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Jiwon Jung

Ph.D. Candidate [CV]

Department of Statistics,
Purdue University

Languages

  • Korean (Native)
  • English (Professional)

Biography

Jiwon Jung is a Ph.D. candidate in the Department of Statistics at Purdue University since January 2021. She is a member of the Data Science in Finance Research Focus Group and are advised by Dr. Kiseop Lee and Dr. Mengyi Xu. She double majored in Economics and Statistics at Seoul National University and completed her Master’s degree in Statistics from the same institution. Prior to joining Purdue, she was a researcher at Asan Medical Center from 2019-2020, where my research focused on developing cancer imaging models. She is currently a smart factory researcher at Vivity AI and contributing to industry-academy collaboration. Her areas of interest include time series analysis using machine learning, modeling and prediction in finance, and applications of stochastic processes. In particular, her research focuses on as follows:

- Quantitative Finance: Modeling limit order book dynamics using machine learning; Analyzing lead-lag effects between intraday and overnight returns

- Actuarial Science: Modeling health transition intensities using a Hawkes process

- Industrial AI: Developing and implementing machine learning models to optimize production processes and improve product quality, including automated inspection of defective products and real-time monitoring of production lines.

Education

Purdue University

Jan. 2021 - Present
Doctor of Philosophy, Department of Statistics

Degree anticipated, May 2024

Seoul National University

Mar. 2017 - Feb. 2019
Master of Science, Department of Statistics

Thesis Title: SportLight: statistically principled crowdsourcing method for sports highlight selection. (Advisor: Prof. Joong-Ho Won)

Seoul National University

Mar. 2013 - Feb. 2017
Bachelor of Science, Department of Statistics

Seoul National University

Mar. 2013 - Feb. 2017
Bachelor of Art, Department of Economics

Upcoming Talks

Invited Talk at 2024 AMS Sectional Meeting, "Modeling multi-state health transitions with a self-exciting process" - Apr 21, 2024, Milwaukee, WI, U.S.

Publications (Journal)

5. Deep Interactive Learning-based Ovarian Cancer Segmentation of HE-stained Whole Slide Images to Study Morphological Patterns of BRCA Mutation
Ho, D. J., Chui, M. H., Vanderbilt, C. M., Jung, J., Robson, M. E., Park, C. S., and Fuchs, T. J.
Journal of Pathology Informatics, 14, 100160 (2023)
4. SportLight: Statistically Principled Crowdsourcing Method for Sports Highlight Selection
Jung, J., Ha, S., Son, W., Lee, J., and Won, J. H.
Journal of the Korean Statistical Society, 1-22. (2022)
3. Style Transfer Strategy for Developing a Generalizable Deep Learning Application in Digital Pathology
Shin, S., You, S., Jeon, H., Jung, J., An, M., Park, R., and Roh, J.
Computer Methods and Programs in Biomedicine, 198, 105815 (2021)
2. Immune Checkpoint Molecule V-set Ig Domain-containing 4 (VSIG4) Expression is Associated with Poor Prognosis in Advanced Gastric Cancer Patients.
Kim, S. W., Roh, J., Jung, J., Pak, H. K., Lee, A. N., Park, Y. S., and Park, C. S.
The Journal of Immunology, 204, 243.4-243.4 (2020)
1. Risk Stratification Using Multivariable Fractional Polynomials in Diffuse Large B-cell Lymphoma
Roh, J., Jung, J., Lee, Y., Kim, S. W., Pak, H. K., Lee, A., and Park, C. S.
Frontiers in oncology, 10, 329. (2020)

Publications (Conference Proceeding)

1. Fused LASSO Application for Gastric Cancer Image Segmentation
Jung, J., Roh, J., and Park, C. S.
American Association of Cancer Research, 27, PO-079, virtual (2021)

Presentations

8. "Attention-Based Reading, Highlighting, and Forecasting of the Limit Order Book"
Invited Talk at 2023 SKKU-KAFE conference; October 25, 2023 (Online)
7. "Modeling Multi-state Health Transitions with Hawkes Processes"
Invited Talk at 2023 INFORMS Annual Meeting
October 15, 2023, Phoenix, AZ, U.S.
6. "Modeling Multi-state Health Transitions with Hawkes Processes"
Presented at CEPAR International Conference 2023; July 5, 2023; UNSW, Sydney, Australia
5. "Attention-Based Reading, Highlighting, and Forecasting of the Limit Order Book"
Presented at SIAM Financial Mathematics and Enginering 2023; June 9, 2023; DoubleTree by Hilton Philadelphia Center City, Philadelphia, PA, U.S.
Invited Talk at SIAM FM23 Minisymposium 48 Data Driven Methods in Finance - Part III of III 2023
4. "Modeling Multi-state Health Transitions with Hawkes Processes"
Presented at Ajou University WCU conference 2023; May 19, 2023; Ajou University, Suwon, Korea
Invited talk at WCU 10th year anniversary conference
3. A Lead-lag Analysis of Intraday and Overnight Returns
Presented at American Mathematical Society (AMS) Sectional Meeting 2023; March 18, 2023; Georgia Institute of Technology, Atlanta, GA, U.S.
Invited talk at Special Session on Advances in Mathematical Finance and Optimization
2. Modeling Functional Disability with Hawkes Process
Presented at Actuarial Research Conference (ARC) 2022; University of Illinois Urbana-Champaign, Champaign, IL, U.S.
1. Modeling Functional Disability with Hawkes Process
Presented at Korean Statistical Society (KSS) 2022 Summer Conference, Seoul, Korea

Awards & Honors

Travel Grant

April 2023
CEPAR 2023

Travel Grant

March 2023
Society for Industrial and Applied Mathematics (SIAM)

Travel Grant

Fall 2022
Graduate Women in Science Program, Purdue University

Emily and Paul Kidwell Graduate Student Excellent Award

Spring 2022
Department of Statistics, Purdue University

Graduate Student Presentation Award, 4th place

July 2022
Korean Statistical Society

Graduate Student Instructor Scholarship

Fall 2018
Department of Statistics, Seoul National University

Academic Scholarship for Excellent Students

Fall 2018
Department of Statistics, Seoul National University

Academic Scholarship for Excellent Students

Fall 2013 - Spring 2014
College of Liberal Studies Dept., Seoul National University

Teaching & Mentoring Experience

Instructor

Spring 2023 - Present
Statistics Dept., Purdue University

- Lectured on elementary statistics as a graduate instructor to 60 undergraduate students

- Covered inferential techniques and data analysis methods and taught SPSS usage as a statistical software

Course:

Teaching Assistant

Spring 2021 - Spring 2022
Statistics Dept., Purdue University

- Led three recitation classes; 20 undergraduate students per class

- Graded assignments and taught Excel and R analysis during weekly recitations

Course:

  • STAT 303: Probability and Statistics for Business (Fall 2021 - Spring 2022)
  • STAT 511: Statistical Methods (Spring 2021)
  • STAT 512: Applied Regression Analysis (Spring 2021)

Teaching Assistant

Spring 2017, Fall 2018
College of Liberal Studies Dept., Seoul National University

- Led weekly discussion sessions and assisted on grading homework assignments and term papers

- Wrote Python code as course material

Course:

  • Selected Topics Seminar 2: Information Theory (Fall 2018)
  • Selected Topics Seminar 1: Knowledge (Spring 2017)

Teaching Assistant

Fall 2017
Statistics Dept., Seoul National University

- Conducted Q\&A session every week to assist students individually with course materials and graded homework assignments and term examinations

- Lectured on text analysis part of the public class lecture using R

Course:

  • Statistics (Fall 2017)
  • Big Data Special Course using R (Jan. 2016)

Mentor

Summer 2017
Statistics Dept., Seoul National University

- Advised high school students on academics and future career concerns

- Supervised and mentored on students' team paper for selective topics in Mathematics and Statistics.

Course:

  • Science Camp for High school Students in College of Natural Science (Summer 2017)

Programming Skills & Proficiency

Python

R

Excel/ SPSS

MATLAB

SAS

Julia

JAVA

C/C++