I believe that creativity is the fuel that drives scientific discovery. As such, we value and promote diversity, equity, inclusion, collaboration and transparency in the laboratory. This culture facilitates the creation of cutting-edge new algorithms for solving the most challenging problems in biomedical research and healthcare.
Breakthrough Research Areas
Our A2I laboratory has been a pioneer in the development, evaluation and application of automated machine-learning methods for biomedical data analysis. For example, our TPOT algorithm and open-source software automatically builds an entire machine-learning pipeline with algorithms for feature selection, feature engineering, feature transformation and machine learning. This takes the guesswork out of machine learning—making this important technology accessible to more users.
Meet Our Team
Our collaborative team includes biologists, computer scientists, data scientists, engineers, mathematicians and statisticians.
Le TT, Fu W, Moore JH.
Bioinformatics. 2020 Jan 1;36(1):250-256.
Li R, Chen Y, Ritchie MD, Moore JH.
Nat Rev Genet. 2020 Aug;21(8):493-502.
La Cava W, Williams H, Fu W, Vitale S, Srivatsan D, Moore JH.
Bioinformatics. 2021 Apr 19;37(2):250-256.
Li R, Duan R, Zhang X, Lumley T, Pendergrass S, Bauer C, Hakonarson H, Carrell DS, Smoller JW, Wei WQ, et al.
Nat Commun. 2021 Jan 8;12(1):168.