Ethan Epperly Receives Chancellor’s Award for Excellence in Undergraduate Research
Ethan Epperly (CCS Computing and CCS Mathematics ‘20) receives prestigious award for research on developing algorithms for potential 3-D imaging applications
By Kailyn Kausen (CCS Writing & Literature ‘20)
The annual Chancellor’s Awards are presented to extraordinary undergraduates and faculty to honor their exceptional contributions to their field or discipline. This year, Ethan Epperly (CCS Computing and CCS Mathematics ‘20) was one of three undergraduates to receive the Chancellor’s Award for Excellence in Undergraduate Research. Stephanie Katz (L&S Sociology ‘20) and Farbod Moghadam (L&S Chemistry ‘20) also received the award and Department of English Professor Candace Waid received the Chancellor’s Faculty Award for Undergraduate Mentoring.
“I feel CCS’s unique structure was essential for me being able to do this work,” said Ethan of the research that resulted in him receiving the Chancellor’s Award. “I first met my advisor Professor Chandrasekaran in a graduate-level mathematics course I took early in my second year, and I was able to take a graduate-level special topics class with him the following quarter where I learned the background material essential for me to work on this project.”
I feel CCS’s unique structure was essential for me being able to do this work.
Ethan began research with Dr. Shivkumar Chandrasekaran, a professor in the Department of Electrical and Computer Engineering, in his third year. In an article for The Current, Dr. Chandrasekaran said Ethan’s work “...would have easily earned him a Ph.D. It is that deep and innovative, with broad applications in applied mathematics and computational science.”
Dr. Chandrasekaran said Ethan’s work “...would have easily earned him a Ph.D. It is that deep and innovative, with broad applications in applied mathematics and computational science.”
Dr. Chandrasekaran’s research focuses on developing new, fast algorithms for solving linear systems of equations which appear in complex applications including three-dimensional (3-D) biomedical and geophysical imaging. Current algorithms have difficulty staying accurate at a large scale. Increasing the accuracy and speed of algorithms used to create these images can provide a range of potential benefits, such as clearer and more holistic brain scans for doctors as well as more precise subsurface geological mapping for geologists and other professionals.
Ethan’s specific research dealt with a deceptively simple question in linear algebra having to do with the processing of matrix data. Matrices are rectangular arrays of numerical data that are the foundation of linear algebra and are ubiquitous tools in designing algorithms for dealing with data. Many important scientific and engineering problems can be cast as matrix problems, allowing these problems to be solved efficiently on computers using the tools of linear algebra. A basic characteristic of a matrix is its rank, which is equivalent to the number of linearly independent columns in the matrix. This means that reducing the rank of a matrix will reduce the amount of discrete data stored in the matrix and speed up the algorithm. For a collection of overlapping matrices, Ethan asked how the data shared by all the matrices could be selected to reduce the overall amount of data stored in the block of matrices by decreasing their rank.
“Our group thought that there would be tradeoffs involved—minimizing the rank of the second matrix might increase the fifth for example,” said Ethan. “However, as I discovered, it was actually possible to simultaneously minimize the rank of all the blocks at once with no tradeoffs.”
“CCS allowed me to achieve all of my wildest dreams for what I wanted out of my undergraduate experience,” Ethan recalled. “I truly owe a great debt to CCS for providing an incredible environment for me to learn and develop as a nascent researcher and scholar.”
CCS allowed me to achieve all of my wildest dreams for what I wanted out of my undergraduate experience.
In addition to receiving the Chancellor’s Research Award, Ethan was a finalist for the Hertz Fellowship and one of eight undergraduates awarded a National Science Foundation Fellowship, which he turned down for a Department of Energy Computational Science Graduate Fellowship (DOE CSGF). He will be pursuing the fellowship and a Ph.D. in Applied and Computational Mathematics from the California Institute of Technology (CalTech).