Boyang Fu headshot

Boyang Fu, PhD

Research Fellow in Biomedical Informatics

Boyang Fu is a Postdoctoral Research Fellow at Harvard Medical School. His research integrates cutting-edge AI and rigorous statistical methods to explore how human DNA influences and interacts with other modalities, ultimately shaping complex diseases. This understanding aims to accelerate the development of effective treatment strategies.

He earned his Ph.D. in Computer Science from the University of California, Los Angeles, with a Designated Emphasis in Computational and Genomic Biology. His doctoral research focused on developing novel machine learning algorithms to uncover genetic interactions and address key challenges such as interpretability and trustworthiness. His work has been published in top-tier conferences and journals, and his research achievements have been recognized with the UCLA Dissertation Year Award, among other honors.

Investigating the sources of variable impact of pathogenic variants in monogenic metabolic conditions.
Authors: Wei A, Border R, Fu B, Cullina S, Brandes N, Jang SK, Sankararaman S, Kenny E, Udler MS, Ntranos V, Zaitlen N, Arboleda V.
medRxiv
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A biobank-scale test of marginal epistasis reveals genome-wide signals of polygenic epistasis.
Authors: Fu B, Pazokitoroudi A, Xue A, Anand A, Anand P, Zaitlen N, Sankararaman S.
bioRxiv
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Fast kernel-based association testing of non-linear genetic effects for biobank-scale data.
Authors: Fu B, Pazokitoroudi A, Sudarshan M, Liu Z, Subramanian L, Sankararaman S.
Nat Commun
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Leveraging family data to design Mendelian Randomization that is provably robust to population stratification.
Authors: LaPierre N, Fu B, Turnbull S, Eskin E, Sankararaman S.
bioRxiv
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