Gene Kim, Ph.D./김 진
Director of Assessment and Research at OMAD
Guest Faculty of Data Science (University of Washington Information School: When available)
Adjunct Faculty of Assessment and Evaluation (University of Washington College of Education: When available)
Education:
Postdoc 1999-2001, University of Wisconsin-Madison School of Education(Automating student demographic and performance data/reports at federal, state, and private levels via various programming languages)
Ph.D. Education 1999, University of Wisconsin-Madison
MS Counseling 1995, University of Wisconsin-Madison
Honors:
Korean Honor Scholarship Winner 1991: Korean Consulate General, Chicago, IL.
Korean Honor Scholarship Winner 1992: Korean Consulate General, Washington, D.C.
- Diversity Officer/Administrator and Teacher for first-generation, low-income, historically underrepresented students and students with disabilities since 1995 to present: Supervision/administration/program management/operational training and instruction.
- Data queries/mining, wrangling, automation, analysis, visualization, for federal (NIH, NSF, US. Dept. Ed), state, private grants and gift proposals, annual reports, and better organizational decision making via SQL, Python, and R.
- Maximum Representation: including/counting, one unique individual with multiple ethnic/racial identities independently via respect, logic, and technology (SQL, R, and Python).
- Automating fiscal data.
- Automating student data.
- Instructions in data/statistics and research methods related course works.
- Policy Analysis
- Student Advising/Undergraduate and Graduate Student Research
- IMT 572 – Introduction To Data Science (Via R: Integrating R with SQL, data wrangling, basic data analysis, data visualization, experimental design/basic inferential statistics, decision tree, unsupervised machine learning algorithm: cluster analysis, supervised machine learning algorithm: regression modeling/predictive modeling, documentations via R Markdown (PDF, html, MS PowerPoint, MS Word…) . Via Python: Introduction to applications such as pandas, vaex, dask, numpy, sidetable, matplotlib, and seaborn packages). MS Excel and MS Access for quick, simple, small, and non-repetitious stuff that does not need to be automated.
- LIS 572
- Why SQL, R, or Python?
- Maximum Representation: counting and respecting unique individual and multiple identities independently.
- EDLPS 593 – Assessment and Evaluation in Higher Education (Introduction to standard assessment and evaluation tools such as SQL, R, MS Access, Minitab, SPSS, Pivot Tables in relation to research methods and statistics in its application to decision making in higher education).
- General Studies 391B – Different Ways of Knowing- Undergraduate Research Methods (Instruction and preparation of undergraduate researchers for presentation to various conferences including UW Annual Pacific Northwest McNair Research Conference and UW Undergraduate Research Symposium)
- 3 Campus Wide Diversity Data Training/Workshops
Bio:
Gene’s Ph.D. dissertation was testing the theory we are treated differently based on what we look like and how much our parent(s) make. In result, we see the world differently and respond to various stimuli differently, therefore when we take our homes to college/universities with us, we utilize and respond to various services in higher education differently which will yield varying academic performances.
After frustratingly spending nearly 85%+ of his time cleaning data over performing statistical modeling for his dissertation, Gene’s postdoctoral research at the University of Wisconsin-Madison was in automating student demographic and performance data(reporting) at a federal, state, and private levels (as well as automating fiscal data) which would usually take weeks or months to a procedure which would only take few minutes once the algorithms are written in various programming languages. Gene was also honored to have run the McNair Scholars Program as a postdoctoral researcher at this time (in the late 1990s).
Gene comes from a low-income immigrant background: it took him nearly 19 years to get his U.S. permanent residency and nearly 23 years to get his U.S. Citizenship. Gene had endured experiences much harder than school. The first 19 years in United States was so painful, he always refers his life events prior to November 1999 and after November 1999.
Gene is a former Assistant Dean of Academic Affairs in College of Letter and Science at the University of Wisconsin-Madison until his wife became an associate professor of history at the University of Washington-Seattle. He is a diversity officer first and data professional second. The first 20 years of Gene’s work with TRIO population group(s) were composed of teaching, advising and mentoring undergraduate and graduate students, and obviously much work in administration/program(s) management. His service and graduate work (including his Ph.D. dissertation on regression modeling on TRIO Student Support Services back in 1999) was on first-generation, low-income, and historically underrepresented population groups since 1995 as an instructor of TRIO Student Support Services in UW-Madison. Gene ran the McNair Scholars Program in both UW-Madison and UW-Seattle, which is a Ph.D. preparatory program to successfully transition first-generation, low-income, and underrepresented students from BA/BS to Ph.D. programs via undergraduate research, seminars, and pre-graduate advising. Gene loves simplifying and clarifying “messy and complex” information and examining its patterns, but also identifying exceptions to those various patterns. In relation to identifying exception to patterns, he is careful NOT to utilize machine learning algorithm as a quantitative profiling tool, rather than a very accurate approximation tool to predict probable future events which will maximally benefit and minimally harm all involved.
Gene started his journey with the TRIO population groups under the mentorship and training from Dr. Ruttanatip Chonwerawong(Brunner), Dr. Brenda Pfaeler, and Dean Walter Lane, at the University of Wisconsin-Madison School of Education which changed his life forever: He is ever so grateful for the opportunities and their teaching/training they provided for him as well as their dedication to first-generation, low-income, and underrepresented students as well as student with disabilities.
As noted above, Gene started his adventures in statistics similar to a lost tourist in the 1990s with XLISPSTAT, Minitab, and S-PLUS, at the University of Wisconsin-Madison, where he took his share of bumps and bruises of anxiety and confusion and thought he was divorced from statistics and data for good upon graduation after becoming dazed and confused. However, as an administrator, explaining the disparities among ethnicities/race, gender, disabilities, and socioeconomic status, application knowledge of statistics/data became a must. And illustrations through data was one of the most effective ways (sometimes the only way) to research, improve, prove and persuade for better opportunities and hope for our students. He was relieved and delighted (and sometimes terrified) when R and Python programming language came about which made him and his research team happier and more efficient . He feels very fortunate to receive his training from late Professor Norman Draper, Professor Wei-Yin Loh , and Professor Bob Wardrop from the University of Wisconsin-Madison Department of Statistics, as well as Mr. Ivan Pagan in University of Wisconsin-Madison Business Learning Center. And when Gene started his data adventure in University of Washington-Seattle, he owes a great deal to Carol Diem and Arlyn Arquiza who trained him in UW data infrastructure since 2006/2007.
Gene’s Background
- Guest Faculty of Data Science (University of Washington Information School)
- Associate Director of McNair Scholars Program and Early Identification Program
- Adjunct Faculty of Assessment and Statistics (College of Education)
- Policy Analyst/Policy Adviser to the Secretary of Faculty
- Assistant Dean of Academic Affairs at College of Letters & Science
- Co-Chair of Assessment and Evaluation at College of Letters & Science
- Letter and Science Experience in Research Mentor (LASER)
- Statistics and Psychology Instructor: TRIO Student Support Services
- TRIO McNair Counselor
- Statistics/Data Consultant: Ph.D. Dissertations
- College of Education (Ethnic/Racial and international demographics for undergraduate, graduate, and professional students, and permanent countries of origin for international students for all UW-Seattle, teaching/instruction of assessment and statistics in higher education, Brotherhood Initiative)
- College of Engineering
- Department of Bioengineering (NSF grant data mining and analysis)
- College of the Environment (Ethnic/Racial and Socio-Economic demographics)
- City of Seattle (Concept of Maximum Representation and data demo)
- Department of Biostatistics (Ethnic/Racial and Socio-Economic demographics)
- Department of Biology/HHMI
- Department of Chemistry (Individual Course Analysis)
- Department of Mathematics (How many URM and women transition to advanced mathematics course works)
- Information School (Ph.D. Dissertation Data Support:Regression Modeling; Survey Support, Guest Faculty of IMT 572 & LIS 572)
- University Honors Program (R code and SQL support/training and Maximum Representation Training)
- Office of Admissions(Enrollment trends of ethnic/race diversity)
- Office of Educational Assessment (R coding research and share in relation to National Clearinghouse Data mining and analysis)
- School of Dentistry
- School of Medicine
- School of Nursing (Ph.D. Dissertation Data Support)
- School of Social Work
- Undergraduate Academic Affairs
- UW Student Life
- UW GenNOM Project