Dr Matteo Fumagalli

Profile

I graduated in biomedical engineering from Politecnico di Milano - Italy (PhD, 2011). I then moved to UC Berkeley for a postdoc position with Professor Rasmus Nielsen funded by EMBO. In 2014 I returned to Europe as a research fellow with Professor Francois Balloux at UCL funded by HFSP and jointly supervised by Professor Frances Brodsky with funding from NIH. I moved to Imperial College London in 2016 and then became Lecturer in Quantitative Evolution at Silwood Park in 2017. I joined Queen Mary University of London as Senior Lecturer in Genetics in 2021. I am also an affiliated fellow at the Digital Environment Research Institute (DERI) and the Turing Institute.

In my research, I use computational methods to solve complex questions in human genetics and evolutionary biology. I am a strong advocate of inclusive education and ethical publishing, such as  Peer Community In. I often deliver outreach activities on human evolution at local communities and organise STEM-career events to secondary school pupils.

Undergraduate Teaching

Evolution (BIO113)

Essentials skills in biomedicine (BMD100)

Postgraduate Teaching

Statistics for Biologists (BIO724P)

Bioinformatics Software Development Group Project (BIO727P)

Research projects (BIO702P)

Research

Research Interests:

See Matteo Fumagalli’s research profile pages including details of research interests, publications, and live grants.

Supervision

Aicha Ben Taher

Amelia Eneli

Baron Koylass

Roudin Sarama

Yuemin Li

Collaborators

On existing grants:

Michael DeGiorgio (Florida Atlantic University)

Moneeza Siddiqui (QMUL)

Nina Overgaard Therkildsen (Cornell) 

On past grants or fellowships:

Austin Burt (Imperial College London)

Francois Balloux (UCL)

Rasmus Nielsen (UC Berkeley)

Sara Mathieson (Haverford College)

Grants

Ongoing:

Barts Charity Research Seed Grant: "Using Population Genetics to Address Metabolic Health Disparities in East London's Diverse Ethnic Populations" 2024 (co-applicant)

NSFDEB-NERC: "Machine learning tools to discover balancing selection in genomes from spatial and temporal autocorrelations" 2023-2026 (UK PI)

Past:

QMUL-Cornell Global Strategic Collaboration Awards: "Demographic inference from cost-effective DNA sequencing experiments using deep learning" 2023 (PI)

NERC Exploring the frontiers of environmental research: "Generative adversarial networks for demographic inferences of nonmodel species from genomic data" 2023 (PI)

The Leverhulme Trust Research Grant: "A deep learning approach to quantify natural selection in Latin Americans" 2018-2022 (PI)

Human Frontier Science Program postdoctoral fellowship 2014-2016 (Fellow)

European Molecular Biology Organization postdoctoral fellowship 2012-2013 (Fellow)