Benjamin Kaufman

Benjamin Kaufman has worked in a variety of roles since 2014. Benjamin began their career as a Treasurer for the Alpha Delta Phi Society in Middletown, managing the finances of the organization and resolving financial and organizational conflicts. In 2014, they also began working as a Computational Biology and Microbiome Research Assistant at Wesleyan University, where they implemented algorithms and statistical methodologies to predict species diversity. Additionally, they were a Teaching Assistant for an introductory computer science course, lecturing a class of 25 students and assisting struggling students. In 2016, they became a Computational Biology Cancer Research Assistant at Carnegie Mellon University. In 2017, they were a Computational Biology Research Intern at the Broad Institute of MIT and Harvard, where they developed a novel convolutional neural network to better discern between somatic mutations and sequencing artifacts. In 2018, they began working as a Bioinformatics Analyst at the Dana-Farber Cancer Institute, where they developed deep learning methods to detect cancer relapse earlier in patients. Benjamin also worked with probabilistic graphical models for detecting copy number variation in cancer cells. Since 2018, they have been a Research Assistant at the University of Wisconsin-Madison, where their research focuses on the applications of machine learning models to molecular data and the development of deep learning models for molecular data. Benjamin has developed multiple novel deep generative models for molecules. In 2022, they will become a Machine Learning Engineer at Terray Therapeutics.

Benjamin Kaufman began their educational journey in 2013 when they attended Wesleyan University, where they earned a Bachelor of Arts (B.A.) in Biochemistry and Molecular Biology in 2016. Benjamin then went on to Carnegie Mellon University, where they earned a Master of Science (MS) in Computational Biology in 2017. Finally, they attended the University of Wisconsin-Madison, where they are currently pursuing a Master of Science (MS) in Biomedical Data Science, which they are expected to complete in 2022.