Dr Jiawei Wang

Dr Jiawei Wang

BEng MSc PhD

  • Position Governing Body Fellow Junior Research Fellow
  • School European Bioinformatics Institute
  • Email jwang@ebi.ac.uk
  • Department link EMBL-EBI

Jiawei is a Marie Curie Fellow and EMBO Non-Stipendiary Fellow at European Bioinformatics Institute (EMBL-EBI) and a Junior Research Fellow at Wolfson College.

Dr Jiawei Wang

Jiawei’s background covers multiple disciplines, from single-cell genomics, computational biology and microbiology to computer science and software engineering. He was initially a computer scientist, trained in China with Master’s degree in Computer Science from Peking University and Bachelor’s degree in Software Engineering from Tongji University.

 In 2017, Jiawei decided to use his computational skills to address real-world biological problems. Jiawei spent four years of PhD and postdoc at Monash University, Australia, mainly working with Professor Trevor Lithgow FAA, on machine learning-based sequence analysis under the context of microbiology. 

Moving to Cambridge in 2021, Jiawei was awarded three internationally prestigious and highly competitive fellowships that he applied for, including Marie Skłodowska-Curie Postdoctoral Fellowship, MSCA-co-funded EIPOD Fellowship and EMBO Long-term Postdoctoral Fellowship. 

At EMBL-EBI, Jiawei works with Dr. John Marioni, FMedSci, and Dr. Rob Finn, on single-cell omics, multi-omics integration and their applications to study bacterial populations at single-cell level.

Jiawei joined Wolfson College as a Junior Research Fellow in January 2023.

 

Jiawei is passionate about multi-disciplinary research, which lies at the interface of computer science and biology. Since his PhD study in Australia, he has been applying machine learning to study a range of topics from bacteriophage anti-CRISPR mechanisms and virion protein identification to bacterial and fungal protein secretion apparatuses. At Cambridge, Jiawei works on the spatiotemporal analysis of mammalian embryonic development at single-cell level. His project aims to investigate early mammalian development by linking spatial transcriptomics and in toto imaging data. To achieve this, Jiawei has developed a deep learning-based architecture to learn spatial and temporal pattens of developing embryos and organs. In parallel, Jiawei keeps an enthusiasm for bacterial and phage biology. With the emergence of high-throughput bacterial single-cell RNA sequencing (scRNA-seq) techniques, Jiawei founded his own research niche – using single-cell genomics and developing computational methods to study bacterial phenotypic heterogeneity at single-cell level.