Matti Corren’s research aims to build machine learning-based classifiers based on methylation and cell-free DNA for early-stage detection of precancer lesions in tumor patients. He combines cancer genomics mechanisms with clinical observational phenotypes to define early lesions that prime cells for tumor development.

Aniket Dey studies interactions of tumor cells and the microenvironment. He pairs functional data from cell lines with genomic profiles from cancer patients to dissect mechanisms that allow tumors to spread to distant organs. He also combines tumor biology with aspects of public health for harmonizing the assessment of personalized cancer risk across demographics.

Dr. Antti Haekkinen has in-depth expertise in computational methods for phenotype profiling and an established track record of analyzing multi-omics data of ovarian cancer. His long term vision is to advance personalized medicine by the rational design of combination therapies that leverage mechanisms in noncoding cancer genomics, DNA repair, and the translational potential of clinical data.

Mirue Kang is an incoming undergraduate student at Brandeis University. Her research focuses on defining genomic loci that confer risks for cancer phenotypes, identifying differences between normal and epithelial cancer stem cells, and applying genetic risk scores to personalized medicine.

Ian Lo is a master’s student in the Health Data Science program at the Harvard T.H. Chan School of Public Health. Her research interests include the use of machine learning and other computational approaches to studying human genetic diseases and disorders.

Vatsal Parikh’s research focuses on applying machine learning techniques to tumor expression profiles, pairing them with data from scalable experimental assays, and inspiring the design of targeted therapies. He also designs interactive web resources to communicate his science to a broad audience.

Yi-Ting Tsai is a master’s student in the Health Data Science program at the Harvard T.H. Chan School of Public Health. Her research focuses on developing new computational strategies for maximizing the value of sequencing in patient care by pairing clinical with genome data.