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Gonzalo Mena is an Assistant Professor in the Department of Statistics and Data Science at Carnegie Mellon University. He is a Florence Nightingale Bicentennial Fellow and has experience as a Postdoctoral Fellow at the Data Science Initiative at Harvard University, where he was mentored by Pierre Jacob. Gonzalo completed his PhD in Statistics at Columbia University under the supervision of Liam Paninski. His research focuses on developing robust and efficient statistical methodologies to tackle challenging problems in the life sciences, particularly those involving large datasets from neuroscience and epidemiology. He aims to derive statistically valid inferences from inherently corrupted and biased data, as well as integrate traditional and reliable sources of information. His work involves the emerging field of statistical optimal transport, which provides advanced tools for measuring distance between distributions and mapping statistical properties of estimators. Gonzalo's research is supported by a National Science Foundation grant and strives to encourage collaborations with motivated students.
Carnegie Mellon University • Pittsburgh, PA
Teaching and conducting research in statistics and data science.
Harvard University • Cambridge, MA
Worked on the Data Science Initiative focusing on statistical methods.
Admission is extremely competitive with no strict GPA cut-offs; holistic review is used.