Research Interests

• Business analytics for information systems, operations, and marketing

• Optimization and algorithm for statistical and machine learning

Education

• Ph.D. in Industrial Engineering and Management Sciences, Northwestern University, Evanston, IL, USA (2015)

• M.S. in Industrial and Systems Engineering, University of Florida, Gainesville, FL, USA (2010)

• B.E. in Industrial Systems and Information Engineering, Korea University, Seoul, Korea (2008)

Work Experience

• Jan 2021 - present: Assistant Professor of Information Systems and Business Analytics, Ivy College of Business, Iowa State University, Ames, IA, USA 

• Aug 2017 - Dec 2020: Adjunct Assistant Professor of Information Systems and Business Analytics, Ivy College of Business, Iowa State University, Ames, IA, USA

• Jul 2015 - Jul 2017: Technical Professor, Cox School of Business, Southern Methodist University, University Park, TX, USA

• Jul 2015 - Jul 2017: Research Associate, National Center for Arts Research, Southern Methodist University, University Park, TX, USA

• Jun 2012 - Aug 2012: Operations Research Intern, Norfolk Southern, Atlanta, GA, USA

Awards and Honors (selected)

• Assistant Professor Achievement in Research Award, Ivy College of Business, Iowa State University, May 2024

• ISBA Assistant Professor in Research Award, Department of ISBA, Ivy College of Business, Iowa State University, May 2024

• Nominee, Best Paper Award, INFORMS Workshop on Data Science 2023, Oct 2023

• Nominee, Assistant Professor Achievement in Research Award, Ivy College of Business, Iowa State University, May 2023

• ISBA Assistant Professor in Research Award, Department of ISBA, Ivy College of Business, Iowa State University, May 2023

• Nominee, Tenure/Tenure Eligible Outstanding Achievement in Teaching, Ivy College of Business, Iowa State University, May 2022

• Best Poster Award, THEREPS 2022 (Tourism, Hospitality, and Event conference for Researchers, Educators, Practitioners, and Students), April 2022

• Teacher of the Month Award, Ivy Student Council, Ivy College of Business, Iowa State University, Nov 2019

• First place, 2015 ICS (INFORMS Computing Society) Student Paper Award

• Terminal Year Fellowship, McCormick School of Engineering, Northwestern University, 2014

• Walter P. Murphy Graduate Fellowship, Northwestern University, 2010

Publications

Peer-Reviewed Journals (corresponding author indicated with *)

1. Y. Jeong, K.B. Lee*, Y.W. Park, and S. Han (2024) "Systematic Approach for Learning Imbalanced Data: Enhancing Zero-Inflated Models through Boosting," Machine Learning 113:8233-8299. [journal link]    † Media coverage: Nature-inspired algorithm to enhance M&A predictions, Auburn University Harbert College of Business News (2024)

2. K.B. Lee*, S. Han, H. Baik, Y. Jeong, and Y.W. Park (2024) "Observation Weights Matching Approach for Causal Inference," Pattern Recognition 154:110549. [journal link]

3. Y.W. Park*, J. Kim, and D. Zhu (2024), "Discordance Minimization-based Imputation Algorithms for Missing Values in Rating Data," Machine Learning 113:241-279. [journal link] [preprint]

4. Y.W. Park, G.B. Voss*, and Z.G. Voss (2023), "Advancing Customer Diversity, Equity, and Inclusion: Measurement, Stakeholder Influence, and the Role of Marketing," Journal of the Academy of Marketing Science 51:174-197. [journal link] [preprint].     † The authors are listed alphabetically.     † Media coverage:  Linking diversity at performing arts nonprofits with marketing, funding, location, Iowa State University News Service (2022).

5. Y.W. Park, J.V. Blackhurst, C. Paul, and K.P. Scheibe* (2022), "An Analysis of the Ripple Effect for Disruptions Occurring in Circular Flows of a Supply Chain Network," International Journal of Production Research 60(15):4693-4711. [journal link] [preprint]. 

6. J. Kim, Y.W. Park*, and A.J. Williams (2021), "A Mathematical Programming Approach for Imputation of Unknown Journal Ratings in a Combined Journal Quality List," Decision Sciences 52(2):455-482. [journal link] [preprint] [code_data.zip]

7. Y.W. Park* (2021), "Optimization for L1-Norm Error Fitting via Data Aggregation," INFORMS Journal on Computing 33(1):120-142. [ journal link ] [ preprint ] [ code_data.zip ]

8. S. Chung, Y.W. Park*, and T. Cheong (2020), "A Mathematical Programming Approach for Integrated Multiple Linear Regression Subset Selection and Validation," Pattern Recognition 108:107565. [journal link] [ preprint ] [code_data.zip]

9. Y.W. Park* (2020), "MILP Models for Complex System Reliability Redundancy Allocation with Mixed Components," INFORMS Journal on Computing 32(3):600-619 [ journal link ] [ preprint ] [ code_data.zip ]

10. Y.W. Park* and D. Klabjan (2020), "Subset Selection for Multiple Linear Regression via Optimization," Journal of Global Optimization 77: 543-574. [journal link] [ preprint ] [ data.zip ] [online appendix]

11. Y.W. Park* and D. Klabjan (2018), "Three Iteratively Reweighted Least Squares Algorithms for L1-Norm Principal Component Analysis," Knowledge and Information Systems 54(3): 541-565. [ preprint ] [journal link]   † Extended journal version of ICDM 2016 proceedings paper

12. Y.W. Park* and D. Klabjan (2017), "Bayesian Network Learning via Topological Order," Journal of Machine Learning Research 18(99) 1-32. [ preprint ] [journal link]

13. Y.W. Park*, Y. Jiang, D. Klabjan, and L. Williams (2017), "Algorithms for Generalized Cluster-Wise Linear Regression," INFORMS Journal on Computing 29(2):301-317. [ preprint ]  [journal link]  [ data.zip ]

14. Y.W. Park* and D. Klabjan (2016), "An Aggregate and Iterative Disaggregate Algorithm with Proven Optimality in Machine Learning," Machine Learning 105:199-232. [ preprint ] [journal link]  † Winner, 2015 INFORMS Computing Society Student Paper Award  [ link ]

15. S. Shebalov, Y.W. Park*, and D. Klabjan (2015), "Lifting for Mixed Integer Programs with Variable Upper Bounds," Discrete Applied Mathematics 186:226-250. [ preprint ] [journal link] [appendix]

16. Y.W. Park* and D. Klabjan (2015), "Lot Sizing with Minimum Order Quantity," Discrete Applied Mathematics 181:235-254. [ preprint ] [journal link]

Peer-Reviewed Proceedings

1. J. Meng, Y.W. Park, and C. Zhang, "Joint Effects and Sequencing of Government Regulations in Sharing Economy Era," Americas Conference on Information Systems (AMCIS) 2024 Proceedings.

2. Y. Jeong, K.B. Lee*, S. Han, Y.W. Park, and J. Park, "CIO Turnover and its Consequences for Competitors," Americas Conference on Information Systems (AMCIS) 2023 Proceedings.

3. Y.W. Park*, Y. Tao, and A. Mishra, "Addressing Health Inequities Using the Quantile Regression with Fairness Constraints," Proceedings of the 31st Workshop on Information Technology and Systems (WITS), Austin, TX, December 2021.

4. Y.W. Park* and D. Klabjan, "Iteratively Reweighted Least Squares Algorithms for L1-Norm Principal Component Analysis," 2016 IEEE 16th International Conference on Data Mining (ICDM), Barcelona, Spain, 2016, pp. 430-438. [proceedings link] [ preprint ] [ data.zip ] [ code.zip ] (Acceptance rate 19.6%)  † Invited to the KAIS special issue of selected papers from ICDM 2016

Non-Refereed Articles

1. Z.G. Voss, G.B. Voss, and Y.W. Park (2021), "The Intersection of Funding, Marketing, and Audience Diversity, Equity, and Inclusion," SMU DataArts. [html] [pdf]

2. G.B. Voss, Z.G. Voss, and Y.W. Park (2017), "At What Cost? How Distance Influences Arts Attendance," National Center for Arts Research. [html] [pdf]

Papers Under Review

1. Y. Jeong, K.B. Lee*, Y.W. Park, S. Han, and J. Park, "Synthetic Control for Count Outcome," Submitted for publication.

2. Y.W. Park*, K.B. Lee, and Y. Jeong, "Coarsened Robust and Inclusive Matching Method," Submitted for publication.

3. H. Lee, and Y.W. Park*, "Algorithm for Geographically Weighted Regression," Submitted for publication.

4. Y.W. Park, Y. Tao, A. Mishra*, and T.S. Raghu, "Fair Analytics Model," Submitted for publication.

5. K.B. Lee, Y. Jeong, S. Han, Y.W. Park, and J. In*, "Learning Unknown Uncertainty," Submitted for publication.

Software

[pcaL1] S. Jot, P. Brooks, A. Visentin, Y.W. Park, and Y.-H. Zhou (2017), pcaL1: L1-Norm PCA Methods. R package version 1.5.2. [Link]  † Co-author since December 2016 (version 1.4.1) 

Presentations

Academic Institutions (selected)

• Coarsened robust and inclusive matching

  • School of Business, Ajou University, Oct 2024 (online seminar)

  • College of Business & Graduate School of Data Science, Seoul National University, May 2024.

  • School of Industrial and Management Engineering, Korea University, Jul 2023.

  • School of Business, Yonsei University, Jun 2023.

  • Department of Supply Chain Management and Analytics, College of Business, University of Nebraska Lincoln, Mar 2023.

  • Department of Industrial Engineering, Hanyang University, Mar 2023 (online seminar).

• Discordance minimization-based imputation algorithms for missing values in rating data

  • Department of Industrial and Management Engineering, Pohang University of Science and Technology, Jul 2021.

  • School of Industrial and Management Engineering, Korea University, Jun 2021.

• Building an industry-specific spatial model based on simultaneous estimation of heterogeneous distance decay functions, Department of Economics, Southern Methodist University, Mar 2017.

• Scalable algorithms for optimization in statistical learning, Department of Statistical Science, Southern Methodist University, Oct 2016.

• An aggregate and iterative disaggregate algorithm with proven optimality in machine learning, Optimization & Learning Seminar, Northwestern University, May 2015.

Conferences

• Coarsened robust and inclusive matching method, INFORMS Workshop on Data Science, Phoenix, AZ, USA, Oct 2023.

• Robust coarsened exact matching: a mixed linear integer program to optimize imbalance measure, INFORMS Workshop on Data Mining & Decision Analytics, Indianapolis, IN, USA, Oct 2022.

• Addressing health inequities using the quantile regression with fairness constraints, 31st Annual Workshop on Information Technologies and Systems (WITS), Austin, TX, USA, Dec 2021

• Fair quantile regression for predicting health outcomes, INFORMS Annual Meeting, Anaheim, CA, USA, Oct 2021 (online presentation)

• Missing values in combined rating lists: analysis and imputation algorithms, INFORMS Annual Meeting (virtual), Nov 2020.

• Missing values in combined rating lists: analysis and imputation algorithms, INFORMS Workshop on Data Mining & Decision Analytics (virtual), Nov 2020.

• A mathematical programming approach for imputation of unknown journal ratings in a combined journal quality list, INFORMS Annual Meeting, Phoenix, AZ, USA, Nov 2018.

• Optimization for l1-norm error fitting via data aggregation, INFORMS Annual Meeting, Houston, TX, USA, Oct 2017.

• Optimization via topological order in presence of acyclic constraints, INFORMS Computing Society Conference, Austin, TX, USA, Jan 2017.

• Estimating distance decay functions for arts & culture markets, INFORMS Annual Meeting, Nashville, TN, USA, Nov 2016.

• Optimization via clustering in machine learning, International Symposium on Mathematical Programming (ISMP) 2015, Pittsburgh, PA, July 2015.

• Optimization via clustering in machine learning, INFORMS Annual Meeting, San Francisco, CA, USA, Nov 2014.

• Algorithm for regression subset selection on a network, INFORMS Annual Meeting, San Francisco, CA, USA, Nov 2014.

• Optimization via clustering in machine learning, 2014 INFORMS Workshop on Data Mining and Analytics, San Francisco, CA, USA, Nov 2014.

• Optimization models for high dimensional variable selection, INFORMS Optimization Society Conference, Houston, TX, USA, Mar 2014.

• Mathematical programming for regression subset selection, INFORMS Annual Meeting, Minneapolis, MN, USA, Oct 2013.

• Lot sizing with minimum order quantity, INFORMS Annual Meeting, Phoenix, AZ, USA, Oct 2012.

Teaching Experiences

Iowa State University

• MIS 3070 Intermediate Business Programming, Fall 2024

• MIS 4360 Introduction to Business Analytics, Fall 2024

• MIS 307 Intermediate Business Programming (Java), Fall 2017 - Spring 2021

• MIS 307 Intermediate Business Programming (Python), Fall 2021 - Fall 2023

• MIS 436 Introduction to Business Analytics, Fall 2022 - Spring 2024

• MIS 446 Advanced Business Analytics, Spring 2024

• MIS 625X Analytical Research in Information Systems, Spring 2023

Southern Methodist University

• Introduction to R, MSBA Boot Camp, Aug 2015 

• MAST 6251 Predictive Analytics 1 (Computer Lab), Fall A 2015, 2016

• MAST 6252 Predictive Analytics 2 (Computer Lab), Fall B 2015, 2016

• ITOM 3306 Operations Management, Spring 2017

Northwestern University  

• IEMS 310 Operations Research, Spring 2014 

• AMPL session, IEMS Boot Camp, September 2014  

Northwestern University (as teaching assistant)  

• MSiA 400 Analytics for Competitive Advantages, Fall 2012, Fall 2013, Fall 2014

• MSiA 490 Introduction to Java Programming, Fall 2013 

• MSiA 401 Statistical Methods for Data Mining, Fall 2014 

• IEMS 313 Deterministic Model and Optimization, Spring 2012

• EECS 317 Data Management and Information Processing, Fall 2012  

Internal Services

Iowa State University

• ISBA Club Faculty Adviser, Fall 2023 - present

• ISBA Research Award Committee, Spring 2023, Spring 2024

• Computer Advisory Committee (Ivy College of Business), Fall 2020 - present

• Chair, Computer Advisory Committee (Ivy College of Business), Fall 2021 - Spring 2023

• Committee on the Advancement of Student Technology for Learning Enhancement (CASTLE), Fall 2021 - Spring 2023

• Department Library Liaison, 2020 - 2022

• ISBA Award & Honors Committee, 2019 - 2020

• ISBA Strategic Planning Committee, 2019 - 2020

External Services

Associate editor, INFORMS Journal on Computing, Oct 2023 - present

Council member, INFORMS Data Mining Society, 2021 - 2023

Paper competition chair (co-chair) 

• 2023 INFORMS Data Mining Society Best Paper Competition

• 2022 INFORMS Data Mining Society Best Paper Competition

Judge

• 2023 INFORMS Best Poster Award

• 2022 INFORMS Best Poster Award

• 2021 INFORMS Workshop on Data Mining & Decision Analytics Best Paper Competition

Research fellow, Southern Methodist University DataArts (SMU DataArts), 

• Oct 2019 - Oct 2020, Apr 2021 - present

Ad hoc reviewer (selected journals in alphabetical order)

• Annals of Operations Research

• Decision Support Systems

• European Journal of Operational Research

• IEEE Transactions on Signal Processing

• IEEE Transactions on Neural Networks and Learning Systems

• INFORMS Journal on Computing

• INFORMS Journal on Data Science

• INFORMS Journal on Optimization

• International Journal of Production Research

• Journal of Machine Learning Research

• Operations Research

• Operations Research Letters

• Optimization Letters

• Production and Operations Management

Session chair

• INFORMS Annual Meeting: 2014, 2018, 2021 - 2023

• INFORMS Workshop on Data Mining & Decision Analytics 2022

• DSI Annual Meeting 2018

• INFORMS Computing Society Conference 2017

Program committee

• Conference on Information Systems and Technology (CIST) 2024

• 2024 INFORMS Workshop on Data Science

• 2023 INFORMS Workshop on Data Science

Discussant

• 19th Big XII+ MIS Research Symposium, Richardson, TX, USA, Mar 2023

• 20th Big XII+ MIS Research Symposium, College Station, TX, USA, Apr 2024

Professional Societies

• Senior Member, INFORMS (Institute for Operations Research and the Management Sciences)

• Member, INFORMS

College of Artificial Intelligence, Computing Society, Data Mining Society, Minority Issue Forum, Information Systems Society, Optimization Society

• Member, AIS (Association for Information Systems)

• Member, Translational AI Center (TrAC), Iowa State University

Links

Articles (writing and graduate school)

• The importance of stupidity in scientific research by Martin A. Schwartz

• The illustrated guide to a Ph.D. by Matt Might

• [Prezi version] The illustrated guide to a Ph.D. by Matt Might

• Ten simple rules for mathematical writing by Dimitri Bertsekas

• Writing Tips for Ph.D. Students by John H. Cochrane

• Fussy Professor Starbuck's Cookbook of Handy-Dandy Prescriptions for Ambitious Academic Authors by William H. Starbuck

• How to be a successful Ph.D. student by Mark Dredze and Hanna M. Wallach

• Advising and Supervising Doctoral Students: Lessons I Have Learned by Gordon B. Davis

• How to Be a Good Dissertation Advisor by Varun Grover and Ramesh Sharda

• Ten Simple Rules for Making Good Oral Presentations by Philip E Bourne

Articles (tutorial, lecture note, etc.)

• H. J. Greenberg. Myths and Counterexamples in Mathematical Programming. INFORMS Computing Society 

• Chris Tang. Op-ed: Paper killers are made, not born. OR/MS Today

Resources for teaching OR

• What is OR (YouTube video) - provided by Learn About O.R.

• PuzzlOR - simple examples of optimization, simulation, scheduling, and predictive analytics

• OR case studies - from HSOR (High School Operations Research)

Source of data sets

• UCI Machine Learning Repository

• Scikit-feature (high dimensional data)

• Kaggle Datasets

Etc.

• Beall's list of predatory journals and publishers 

• Excel2latex (Convert Excel spreadsheets to LaTeX tables)

• Graph of NP-Complete Problems 

• Kaggle (predictive modeling and analytics competitions)

• Scikit-learn (machine learning in Python)

• Gapminder (data and cool interactive plots)

• Rainy Cafe (white noise generator)

• Connected Papers (searching academic papers based on graphs)