Workshop Overview

The workshop is a three-day international training event designed to equip early-career researchers and public health professionals with cutting-edge skills in molecular epidemiology and artificial intelligence (AI) for viral pathogen surveillance and epidemic/pandemic preparedness. The expected number of participants is 30-40, and will include primarily graduate students, but also open to early career faculty, and public health officials or professionals interested to gather new specialized skill sets. The program will include lectures, hands-on sessions, and structured networking activities, all designed to foster both technical skill development and long-term professional connections.

Organizers

Organizer

Prof. Dr. Marco Salemi
Emerging Pathogens Institute, University of Florida, USA.

Local Organizers

Prof. Dr. Hsin-Fu Liu
Dept. of Medical Research, MacKay Memorial Hospital Taipei, Taiwan.
Institute of Biomedical Sciences, MacKay Medical University, Taiwan.

Prof. Dr. Wen-Shyong Tzou
Dept. of Bioscience and Biotechnology, National Taiwan Ocean University, Taiwan.

Dr. Tsung-Nan Ho
National Museum of Marine Science & Technology, Taiwan.

Co-organizers

Taiwan Society of Engineering Technology and Practical Medicine.
Taiwan Ocean Genome Center (TAoGC).

Speakers

• Prof. Dr. Marco Salemi
  Emerging Pathogens Institute, University of Florida, USA.
• Dr. Yi Guo
  Dept. of Health Outcomes & Biomedical Informatics, University of Florida, USA.
• Dr. Brittany Rife Magalis
  Dept. of Biochemistry and Molecular Genetics, University of Louisville, USA.
• Dr. Simone Marini
  Dept. of Epidemiology, University of Florida, USA.
• Dr. Enea Parimbelli
  Dept. of Electrical, Computer and Biomedical Engineering, University of Pavia, Italy.
• Prof. Dr. Mattia Prosperi
  College of Public Health and Health Professions, University of Florida, USA.
• Prof. Dr. Patrick C.Y. Woo
  Doctoral Program in Translational Medicine, National Chung Hsing University, Taiwan.

Venue

International conference hall, National Museum of Marine Science & Technology, Keelung, Taiwan.

No. 367, Beining Rd., Zhongzheng Dist., Keelung City 202010, Taiwan.
https://www.nmmst.gov.tw/enhtml/index

Workshop Agenda

Day 1: Introduction to Molecular and Computational Epidemiology

• 09:00-09:15 - Opening the workshop
• 09:15-10:15 - Opening lecture - Genomic epidemiology in the era of big data (Marco Salemi)
• 10:15-10:30 - Coffee break
• 10:30-11:30 - Lecture on principles of machine learning in antimicrobial resistance bioinformatics (Simone Marini, online)
• 11:30-12:30 - Keynote lecture - Twenty years of coronavirus discovery (Patrick CY Woo)
• 12:30-14:00 - Lunch
• 14:00-16:00 - Trainees' presentations (~5 short talks selected from the participants' pool)

Day 2: Phylogenetics, Phylodynamics, and genomic LLMs

• 09:00-10:00 - Molecular phylogenetics (Marco Salemi)
• 10:00-10:30 - Coffee break
• 10:30-11:30 - Lecture on phylodynamics with AI (Brittany Rife Magalis)
• 11:30-12:30 - Lecture on generative AI for genomics (Enea Parimbelli)
• 12:30-14:00 - Lunch
• 14:00-16:00 - Practice sessions with software tools (Simone Rancati, Michael Aaron Sy)

Day 3: Causal AI and Epi-informatics

• 09:00-10:00 - Lecture on causal AI (Mattia Prosperi, online)
• 10:00-10:30 - Coffee break
• 10:30-11:30 - Lecture on medical LLMs (Simone Rancati, Michael A Sy, Enea Parimbelli)
• 11:30-12:30 - Closing keynote - Predicting SARS-CoV-2 evolution with machine learning (Marco Salemi)
• 12:30-14:00 - Lunch
• 14:00-16:00 - Trainees' networking (workshop participants and teachers sit in small group tables, introducing themselves, rotate)

Instructional Rationale

The COVID-19 pandemic underscored the critical need for real-time genomic surveillance and intelligent data analysis to inform public health responses. This workshop addresses that need by integrating molecular epidemiology with AI-driven analytics, including:

- Machine learning and AI for outbreak modeling and genomic classification
- Large language models (LLMs) for pathogenomic data interpretation
- Phylodynamics to understand viral evolution and transmission
- Causal AI to infer drivers of viral spread and intervention effectiveness

The curriculum is designed to be highly innovative, combining foundational theory with practical applications using state-of-the-art tools. Participants will gain hands-on experience with software platforms and datasets, enabling them to apply these methods in their own research and public health contexts.

Registration

The applicants should give an abstract presenting their work with a short CV via email to:
salemi@pathology.ufl.edu (Cc to: hsinfu@mmh.org.tw)

Registration fee: NT$ 3000 TWD (payment details will be provided in the acceptance letter)