Hyonho Chun

Hyonho Chun

Hyonho Chun; Assistant Professor, Statistics (Wisconsin; Statistics; 2008)

Awarded the Department of Statistics Outstanding Assistant Professor Undergraduate Teaching Award in 2014, Dr. Hyonho Chun combines her expertise in statistics and science with enthusiasm for education.  Her history in statistics and science began with a Bachelor of Science degree from Seoul National University in Earth Science Education, and remained for a Master of Science in Statistics.  She then continued with a PhD from University of Wisconsin at Madison in Statistics.  Initially, she was interested in a career in meteorology, but was encouraged to pursue teaching for its stability. 

Throughout her undergraduate training she was exposed to statistics courses, and found that they interested her.  Her courses in earth sciences focused on differential equations, while statistics focused on uncertainty.  She realized that the fundamental assumption of statistics that nothing is certain aligned with her thought process, and decided to minor in it as an undergraduate and continue with a Masters from Seoul National University.

Upon graduating with her Masters degree, and under the political leadership of President Kim, there was a lot of opportunity in Korea for funded travel to the US for further education.  She took one such opportunity to travel to the University of North Carolina for a week to a conference focusing on survival analysis.  This was her first travel experience to the United States, and it was eye-opening to the breadth of statistical topics and applications studied in the US.  After this trip, she easily made the decision to pursue a PhD in Statistics at the University of Wisconsin at Madison. 

Dr. Sunduz Keles advised Hyonho through her thesis focusing on dimension reduction and variable selection with genomics applications.  She then went to Yale for a Post Doc opportunity working with Hongyu Zhao on combining multiple markers in a genome-wide study using human data from a hospital.  As opposed to the genomics dataset she used in her thesis, which was from a public dataset, the focus of this project was to connect a signal and its impact to the human subject. 

After living in the fast paced environment of the east coast for two years, Hyonho decided to return to the Midwest, and in 2010 joined Purdue Statistics.  For Dr. Chun, coming to Purdue was a natural progression for her career.  Purdue Statistics’ appreciation for the breadth of statistical research allows Dr. Chun to focus on what she’s interested in, and respects it.  This has encouraged Dr. Chun to begin focusing on new methodology for cancer genomics.

Historically, Dr. Chun has focused on dimension reduction and variable selection methodology with applications to genomics.  She has now turned that focus to identifying new areas to contribute as a statistician.  Her current research has indicated that as opposed to identifying properties at a population level, in studying cancer one looks at recovering the entire evolution from cells of each individual and then work to a population level.  This alternate way of analyzing datasets usually uses moment solutions which are inefficient, and Hyonho is working to improve the efficiency in order to be impactful and bridge methodology and application.

Hyonho’s focus on creating new methodology that has practical applications is indicative of her collaborative nature.  Currently she is involved in the following projects:

  • MCTP: Sophomore Transitions: Bridges into a Statistics Major and Big Data, Research Experiences via Learning Communities-  As Senior Personnel in collaboration with the Principal Investigator, Dr. Mark Daniel Ward from the Department of Statistics, Dr. Chun will mentor two sophomore students training them to collect datasets from public databases and perform translational research including next generation sequencing. (Funded by National Science Foundation)
  • Variation Discovery from Heterogeneous Tumor-normal Paired DNA Samples using Exome Sequencing-  Principal Investigator collaborating with Xiwen Ma (Funded by Eli Lilly and Company)
  • Collaborative Research: Semiparametric Conditional Graphical Models with Applications to Gene Network Analysis- Collaborative research with Dr. Bing Li at The Pennsylvania State University and Dr. Hongyu Zhao of Yale University. (Funded by National Science Foundation)
  •  Performance Acceptance and Performance Monitoring of Pavement Using Falling Weight Deflectometer (FWD) and International Roughness Index (IRI)-  Mentoring a Masters student, Dr. Chun is working with Tommy Nantung of the Indiana Department of Transportation.

Dr. Hyonho Chun’s research program is focused on many aspects of network inference, statistical genomics, and statistical theory concentrating on real-world applications.  She welcomes new Purdue collaborations and can be reached via email: chunh@purdue.edu.