Instructor: Prof. Dr.Sherif Edris
Format: Online | Day: 11/10/2026 |Time: To be annouced
Limited Seats Available – Register Early!
Purpose: This workshop focuses on applying AI and machine learning in microbiome data analysis. Participants will learn to preprocess, normalize, and visualize microbiome data, and build predictive models linking microbial signatures to health outcomes.
Learning Objectives:
- Understand AI and ML applications in microbiome data analysis
- Learn to preprocess, normalize, and visualize microbiome data
- Build predictive models linking microbial signatures to health outcomes
- Integrate AI-based tools into reproducible analytical workflows
Expected Outcomes:
- Practical skills in applying AI/ML methods to microbiome datasets
- Ability to interpret complex microbial community patterns using visualization and modelling tools
- Understanding of the challenges and future directions of AI in microbiome science
Speaker Biography:
Dr. Sherif Edris Ahmed is a professor of molecular genetics and genomics at King Abdulaziz University, specializing in microbiome research, genetic variation, and bioinformatics. His work focuses on understanding the molecular basis of diseases through integrated experimental and computational approaches.
He has an extensive publication record with significant citation impact, contributing to areas such as gut microbiome analysis, next-generation sequencing, and disease-associated genetic studies. His research reflects a consistent, interdisciplinary approach with both scientific and translational relevance.
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