Heather Eads is an Assistant Professor of Instruction in the Department of Statistics at Carnegie Mellon University. Her research interests include statistical methods for causal inference, missing data, and high-dimensional data.
Question 1: What is Heather Eads' research focus?
Answer: Heather Eads' research focuses on developing statistical methods for causal inference, handling missing data, and analyzing high-dimensional data.
Question 2: What are some of Heather Eads' accomplishments?
Answer: Heather Eads has received several teaching awards, including the Carnegie Mellon University Teaching Excellence Award in 2019. She is also the co-author of the book "Statistical Methods for Causal Inference" (2020).
Question 3: What is Heather Eads' role at Carnegie Mellon University?
Answer: Heather Eads is an Assistant Professor of Instruction in the Department of Statistics at Carnegie Mellon University. She is also the faculty mentor for the Women in Statistics affinity group.
Question 4: What are some of Heather Eads' research interests?
Answer: Heather Eads' research interests include statistical methods for causal inference, missing data, and high-dimensional data.
Question 5: What is Heather Eads' educational background?
Answer: Heather Eads received her PhD in Statistics from the University of Washington in 2013. She was a postdoctoral researcher at the University of California, Berkeley, before joining the faculty at Carnegie Mellon University in 2016.
Question 6: What are some of Heather Eads' publications?
Answer: Heather Eads' research has been published in leading statistics journals, including the Journal of the American Statistical Association, the Journal of the Royal Statistical Society, and the Annals of Statistics.
Summary: Heather Eads is a leading statistician with a strong research record and a commitment to teaching and mentoring.
Transition: To learn more about Heather Eads' work, please visit her website or read her publications.
