Faculty

Professor 

Data-related Research and Teaching:  Carlson uses large administrative datasets to estimate the effects of policies on social, political, and economic outcomes of interest. I incorporate data exercises into all the courses I teach.

Professor 

Data-related Research and Teaching:  Michael Crespin's research focuses on legislative politics, congressional elections, and political geography. I teach undergraduate research fellows and graduate students outside of the classroom how to work with data. 

Collaborative Interests: I am interested in collaborating on projects related to text analysis. The Carl Albert Center uses data intensive techniques in our daily archival work. We largely work with text, images, and video. We are especially interested in collaborating with students and faculty who are interested in using our holdings in their research.

Websites:
Department
Personal

Assistant Professor 

Data-Related Research
Chris Garneau is a quantitative social researcher who primarily conducts research with large data sets. His broader research disciplines include sociology, political science, social psychology, and environmental studies. The more specific focus of his research has centered on the intersection of politics, religion, social psychology, and environment. He has experience with higher-level statistical analysis like hierarchical age-period-cohort modeling to measure social change. Garneau recently started exploring machine learning techniques that complement foundational social science statistical methodology. Some of the ML techniques he is familiar with include the SHAPley method, SOM and K-Means clustering, and natural language processing. He has a strong interest in transdisciplinary research with scholars in dissimilar disciplines in the humanities and natural sciences. 

Data-Related Teaching
Each year he teaches two sections of statistics and one section of research methods for sociology undergraduate students. In both classes, students work with real data to get hands-on experience. In my methods course, students conduct their own research with a large secondary data set. 

Collaborative Interests
He has a strong interest in transdisciplinary research with scholars in dissimilar disciplines in the humanities and natural sciences. He is also interested in collaborating to expand my methodological skill set, work on publications, or pursue funding. 

Chris' Website
Email Chris

Associate Professor

Data-related Research and Teaching:  My primary research topic concerns data models for semantically encoding the many types of information in critical editions of literary and documentary texts in ancient languages, especially Latin. I also develop software based on these models to facilitate the creation and the use of born-digital critical editions. Leveraging the best practices known as Linked Open Data to record, preserve, and study texts, people, and objects related to the ancient world is another research interest of mine. Although I have not taught courses on these subjects, I have directed many undergraduate research projects that focus on the intersection of technology and the humanities.

Collaborative Interests: I am interested in collaborating on data visualization techniques, Linked Open Data applications, and text analysis projects. I am especially interested in collaborating with people and organizations seeking entry into any of these fields.

Websites:
Department
Digital Latin Library
GitHub

Assistant Professor

Teaching:
· CL C 3133 – Plato and the Platonic Tradition
· CL C 3803 – From Rome to Baghdad: The World of Late Antiquity
· CL C 4503 – Classical Languages Capstone

Research:
· Greek in Late Antiquity and Byzantium
· Multilingualism in the Christian East
· Syriac Language and Literature
· The Organization of Knowledge in the Ancient and Medieval Worlds

Websites:
Department
Personal

Assistant Professor

Research: My research predominantly use survey data in addition to publication data (bibliometrics) in some cases. In most cases, I use ego-centric network data collected by the survey via name generator and interpreter questions to conduct social network analysis and visualize individuals' social network. Method-wise, I'm trained as quantitative methods scholar with some understanding of Bayesian statistics. I use R for my research. 

Teaching: I have not taught methods course so far, but in case I had to show public-use data and play with it in-class, I've used R and excel since both are more accessible than other tools.

Collaborative Interests: I'm interested in collaboration for data collection and analyses. I'm looking for other faculty who are interested in intergroup relations to address workplace inequity, in collecting network data in public organizations (e.g., universities, public agencies), and who have expertise in qualitative methods (e.g., interviews, focus groups, etc).

Websites:
School
 

Associate Professor

Research:  Asian immigrants' diabetes disparity research is in the process of collecting data. The purposes are to investigate diabetes indicators salient to Asian immigrants’ diabetes and why such a high diabetes disparity is observed among Asian immigrant groups. 

Teaching: The Introduction to Data Analytics covers various data processing tools, so the processed data can be used for data analysis. This class also covers basic statistics, data analytics concepts such as function and data structure, and programing concepts using R.

Collaborative Interests: Overall, I am interested in health disparity. The topics I have investigated include substance abuse such as opioids, cocaine, etc. health literacy, and diabetes. Additionally, I am currently working on a cancer project.

Websites:
School
Personal

Professor

Research: My research is in the area of frames, or overcomplete systems.  A frame will allow you to represent data with a kind of structured redundancy, to provide resilience to erasures or noise while still providing stable reconstruction.  There are applications of frame theory in signal processing, imaging, sparsity, compressed sensing, and a variety of other data-related fields. Most recently, I have worked in a new area called dynamical sampling.  The idea is to use samples from a system that evolves in a way that can be modeled, so that samples taken at time increments, as well as different positions, add to the knowledge of the original signal. This could be useful in cases where sensors are sparse and/or expensive.  If you have a problem like that, I'd love to talk to you!

Teaching: I sometimes teach our capstone course on the topic of frame theory in finite dimensions.  I also enjoy teaching MATH 4373/5373 Abstract Linear Algebra, where we tackle vector spaces and subspaces, operators, inner products, eigenvalue/eigenvector spectral theorem in great detail.  This is an excellent follow-on to the basic linear algebra course for students who wish to understand data algorithms in greater detail.

In Spring 2022, I collaborated with Miro Kramer and Alejandro Chavez-Dominguez to teach a Presidential Dream Course called the Mathematics of Data.  This was a lot of fun to create this course.  I hope we get the chance to do it again.

Collaborative Interests: I’m interested in collaborating with others who are studying different ways to represent data in order to identify or preserve structure.   This could also involve dimension reduction or machine learning techniques.  Also, as mentioned above, I would like to hear about distributed sensor networks or other situations where data is sparse but evolving over time.  

Websites:
Department
Personal

Professor

Data related Research and Teaching: I use panel data econometric techniques to research strategic behavior of bidders in auctions. I analyse the public procurement process, contract renegotiation and market efficiency.  I also study network dynamics using panel data analysis with applications in industrial organization and emphasis in auctions, procurement contracting and the airline industry. My teaching interests include Econometrics and Industrial Organization.

Collaborative Interests: I am interested in collaborating with those who share methodological interests in network analysis. This includes computer scientists, statisticians, engineers, political scientists, sociologists, and faculty in communication.  

Websites:
Department
Personal

Assistant Professor

Research: I am a specialist in topological data analysis. I develop new methods in this field and apply them to problems ranging from material science and fluid dynamics to atmospheric science and biology.

Teaching: I was part of the group that developed a new course called Mathematics of Data. This course In introduces students to the mathematical theory of various aspects of data and image processing. The main themes include categorization and clustering; sparsity and compressed sensing; machine learning; and topological data analysis. This class is a mix of theory and application. Students learn to use Python packages that perform some algorithms in each section. Students also learn the mathematical underpinnings of the algorithms, using what they have learned in linear algebra, differential equations, and – if they have taken these courses - analysis and topology. Participants gain experience with some of the most rapidly-growing and important applications of mathematics - the applications to data and image processing.

Collaborative Interests: I am interested in collaborating with scientists that are interested in understanding complex spatio-temporal patterns in their data. In my previous projects, I predominately worked with physicists, chemists, and biologists. However, I wold be exited to get involved in social sciences as well.

Websites:
School
Personal

Assistant Professor

Data-related Research and Teaching: My research broadly falls under computational social science and digital humanities. I primarily focus on using computational methods (such as NLP, text mining, machine learning) to provide better solutions for information retrieval and organization of digital libraries. I teach one of the core MLIS courses (LIS 5043 - Organization of Information) which is heavily based on the management and organization of data. It covers the basic concepts of information organization and management; information storage and retrieval systems; design and structure of information systems; identification and organization of knowledge resources; and knowledge organization methods. 

Collaborative Interests: I am interested in collaborating with researchers working in text analysis, human-ai interactions, computational social science, digital humanities, critical studies, and gender and technology. 

Websites:
Personal

Associate Professor

Dr. Larson leads the Sport, Health, and Exercise Data Analytics laboratory, which is an interdisciplinary data analytics hub created to serve the general research areas of health promotion, exercise physiology, and sport business. Research projects taking place in his laboratory range from analysis of physical activity, training, and physical performance metrics, to analyzing neurological measurements of sports product consumers.

The laboratory is currently involved in, and open to, research investigations from across the entire spectrum of the production and exchange processes of elite and professional sport, as well as the empirical analyses of exercise and health behaviors. Students participating in laboratory research are competitively selected for the ability, experience, and/or potential capability of becoming a top data analyst in their respective fields.

Websites:
Department
Personal

Research Data Specialist

Dr. Mark Laufersweiler has always had a strong interest in computers, computing, data and data visualization. Mark started at OU as the Computer Systems Coordinator for the School of Meteorology from 1999-2013. Part of his duties included managing the real time data feed and maintaining the departmental data archive. He assisted the faculty, students, and staff in their courses to help promote the computing and data skills needed for the classroom and instruction based on current best practices regarding research data management and code development. Since the Fall of 2013, he has served as the Research Data Specialist for the OU Libraries.

Mark supports the educational mission of the OU Libraries by developing and offering workshops, seminars and short courses, helping to inform the university community on data management plans and better practices for research data management. He is the university's representative to ORCID and the Software and Data Carpentry Foundation and is an active Carpentry instructor and trainer. Currently, he is activities include OU joining as an institutional member with the Open Science Framework (OSF) tool, hosted by the Center for Open Science and organizing activities for the Data Analytics, Visualization, and Informatics Syndicate (DAVIS) located in Bizzell Memorial Library.

Websites:

School of Meteorology
OU Libraries
Data Analytics, Visualization, and Informatics Syndicate (DAVIS) 
The Carpentries  
Software Carpentry   
Data Carpentry  
Carpentries at OU  
ORCID  
Open Science Framework  

Professor

Teaching:
· ASTR 1504 – Astronomy: Exploring the Universe
· ASTR 3103 – Stars
· ASTR 3190 – Observational Astrophyics
· ASTR 4512 – Observatory Methods
· ASTR 5403 – High Energy Astrophysics
· ASTR 5900 – Seminar on Active Galactic Nuclei

Research:
· My current research involves development and implementation of SimBAL, a novel spectral synthesis method to analyze Broad Absorption Line Quasar (BALQ) spectra.

Websites:
Department
Personal

Assistant Professor

Research: At SLIS, I teach information visualization, data
analytics, and evaluating interactive information systems with
users. My courses include modules that allow students to learn
and practice data analysis, visualization, and interpretation skills.

Teaching
At SLIS, I teach information visualization, data analytics, and evaluating interactive information systems with users.
My courses include modules that allow students to learn and practice data analysis, visualization, and interpretation skills.

Collaborative Interests:  I am looking forward to interdisciplinary collaborations on following topics:
- Human information interaction and learning
- Information retrieval and machine learning
- Cognitive modeling of users interacting with information systems
- Bounded rationality
- Human-AI interaction and collaboration
- Data reusability

Websites:
Department
Personal

Associate Professor

Data-related Research and Teaching:  I am an archaeologist that uses computer and statistical methods to study the past, including analyses of movement in the past using geographic data, digital image analysis of archaeological specimens for classification, and analyses of datasets large and small. I regularly teach ANTH 5083, the graduate level statistics class in Anthropology which covers basics and emphasizes Exploratory and Multivariate applied analyses that are frequently of use the small and flawed data sets that anthropologists frequently work with; and ANTH 5593, a graduate level class which covers the use of GIS and spatial data analysis.

Collaborative Interests: I am interested in collaboration on GIS, cost distance analysis, data visualization, and a range of topics.

Websites:
Department
Personal

Co-Director of the Data Scholarship Program, Academic Programs
Associate Professor

Research:
My research focuses on textual data analytics. I use natural language processing and machine learning techniques to analyze textual data. I have applied natural language processing and machine learning techniques to scientific literature to analyze knowledge creation, emergence, evolution, and integration. I have also developed novel information retrieval tools and models to improve text retrieval. More recently, I have collaborated with domain specialists to apply my text analytics skills to a variety of domains. This includes developing natural language processing methods to accelerate patients and clinical trials matching for phase 1 oncology clinical trials, information extraction algorithms to extract band gap information from materials science literature and applying text mining to understand Native American authors and their works.

Teaching:
I teach a variety of technology courses in our department, including introductory IT course, text mining and information retrieval, database, dynamic web development. These courses cover SQL, PHP, Python, HTML.

Collaborative Interests: 
I am looking for domain scholars who need text analysis. I can apply text analytics to a large scale of textual data to extract insights.Websites:

Department
Personal

Assistant Professor

Teaching:

• Energy and the Economy

Research:

• Applied Empirical methods
• Causal inference
• Large-scale modeling of natural phenomena

Collaborative Interests:

I am interested in collaborating with individuals who have expertise in modeling natural processes such as fire spread or weather regimes and built systems such as energy infrastructure.

Websites:
Personal

Assistant Professor

Teaching:
· ASTR 1504 – Astronomy: Exploring the Universe
· ASTR 1504 – Astronomy: Exploring the Universe with Laboratory
· ASTR 4990 – Independent Study

Research:
· Near-Field Cosmology
· Galaxies
· Star Formation
· Stellar IMF
· Big Data

Websites:
Department
Personal

Director, OU Supercomputing Center for Education and Research

Collaborative Interests:  Research Computing

Websites:
Department 
Personal

Assistant Professor

Research: I teach Econ 2843- Business Statistics. I also have research in the areas of public policy that effect low and middle income households. I have used advanced econometrics and regression analysis. I also use ArcGIS for spatial analysis and to capture spatial information that I can use in STATA for regression analysis. I have papers over how Universal Free Breakfast effects test scores and conflict in schools. How fracking has effected home prices, and how flat rate tuition effects student enrollment and GPA's.

Teaching: I teach the large lecture Econ 1113 Macroeconomics and have redeveloped Econ 2843 Business Statistics. Business Statistics we focus on excel coding

Collaborative Interests: In areas of public policy that effect low and middle income families and how to make statistical analysis, and data science in public policy and the business world. 

Websites:
School
Personal

Professor

Research: My interest is in Topological Data Analysis (TDA)
which is an application of Algebraic Topology. A standard set-up is: Given a data cloud, a parametrized family (usually 1 real parameter) of topological spaces (simplicial or cell complexes)
are constructed based on proximity restraints of the data
points and the variation of their topological invariants (usually homology) with respect to the parameter is studied (using tools like persistent homology). This provides some insight into the deeper structure of the data, the most basic case being clustering properties. Currently with my PhD student Wenwen Li we are working on multi-persistence (several parameters) with applications to robotics.

Teaching:
I have only taught advanced courses on the necessary mathematical background such as Topology, Algebraic Topology and Configuration Spaces (as Topics in Topology).

Collaborative Interests: 
I'm on the theoretical side of the discipline, but I'm happy to collaborate with those interested. I have collaborated before with some EEC faculty on Signal and Image Processing as well as Computer Architecture (not on TDA).

Websites:
Department

Associate Professor

Data-related Research and Teaching:  I am interested in using artificial intelligence, network analysis, and high-performance computing for data mining, knowledge discovery, and predictive analytics.  My current research focuses include machine learning for predictive genomics and network analysis of big -omics data.  My teaching interests include data analytics, applied artificial intelligence, and parallel programming.

Collaborative Interests: I am interested in collaborating with domain scientists who would like to test hypotheses or develop predictive models using a large amount of data. I can contribute to analytics of big data with high-performance computing, construction and analysis of complex networks, development of machine learning models.

Websites:
Department of Microbiology and Plant Biology
School of Computer Science 
Personal

Associate Professor

Teaching:
· SOC 3123 – Social Statistics
· SOC 3643 – Population and Society
· SOC 5483 – Advanced Regression Analysis
· SOC 5960 – Directed Readings
· SOC 6980 – Research for Doctoral Dissertation
· SOC 6990 – Special Studies in Sociology

Research:
· Migration
· Social Networks
· Inter-Generational Relations
· Household Demography
· Quantitative Research Methods

Websites:
Department
Personal

Assistant Professor
Data-related Research and Teaching: The focus of my laboratory is determining the mechanisms of CRISPR-Cas systems, the bacterial and archaeal adaptive immune system. These RNA-protein complexes have been repurposed as powerful gene-editing tools. There are two aspects of data-related research in my laboratory. 1) Bioinformatics analysis of sequences of protein and nucleic acid components of the CRISPR-Cas systems across the microbial world; this gives us information on evolutionary relations and conservations, which leads to experimental approaches testing bioinformatics-derived hypotheses. 2) Deep-sequencing approaches (DNA-seq) to determine sequences promoting promiscuous activities of Cas proteins; this enables us to perform protein engineering to develop Cas variants that are devoid of promiscuous activities    

Collaborative Interests:  Currently, I collaborate with the Chemistry & Biochemistry Bioinformatics Core (CBBC) for genomic data mining as well as developing pipelines for assembly and analysis of next-generation sequencing data.

Websites:
Department
Personal

Assistant Professor

Data-related Research and Teaching:  I use machine learning and dynamic programming methods to estimate models of individual choice, applied to topics on human capital such as college completion, college major choice, and occupational choice. My teaching interests include Econometrics, Data Science, and Economics of Education.

Collaborative Interests: I am interested in collaborating with those who share either a methodological interest, or a topical interest in what I research. This includes statisticians, computer scientists, sociologists, psychologists, and political scientists.

Websites:
Department
Personal

Associate Director, IPPRA / Associate Professor, Political Science 

Data-related Research and Teaching: I primarily focus on risk and public policy, with an emphasis on social and behavioral responses to information about risk. My data-related research involves a combination of social data (e.g., large surveys) and physical data (e.g., weather/climate data). I teach intro and intermediate analysis of political data (PSC 5923 & PSC 5933), data visualization (PSC 5923), and other special topics, such as survey research and interactive data visualization. 

Collaborative Interests: I enjoy collaborating on all sorts of projects, particularly interdisciplinary projects that merge physical and social data. 

Websites:
Department

Associate Professor

Teaching:
· HIST 2713 – African Civilization
· HIST 3723 – Africa Since 1945
· HIST 3943 – Muslim Societies in Africa
·  HIST 4493 – Africa and the Atlantic Slave Trade
·  HIST 6700 – Colonialism in Comparative Perspective

Research:
·  I am an historian of nineteenth and twentieth century West Africa (religious, legal, cultural, and social, women and gender history).

Websites:
Department
Personal

Presidential Professor

Data-related Research and Teaching:  I teach a statistics course for Graduate students in Biology. 

Collaborative Interests: I have interests in transcriptomics and genomics. I am also interested in using AI in the study of Animal Behavior.

Websites:
Department
Personal

Professor

Data-related Research and Teaching:  Introduction to Digital Humanities; cultural heritage as data; digital antiquities, text as data (text analysis, digital editions), feminist and post-colonial digital humanities  

Collaborative Interests: Text analysis, digital and computational research in antiquity, digital and computational research on religion, feminist digital humanities. My primary collaborative research project currently is Coptic Scriptorium, a platform for digital and computational research in Coptic language and literature; Coptic is the last phase of the ancient Egyptian language, and this project produces digital editions, natural language processing, and other digital resources for research in the language and literature.

Websites:
Department
Personal

Assistant Professor

Research: I am a quantitative methodologist. My research program focuses on developing advanced statistical modeling techniques that can be useful to address issues common in behavioral, cognitive, social, and health-related data. I particularly focus on the methodological aspects of Bayesian statistics, network psychometrics, and ecological momentary assessment data. More recently, I collaborate with health domain researchers, where we use digital mobile technology coupled with statistical modeling to address health-related issues and promote healthy living. I also collaborate with engineering researchers to assess the decision-making and decision-choice processes that will inform intervention.

Teaching: My teaching interests include linear models, longitudinal modeling, and Monte Carlo simulation.

Collaborative Interests: I’m interested in working with researchers having domain expertise that are interested in using statistical models to understand data and test hypotheses. I’m also interested in working with quantitative methodologists to further expand the statistical methodology literature.

Websites:
School
Personal

Edith Kinney Gaylord Presidential Professor, Co-Director of National Center for Risk and Resilience

Teaching:
· PSC 2013 – Introduction to Political Science
· PSC 3233 – Environmental Policy and Administration
· PSC 5950 – Research Problems

Research:
· Risk Perception
·  Environmental Politics and Policy
·  Science and Technology Policy
·  Climate, Weather, and Social Science
·  Contingent Valuation Methodology
·  Policy Analysis
·  Cost Benefit Analysis
·  Risk Analysis and Assessment

Websites
Department
Personal

Associate Professor

Research: My current research interests lie in three areas: (1) statistical techniques for analysis of change in panel data and dynamics in intensive longitudinal data, (2) measurement equivalence/bias across groups and occasions, and (3) applications of quantitative methods in health, social, and behavioral research.

Teaching: Regression, multilevel modeling, structural equation modeling, hierarchical linear models, factor analysis

Collaborative Interests: I am interested in the applications of statistical modeling and psychometric analysis in health, social, and behavioral research.

Websites:
School
 

Teaching:
· MATH 4753 – Applied Statistical Methods
· MATH 4773/5773 – Applied Regression Analysis
· MATH 4793/5793 – Advanced Applied Statistics
· MATH 4803/5803 – Topics in Mathematics
· DSA 5011 – Introduction to R
·  DSA 5041 – Advanced R
·  DSA 5403 – Bayesian Statistics

Research:
· Statistics and R
· Bayesian Statistics
·  Teaching Bayesian Statistics

Websites:
Department

Professor of Mathematics, Anadarko Petroleum Corporation Presidential Professor

Teaching: 
MATH 3113 - Introduction to Ordinary Differential Equations
MATH 4073 – Numerical Analysis
MATH 5173/5183 Advanced Numerical Analysis I/II

Research:
I perform interdisciplinary and data-driven research with emphasis on computation, modeling and analysis of differential equations. I have been focusing on the study of numerical solutions and mathematical modeling of the PDEs describing various applications, and how the computational and analytical results can be interpreted to answer problem-specific questions.

Collaborative Interests: 
I am interested in collaborating with scientists and engineers whose applications involve differential equations and are interested in modeling and solution process, as well as analyzing the results.

Websites:
Department
Personal

Professor

Data-related Research and Teaching: I use large datasets from satellites to measure and monitor the Planet Earth, specifically, land use and land cover change, agriculture, forestry, surface water resources, and atmospheric composition. My teaching interest includes remote sensing and biogeochemical models.

Collaborative Interests: I am interested in collaborating with those who study Earth System science and sustainability, biodiversity and ecological forecasting, disease ecology and public health.

Websites:
Department

Assistant Professor

Research: Research on data-driven decision-making (DDD) and scientific learning in entrepreneurship, using field experiments and natural experiments.

Teaching: Econometrics for Ph.D. students (causal inference). Finance for undergraduates (with emphasis on data and interpretation).

Collaborative Interests: AI-human interactions, structured practices to link boundedly rational humans with data-intensive AI systems.

Websites:
School
Personal