Michael J. Clark

General Statement

I do a lot of data science, and combined with my consulting experience, this means I’ve covered a lot of ground- analytically, dealing with many types of data both big and small, and with ideas, just burgeoning or traipsing well established domains. Clients come from a wide variety of backgrounds and the range of their needs is quite extensive. In a given week, I might help someone with some code to scrape the web, employ a Bayesian model to incorporate spatial random effects, use machine learning techniques to predict rare events, develop theoretical motivations to eventually be tested with structural equation modeling, or maybe help an undergrad understand some regression basics. Among my own work, clarity, especially via visualization, as well as reproducibility, are the goals I continually strive for.

I enjoy empowering people and helping them discover the secrets hidden in their data. Underlying all of my efforts is a willingness to use whatever means necessary to gain more knowledge about the underlying mechanisms that produce the information (in the form of data) we seek to understand, and a view of science as software development, continually upgraded, and never static.

Skills

Programming



I primarily work within the R statistical environment for most of my own needs, including the development of my own packages, and I have years of experience with it. I use Stan for Bayesian analysis, and Python for things such as web scraping, text analysis, machine learning, and deep learning. I have experience utilizing a high performance computing environment and parallel processing in general.

I develop R packages primarily for personal use or for fun, but I also use them to improve my coding skills by adhering to common coding standards, striving for high code coverage, and engaging in unit testing. All would pass CRAN checks as well. These include: mixedup, confusionMatrix, visibly, noiris, tidyext, gammit, lazerhawk, 198R, five38clubrankings. In addition to these, though they are not publicly available, I’ve created more packages for work-related projects.

Demonstration, i.e. ‘by-hand’, code for dozens of models and algorithms may be found here.

Analysis


On the analytical side, aside from traditional methods with generalized linear models, mixed models, and latent variable models, I’ve also extended those approaches to the Bayesian world and expanded upon them there. I’ve examined nonlinear relationships via additive models, gaussian processes, etc. I’ve analyzed different types of networks and graphical models generally. I have explored time and space issues via mixed/multilevel/growth model frameworks, survival analysis, and spatial models for both the discrete and continuous setting. I’ve utilized machine learning approaches in a variety of settings and contexts. I’ve also dealt with unstructured data situations such as that found in the analysis of text.

Workshops


When I was in academia, I used to conduct workshops on a near monthly basis, exploring a variety of topics covering programming, analysis, visualization and more. Most were shorter expositions to introduce a topic or tool, while others were more involved, or were invited workshops for specific groups.


Content Title
Modeling Introduction to Machine Learning
Modeling Easy Bayes with rstanarm and brms
Modeling Become a Bayesian in 10 minutes
Modeling Text Analysis with R
Modeling Generalized Additive Models (brief)
Modeling Generalized Additive Models
Modeling Mixed Models with R
Modeling More Mixed Models
Modeling Structural Equation Modeling
Programming Patchwork and gganimate
Programming Engaging the Web with R
Programming Getting More from RStudio
Programming Ceci n’est pas une %>%
R Series Data Processing
R Series Programming
R Series Modeling
R Series Visualization
R Series Presentation

Professional Experience

Senior Machine Learning Scientist

Presently I am a data scientist at Strong Analytics, using a variety of modeling approaches to help clients reach their goals.

Statistician Lead

As a member of CSCAR at the University of Michigan, I provided statistical consultation for faculty and students from various disciplines across campus, as well as serving as analytical lead or providing consulting services for specific research projects. I also conduct workshops related to statistical programming and modeling techniques.

Statistical Consultant

At the University of Notre Dame, I worked for the Center for Social Research (now CSSR) in a position providing aid at any stage of various research projects for students, staff and faculty from various departments on campus, particularly, but not exclusively, to those of the Social Sciences.

Other

Lecturer, Teaching fellow, Research assistant, Test center administrator, Book department clerk, Assistant at a behavioral health care center, Survey conductor, Stable-hand, Pizza delivery driver and cook, Odd jobs via temporary agency, General retail.

Education

Ph.D. Experimental Psychology, Concentration: Statistics, UNT

B.Sc. Philosophy & Psychology, Cum Laude, TCU

Education does not end with a degree. I continue learning both formally and informally by attending workshops, conferences, and talks, and take an occasional online course to further my skills.

Advancement of Research

When I was a member of academia, my primary duty was to strengthen research by bringing sound and advanced methods to a variety of disciplines, in order to provide answers to pressing theoretical concerns. While not a first author due to my role as consultant, almost every academic paper I’ve been affiliated with across several fields has at least 10 citations, with a median number of citations of 31, an h-index of 14, an i10 index of 14 and g-index of 6.

Representative

George, B. et al. (2017). Readiness of US General Surgery Residents for Independent Practice. Annals of Surgery. (link to article; 99th Altmetric percentile, top 50 paper from Annals of Surgery)

Archie, E.A., Tung, J., Clark, M., Altmann, J., Alberts, S.C. (2014). Social affiliation matters: both same-sex and opposite-sex relationships predict survival in wild female baboons. Proceedings of the Royal Society: of London Series B. (link to article; 99th Altmetric percentile)

The following are more involved documents I’ve personally authored. While complete, I update these as I can, and along with other documents I provide, they are downloaded thousands of times per month.

Recent

In progress

Chervin, R. et al. (in preparation). CPAP after Adenotonsillectomy for Pediatric Sleep-Disordered Breathing.

Minh, K. et al. (in preparation). Interface of explicit and implicit second language knowledge.

Gates, R. Bredbeck, B., Chen, X., George, B., Clark, M. et al. (submitted) A multi-institutional study of surgical resident entrustability across multiple phases of care.

Published, Presented, In Press

Kendrick, D.E. et al. (2023). Association of Surgical Resident Competency Ratings with Patient Outcomes. Academic Medicine.

Gonzalez, D. et al. (2022). Brief report: An evaluation of item bias on the Functional Activities Questionnaire. Archives of Clinical Neuropsychology.

Abbott, K.L., Krumm, A.E., Clark, M.J. et al. (2022) Representativeness of workplace-based operative performance assessments for resident operative experience. Journal of Surgical Education.

King, C.A., Gipson, P.Y., Arango, A., Lernihan, D., Clark, M., et al. (2021). LET’s CONNECT Community Mentorship Program for Adolescents with Peer Social Problems: A Randomized Intervention Trial. American Journal of Community Psychology.

Abbott, K.L., Krumm, A.E., Kelley, J., Kendrick, D.E., Clark, M., et al. (2021). Surgical Trainee Performance and Alignment With Surgical Program Director Expectations. Annals of Surgery.

Thelen, A.E., Kendrick, D.E., Chen, X., et al. (2021). Novel method to link surgical trainee performance data to patient outcomes. The American Journal of Surgery.

Schweinsberg, M. et al. (2021). Same data, different conclusions: Radical dispersion in empirical results when independent analysts operationalize and test the same hypothesis. Organizational Behavior and Human Decision Processes.

Abbott, K.L., Kwakye, G., Kim, G.J., Luckoski, J.L., Krumm, A.E., Clark, M., et al. (2021) US general surgical trainee performance for representative global surgery procedures. The American Journal of Surgery.

Kabo, F., Bradley, D., & Clark, M. (2021). The Impact of Library Curriculum-Integrated Instruction On Student Performance. Association of College & Research Libraries (ACRL).

Vu, J., George, B.C., Clark, M., et al. (2021). Readiness of Graduating General Surgery Residents to Perform Colorectal Procedures. Journal of Surgical Education.

Kendrick, D.E., Chen, X., Jones, A.T., Clark, M. et al. (2021). Is Initial Board Certification Associated with Better Early-career Surgical Outcomes? Annals of Surgery.

Kendrick D.E., Clark M.J., et al. (2021). The Reliability of Resident Self-Evaluation of Operative Performance. American Journal of Surgery.

Schuler, B.R., Bauer, K.W., Lumeng, J.C., Rosenblum, K., Clark, M., Miller, A.L. (2020). Poverty and Food Insecurity Predict Mealtime Structure: Mediating Pathways of Parent Disciplinary Practices and Depressive Symptoms. Journal of Child and Family Studies.

Kim, G., Clark, M.J., et al. (2020). Mind the Gap: The Autonomy Perception Gap in the Operating Room by Surgical Residents and Faculty. Journal of Surgical Education.

Schuler, B.R., Daundasekara, S.S., Hernandez, D.C., Dumenci, L., Clark, M. et al. (2020). Economic Hardship and Child Intake of Foods High in Saturated Fats and Added Sugars: The Mediating Role of Parenting Stress among High-Risk Families. Public Health Nutrition.

Scully, M.E., Deal, S.B., Clark, M.J., et al. (2020). Concordance between expert and non-expert ratings of condensed video-based trainee operative performance assessment. Journal of Surgical Education.

Kendrick, D.E., Matusko, N., Hamstra, S.J., Clark, M., et al. (2020) Examining the Generation of Milestone Ratings by Clinical Competency Committees: a Single-Institution Exploratory Factor Analysis. Presented at the Association of Program Directors in Surgery Meeting.

Deal, S., Scully, R.E., Clark, M.J., George, B.C., Alseidi, A. (2020). Crowd-sourced and attending assessment of general surgery resident operative performance using global ratings scales. Presented at the Association of Program Directors in Surgery Meeting.

Kendrick, D.E., Clark, M., Chen, X., et al. (2020). Comparing hospital and surgeon contributions to the likelihood of a severe complication. Presented at the 32nd Annual Moses Gunn Research Conference.

Dabney, B., Kalisch, B., and Clark, M. (2019). A Revised MISSCARE Survey: Results from Pilot Testing. Applied Nursing Research.

Abbot, K, Chen, X., Clark, M. et al. (2019). Number of operative performance ratings needed to reliably assess the difficulty of surgical procedures. Journal of Surgical Education.

Schuler, B. R., Bauer, K.W., Lumeng, J. C., Rosenblum, K., Clark, M., & Miller, A. L. (2019). Food Insecurity and Parenting Styles: Pathways to Mealtime Structure among Low-Income Families. Presentation at the American Public Health Association’s Annual Meeting and Exposition.

Ahle, S. L., Schuller, M., Clark, M. J., et al. (2019). Do End-of-Rotation Evaluations Adequately Assess Readiness to Operate? Academic Medicine.

King, C. et al. (2018). Let’s Connect Community Mentorship Program for Youth with Peer Social Problems: Preliminary Findings from a Randomized Effectiveness Trial. Journal of Community Psychology.

Arango, A., et al. (2018). The Protective Role of Connectedness on Depression and Suicidal Ideation among Bully Victimized Youth. Journal of Clinical Child and Adolescent Psychology.

Coda

I like answering difficult questions with thoughtful approaches to analyzing data, and also just having fun with an interesting challenge. Feel free to contact me if you have any questions about the things I’m up to!



Last updated: 2022 Oct