Dr Vasileios Panagiotis Lenis PhD, FHEA

• PgCert Learning and Teaching in Higher Education (LTHPGC), Teesside University, UK.
• PhD in Bioinformatics, Aberystwyth University, UK.
• M.Sc. in Applied Informatics, University of Macedonia, Greece.
• B.Sc. in Computer Science, Hellenic Open University, Greece.

I am an Associate Professor in Bioinformatics and Health Data Science Education at the University of Birmingham. I hold a PhD in Bioinformatics from Aberystwyth University and have previously held academic and research positions at Aberystwyth, Plymouth and Teesside universities.

My academic work combines research in computational biology and bioinformatics with teaching, curriculum development and postgraduate programme leadership. As Programme Director for the MSc Health Data Science at the University's Edgbaston campus, I contribute to the development and delivery of interdisciplinary education at the interface of computing, statistics, biomedical sciences and healthcare.

I am also actively involved in research software and data science training, contributing to national and international training communities and initiatives that promote open, reproducible and accessible computational research.

Programme Leadership

• Programme Director, MSc Health Data Science (Edgbaston campus)
• Deputy PGR Training Lead, School of Medical Sciences

MSc Health Data Science – Edgbaston

Teaching and module leadership contributions across:

• Foundations of Computing Practices in Health Data Science
• Epidemiology and Health Informatics
• Data Analytics and Statistical Machine Learning for Health Data Science
• Integrative Multimodal Data Analytics
• Health Data Science Challenges
• Health Data Analytics
• Interdisciplinary Health Data Research Project

MSc Health Data Science – Dubai

Teaching and module leadership contributions to:

• Foundations of Computing Practices in Health Data Science
• Interdisciplinary Health Data Research Project

My teaching focuses on computational approaches to biomedical and healthcare data, including programming, statistical analysis, machine learning, bioinformatics, reproducible research and the interpretation of complex biological datasets.

I am always looking for interested and motivated PhD students within my preferred research areas. Please contact me directly via email. 

My research interests lie at the intersection of bioinformatics, computational biology and health data science, with a particular focus on applying computational and statistical approaches to understand complex biological systems and human disease.

My work includes the analysis and integration of high-throughput omics datasets, including genomics, transcriptomics and other molecular data, alongside the application of machine learning and systems biology approaches to biomedical research.

I am particularly interested in cancer biology, molecular mechanisms of disease, biomarker discovery and the integration of heterogeneous biological and clinical data to support translational research and precision medicine. I also have a broader interest in reproducible computational workflows, research data management and FAIR data practices.

I am actively involved in national and international bioinformatics and data science training initiatives, with a particular interest in building computational research skills and promoting reproducible, open science practices.

• ELIXIR-UK: ELIXIR-UK Fellow and contributor to training, research data management and FAIR data stewardship initiatives, including activities supporting the development and sharing of bioinformatics training resources.
• The Carpentries: Certified Instructor and Instructor Trainer, contributing to the delivery of Software Carpentry and Data Carpentry workshops, as well as the training of new instructors in evidence-based approaches to computational skills teaching.
• Bioconductor: Instructor contributing to training in the analysis of high-throughput biological data using R and Bioconductor.

Through these activities, I contribute to the development and delivery of workshops and training resources for researchers and students in the UK and internationally, promoting accessible, reproducible and sustainable computational research practices.