BRIAN KIM

1218 LeFrak Hall 7251 Preinkert Dr. University of Maryland, College Park, MD 20742

kim[email protected]

EDUCATION

University of California, Los Angeles October 2017

Ph.D. in Statistics

Dissertation: Population Size Estimation using Multiple Respondent-Driven Samples

I develop a model for estimating the size of a hard-to-reach population (e.g. people at high risk for HIV) using

respondent-driven sampling (RDS) data, applying capture-recapture concepts and using the respondents’

• Population Size Estimation: Capture-Recapture and Multiple List methods

• Social Network Analysis

• Network Sampling Methods

• Machine Learning with Survey Data

• Data Science Education

EXPERIENCE

Assistant Research Professor 8/20 - Present

Lecturer 10/17 - 8/20

Joint Program in Survey Methodology

University of Maryland, College Park

• Developed and taught introductory statistics material for both undergraduate and graduate students, utilizing

both traditional and flipped classroom formats in online and in-person settings.

• Wrote, edited, and maintained an online textbook on Introductory Python and SQL with executable code to

be used in various classes.

Statistical Consultant 5/14 - 6/16

Institute for Digital Research and Education

University of California, Los Angeles

• Assisted clients in cleaning, merging, and preparing data for analysis.

• Helped graduate students and professors with their dissertations, publications, and other projects using

methods such as mixed modeling, PCA, simulation, and more using a variety of statistical software.

Journal of Statistics Education

Kreuter, F., Barkay, N., Bilinski, A., Bradford, A., Chiu, S., Eliat, R., Fan, J., Galili, T., Haimovich, D., Kim, B.,

LaRocca, S., Li, Y., Morris, K., Presser, S., Sarig, T., Salomon, J. A., Stewart, K., Stuart, E. A., & Tibshirani, R.

(2020). Partnering with a global platform to inform research and public policy making. Survey Research Methods,

14(2), 159-163. https://doi.org/10.18148/srm/2020.v14i2.7761

Kim, Brian J., Ogwal, M., Sande, E., Kiyingi, H., Serwadda, D., and Hladik, W. (2020) Using Geograph-

ical Data and Rolling Statistics for Diagnostics of Respondent-Driven Sampling. Social Networks. https:

//doi.org/10.1016/j.socnet.2020.05.001

Kim, Brian J. and Handcock, M. (2019) Population Size Estimation Using Multiple Respondent-Driven Sam-

pling Surveys. Journal of Survey Statistics and Methodology. https://doi.org/10.1093/jssam/smz055

at the Symposium on Data Science and Statistics, Bellevue, WA.

Kim, Brian J., Ogwal, M., Sande, E., Kiyingi, H., Serwadda, D., and Hladik, W. (November 2018) Assessing

Respondent-Driven Sampling Using Geographical Data. Presented at the North American Social Network Con-

ference, Washington, D.C.

OTHER ACADEMIC WORK

Reviewer

• Journal of Survey Statistics and Methodology

• Journal of Statistical Software

• Public Opinion Quarterly

Committees

• SURV 673: Introduction to Python & SQL (Fall 2020)

• SURV 673: Introduction to Python & SQL (Summer 2020)

• SURV 622: Fundamentals of Data Collection (Spring 2020)

• BSOS 233: Data Science for Social Sciences (Spring 2020)

• BSOS 233: Data Science for Social Sciences (Fall 2019)

• SURV 673: Introduction to Python & SQL (Fall 2019)

• SURV 673: Introduction to Python & SQL (Summer 2019)

• SURV 699M: Review of Statistical Concepts (Summer 2019)

• SURV 699C: Introduction to Python & SQL (Summer 2018)

Teaching Assistant

• SURV 751: Big Data and Machine Learning (Spring 2018)

University of California, Los Angeles 1/17 - 3/17

Instructor

• Stat 98T: Six Degrees of Separation: Studying the World Through Social Networks (Winter 2017)

University of California, Los Angeles 9/13 - 6/16

Teaching Assistant

• Stat 10: Introduction to Statistical Reasoning (Spring 2016)

• Stat 10: Introduction to Statistical Reasoning (Winter 2016)

• Stat 10: Introduction to Statistical Reasoning (Fall 2015)

OTHER TEACHING ACTIVITIES

Applied Data Analytics Program 10/17 - Present

Coleridge Initiative

Instructor

GRANTS AND AWARDS

National Science Foundation, NCSES BAA 9/20 - 8/21

Modernizing NCSES Data Collection Approaches (co-PI)

National Science Foundation, ECR: 1956114 ($401,716) 5/20 - 5/25

Collaborative Research: Impacts of Hard/Soft Skills on STEM Workforce Trajectories (co-PI)

Feasibility Testing of a Respondent-Driven Sampling Approach to

Recruit Human Trafficking Victims

Dissertation Year Fellowship 9/16-6/17

Collegium of University Teaching Fellows 9/16-6/17

Graduate Dean’s Scholar Award 6/12-9/14

TECHNICAL STRENGTHS

Statistical Software Highly skilled in R, including integrating C++ with R using Rcpp, and in the use

Statistics Highly skilled in a variety of methods, including but not limited to hypothesis test-