معرفی
Jeffrey Mak is a Doctoral Student and Departmental Lecturer in the Department of Computer Science at the University of Oxford, affiliated with Keble College. His research bridges machine learning and CRISPR biology to develop interpretable tools for predicting CRISPR-Cas9 cleavage activity, incorporating factors like protein 3D structure and epigenetic markers to enhance genome editing safety.
His educational background includes:
- BEng in Computer Science from the University of Hong Kong
- MSc in Computer Science from the University of Oxford
Research interests span Computational Biology and Health Informatics, with emphasis on structure-aware machine learning models that integrate molecular nanoenvironment descriptors and epigenetic features. This approach addresses critical gaps in CRISPR prediction by moving beyond sequence-only analysis to model complex biological contexts influencing off-target effects.
Professional recognition includes:
- Associate Fellow of the Higher Education Academy, UK (2021)
As an educator, Mak has served as graduate teaching assistant (2019-2024) for core modules including Databases and Design and Analysis of Algorithms, and as stipendiary lecturer at Keble College (2024-2025). He completed Oxford's Advanced Teaching and Learning programme in 2021, demonstrating commitment to pedagogical excellence alongside his research in computational genomics.
