Developing models for analyzing electronic health records and clinical notes
* Creating language models capable of understanding and generating complex biomedical texts
* Exploring multi-modal models that can integrate text, image, and genomic data

AI Frameworks and Biomedical Applications:
The lab utilizes popular AI/deep learning frameworks like TensorFlow and PyTorch to build and deploy models using real-world biomedical datasets. Projects may include:
* Developing AI models for early disease detection and prognosis prediction
* Creating AI-powered tools for drug discovery and repurposing
* Designing AI systems for personalized treatment recommendations

Deep Learning and Transfer Learning in Medical Imaging:
Building on Dr. Lee's work in medical image recognition, the lab explores advanced deep learning concepts, including:
* Developing novel architectures for analyzing various medical imaging modalities (e.g., histopathology, radiology)
* Applying transfer learning techniques to improve performance on limited medical datasets
* Creating interpretable AI models for assisting medical professionals in image-based diagnoses

Mixed Reality in Healthcare:
Students work on cutting-edge mixed reality applications in medical training and patient care, using platforms like Unity and devices such as Microsoft HoloLens. Projects may include:
* Developing AR/VR systems for surgical planning and training
* Creating immersive patient education experiences
* Designing mixed reality interfaces for telemedicine and remote patient monitoring

IoT and Computer Vision for Smart Healthcare:
Integrating Dr. Lee's experience with IoT and image recognition, the lab develops intelligent healthcare systems using Raspberry Pi and related hardware. Focus areas include:
* Creating smart monitoring systems for patient care and medical facilities
* Developing computer vision applications for automated medical image analysis
* Designing IoT-based solutions for remote patient monitoring and chronic disease management

Through these diverse research areas, the Generative AI Lab offers students a unique opportunity to contribute to groundbreaking projects at the intersection of AI and healthcare, with the potential to make significant impacts on medical practice and patient care.