DOO YOUNG KIM, Ph. D.

STATISTICAL MACHINE LEARNING

• Cluster Analysis of Time Dependent Information from Finance and Health Science
• Classification of Financial Information – Neural Network (RNN, Deep Learning, etc. & Tree Methods (Random Forest)
• Bayesian Machine Learning

STATISTICAL ANALYSIS AND MODELING

• Parametric and Semi-Parametric Statistical Modeling of Time Dependent Information from Finance and Health Science – Time Series, Longitudinal Data, Survival Data, etc.
• Bayesian Joinpoint Modeling – Multi-Stage Models
• Topics from Quality Control

• [JUN 2023]
  Ram C. Kafle, Doo Young Kim, and Melinda Holt
  “Gender-Specific Trends in Cigarette Smoking and Lung Cancer Incidence: A Two-Stage Age-Stratified Bayesian Joinpoint Model.”
  Cancer Epidemiology, Vol. 84, 102364
• [AUG 2022]
  Ranju Karki, Doo Young Kim, and Chris P. Tsokos
  “Statistical Modeling of S&P 500 Data Based on Time Lags of Apple Corporation.”
  International Journal of Science and Research, Vol. 11(8), pp. 1397-1409
• [MAR 2021]
  Ram C. Kafle, Doo Young Kim, Martin E. Malandro, and Melinda M. Holt
  “Modeling COVID-19 Positivity Rates and Hospitalizations in Texas.”
  Model Assisted Statistics and Applications - Special Issue on Pandemics, Vol. 16(1), pp. 53-58
• [MAR 2020]
  Doo Young Kim and Chris P. Tsokos
  “A Stochastic Approach in Modeling of Regional Atmospheric CO2 in the United States.”
  Journal of Statistical Theory and Applications, Vol. 19(1), pp. 10-20
• [SEP 2018]
  Doo Young Kim and Chris P. Tsokos
  “Active and Dynamic Approaches for Clustering Time Dependent Information: Lag Target Time Series Clustering and Multi-Factor Time Series Clustering.”
  Journal of Statistical Theory and Application, Vol. 17(3), pp. 462-477
• [SEP 2015]
  Doo Young Kim and Chris P. Tsokos
  “Statistical Significance of Fossil Fuels Contributing to Atmospheric Carbon Dioxide in South Korea, and Comparisons with USA and EU.”
  Journal of Applied Statistical Science, Vol. 21(4) pp.345-355

• [SEP 2023]
  Jamile Forcelini and Doo Young Kim
  “Focusing on Derivational Driven Cognate Patterns to Promote Vocabulary Acquisition in Spanish.”
  EuroAmerican Journal of Applied Linguistics and Languages Submitted on December 31, 2022, Revision Request on September 8, 2023
• [FEB 2023]
  Sahar Soliman, Doo Young Kim, Noura Ammar, Jocelynn Robinson, Melinda Holt, Kevin Lord, Maria Zimpfer, David, Hoffpauir, and Diego Alvarez
  “A Tapestry of Socioeconomic Determinants of Health Underlies Prescription Opioid Use in Rural and Urban Counties.”
  The Journal of Rural Health, Submitted on February 10, 2023

• [AUG 2023]
  Colleagues & Collaborations: College of Osteopathic Medicine (COM), College of Health Sciences (COHS), and College of Science & Engineering Technology (COSET)
• “Collaboration Experience with Statisticians: Cluster Analysis and Bayesian Modeling.”
• Sam Houston Room, SHSU The Woodlands Center, TX, USA
• [AUG 2023]
  Teaching & Learning Conference
• Consulting-Based Course Redesign and Significance Testing for Statistics Courses.”
• Sam Houston State University, Huntsville, TX, USA
• [JUL 2023]
  The Korean Data Analysis Society Summer 2023 Conference
• “Correlation-Based Cluster Analysis of the Opioid Epidemic Data from East Texas Counties.”
• Korea University, Seoul, South Korea
• [NOV 2022]
  Colloquium Talk: Department of Mathematics and Statistics at SHSU
• “Subject Specific Correlation Clustering, Bayesian, and Quality Control.”
• Lee Drain Building, SHSU, Huntsville, TX, US
• [APR 2021]
  Invited Talk: Statistics Seminar at The University of Texas Rio Grande Valley
• “Statistical Analysis of Stock Prices with Machine Learning Tools.”
• Remote Conference over Zoom
• [JUL 2019]
  Invited Talk: Joint Statistical Meetings (JSM) 2019
• “Data in the 21st Century: Corporate and Non-Profit Decision Making in the Digital Age.”
• Denver, CO, USA
• [APR 2019]
  Invited Talk: As a New Texas Statistician at the Conference of Texas Statisticians (COTS) 2019
• “New Statistical Approaches in Clustering Financial Time Dependent Information.”
• Lamar University, Beaumont, TX, USA
• [MAY 2018]
  Invited Talk: Frontiers of Statistics Conference
• “Lag Target Time Series Clustering for Financial Time Dependent Information.”
• University of South Florida, Tampa, FL, USA
• [JAN 2018]
  Joint Mathematics Meetings (JMM) 2018
• “Risk Based Target Lag Clustering of Time Dependent Information in Finance.”
• San Diego, CA, USA
• [APR 2016]
  International Federation of Nonlinear Analysts (IFNA) Workshop
• “Active and Dynamic Approaches for Clustering Time Dependent Information.”
• University of South Florida, Tampa, FL, USA
• [JAN 2016]
  Joint Mathematics Meetings (JMM) 2016
• “A Prediction-Based Time Series Clustering of Brain Cancer Mortality Rates in the United States.”
• Seattle, WA, USA
• [FEB 2015]
  American Statistical Association (ASA) Florida Chapter Meeting 2015
• “Parametric Analysis of the Carbon Dioxide in the Atmosphere in the United States.”
• University of South Florida, Tampa, FL, USA
• [JAN 2015]
  Joint Mathematics Meetings (JMM) 2015
• “Transitional Modeling of the Carbon Dioxide in the Atmosphere by Climate Regions in the United States.”
• San Antonio, TX, USA
• [FEB 2014]
  American Statistical Association (ASA) Florida Chapter Meeting 2014
• “Statistical Significance of Fossil Fuels Contributing to Atmospheric Carbon Dioxide in South Korea, and Comparisons with USA and EU.”
• Gainesville, FL, USA
• [JUN 2012]
  International Federation of Nonlinear Analysts (IFNA) World Congress 2012
• “A Betting Strategy in Major League Baseball Using Bayesian Approach.”
• University of Athens, Athens, Greece

• [JUN 2023 – PRESENT] [FUNDED]
  Develop a new distance learning (online) course:
• Premium Distance Learning (PDL) of STAT 3379 for 100% online CJ Majors
• Collaboration with Di Gao
• Funded Amount: $20,000
• [FEB 2022 – DEC 2022] [FUNDED]
  Develop a Texas State University System (TSUS) Online Data Science Certification Program – ZEUS
• A New Online Data Science Certification Program Funded by Texas Higher Education Coordinating Board (THECB)
• Consortium with Texas State University
• Designing Block 4 - Statistics for Data Analysis
• Total Funded Amount for ZEUS: $1.45M
• [JAN 2022 – AUG 2023] [FUNDED]
  Teaching Innovation Grant (TIG)
• Consulting-Based Course Redesign and Significance Testing for Statistics Courses
• PI: Di Gao / Co-PI: Doo Young Kim, Renjie Zhou, and Danhong Chen
• Funded Amount: $9,580
• [OCT 2021 – SEP 2024] [FUNDED]
  Data Science for Energy Transition: Summer Data Science Program Sponsored by University of Houston
• PI for Sub-Award at SHSU / Prime Sponsor: National Science Foundation (NSF)
• Funded Sub-Award Amount: $6,165
• [AUG 2017 – DEC 2017] [FUNDED]
  Student Undergraduate Research Fellowship (SURF)
• PI and the mentor of the recipient, Casey Gilbert
• Sponsored by Arkansas Department of Higher Education (ADHE)
• Funded Amount: $2,750/semester
• [JAN 2017] [NOT FUNDED]
  ORAU (Oak Ridge Associated Universities) – Directed Research and Development Partnership Grant
• Applied as a PI
• “Clustering of Nonstationary Signals with Applications to Health Sciences, Environmental Sciences, and Cybersecurity.”
• [DEC 2016] [TRAINING]
  Beginning a Research Program in the Natural Sciences at a Predominantly Undergraduate Institute
• 72 hours training in 5 days
• Washington D.C., USA

• [JUL 2023]
  Doo Young Kim
  “Correlation-Based Cluster Analysis of the Opioid Epidemic Data from East Texas Counties.”
  Proceedings of the Korean Data Analysis Society, pp. 113
• [DEC 2018]
  Michael W. Kotarinos, Doo Young Kim, and Chris P. Tsokos
  “Multi-Level Time Series Clustering for Asset Selection in Allocation Problems.”
  Proceedings of Joint Statistical Meeting, Business and Economic Statistics Section, Alexandria, VA: American Statistical Association

• [DEC 2012]
  Doo Young Kim
  “Magic of the First Game in MLB: Longitudinal Modeling Approach.”
  USF Tech. Report, 207
• [MAR 2012]
  Doo Young Kim
  “A Betting Strategy in Major League Baseball Using Bayesian Approach.”
  USF Tech. Report, 101

• [ONGOING]
  Di Gao, Doo Young Kim, and Stephen M. Scariano
  “Quality Control in Bayesian Perspective.”
  Simulation Study under Process
• [ONGOING]
  Doo Young Kim, Di Gao, and Stephen M. Scariano
  “Subject Specific Correlation Clustering.”
  Manuscript under Preparation

• [JAN 2023 – PRESENT]
  Graduate Practicum Advisor for Yojana Sharma
  “Prediction of the Probability of Credit Card Customer Churning Using Machine Learning Techniques.”
• [JAN 2023 – MAY 2023]
  Undergraduate Honors Research Project Advisor for Brian Cory
  “Crime in Metropolitan Cities from 2018-2019: Statistical Summary.”
• [AUG 2022 – MAY 2023]
  Graduate Practicum Advisor for Anisha Koirala
  “Predicting the Probability of ICU Patients’ Hospital Death Using Classification Algorithms.”
• [AUG 2021 – AUG 2022]
  Graduate Practicum Advisor for Duleepa Sembukutti
  “Astronomical Image Classification.”
• [JAN 2021 – DEC 2021]
  Graduate Practicum Advisor for Babatunde Aluko
  “Multivariate Stock Price Analysis Using Vector Autoregressive Model and K-Means Algorithm.”
• [AUG 2020 – DEC 2021]
  Graduate Practicum Advisor for Jocelynn Robinson
  “Analysis of Opioid Prescribing Habits in Texas Using K-Means Clustering Algorithm.”
• [MAY 2020 – MAY 2021]
  Graduate Practicum Advisor for Blake Bogs
  “Statistical Analysis of Stock Prices.”
• [AUG 2019 – MAY 2020]
  Graduate Practicum Advisor for Mario Antonio Gonzalez
  “Cluster Analysis of Risk Factors for Foreclosing Houses in Houston.”
• [AUG 2019 – MAY 2020]
  Graduate Practicum Advisor for Nishantha Poddiwala Hewage
  “Cluster Based Multivariate Time Series Modeling of Lung and Bronchus Cancer Mortality Rates in the United States.”
• [AUG 2019 – MAY 2020]
  Undergraduate Honors Research Project Advisor for 6 students: Sara Balusek, Peter Colletti, Amilcar Flores, Megan Porrovecchio, Preston Truong, and Julieta Verdejo-Parada
  “Statistical Modeling of Bivariate Data with Statistical Programming Language R.”
• [AUG 2018 – MAY 2019]
  Undergraduate Honors Research Project Advisor for 2 students: Kayla Clement and Pamela Dominguez
  “Data Analysis with R Programming.”
• [AUG 2017 – MAY 2018]
  Graduate Thesis Advisor for Ranju Karki (Currently, Assistant Professor at North Central College)
  “Risk Based Target Lag Clustering and Modeling of Time Dependent Information in Finance.”
• [AUG 2017 – MAY 2018]
  Undergraduate Honors Thesis Advisor for Casey Gilbert
  “Multivariate Time Series Analysis of Lung and Bronchus Cancer Mortality Rates in the United States.”
• [AUG 2017- DEC 2017]
  Graduate Independent Study Research Advisor for Prabu Annamalai
  “Adaptive Classification by Variational Kalman Filter.”
• [JAN 2017 – DEC 2020]
  Research Advising for a Ph.D. Candidate at USF – Michael Kotarinos
  “Multi-Level Time Series Clustering for Asset Selection in Allocation Problems.”

• [JAN 2023 – MAY 2023]
  Advisor for Data Science for Energy Transition Cohort 1 Group Research
• Yojana Sharma, Madan Neupane, Jordan Yu, and Ethan Hawkins
• “Empowering the Energy Sector with AI: Forecasting Well Bottom Hole Temperature with Machine Learning Techniques on Geophysical Data.”
• University of Houston, Houston, TX, USA
• [APR 2021]
  Mentor for American Statistical Association DataFest
• Virtual Mentoring for students’ research during the 3 day-event
• Southern Methodist University, Dallas, TX, USA
• [AUG 2020]
  Joint Statistical Meetings (JSM) 2020
• 3 Day - Virtual Conference Due to the Pandemic
• [JUL 2020]
  The Exposome Boot Camp
• Virtual Meeting Due to Pandemic
• Columbia University, New York City, NY, USA
• [JUL 2019 – AUG 2019]
  Joint Statistical Meetings (JSM) 2019
• Invited Session
• Denver, CO, USA
• [MAY 2019]
  Symposium on Data Science & Statistics (SDSS) 2019
• Completed a Short Course, “Reproducible Research with R.”
• Completed a Short Course, “Introduction to Deep Learning.”
• Bellevue, WA, USA
• [JUL 2017]
  Review Papers
• Neural, Parallel, and Scientific Computations
• [SEP 2014 – MAY 2016]
  Interdisciplinary Data Sciences Consortium (IDSC)
• Participating Member
• University of South Florida, Tampa, FL, USA
• [MAY 2012 – JAN 2019]
  International Journal of Environmental Sciences (IJES)
• Managing Co-Editor
• IFNA Publishers
• [JUN 2012 International Federation of Nonlinear Analysts (IFNA) World Congress 2012
• A Chair for the “Statistical Modeling” Session
• University of Athens, Athens, Greece