ATHUL SUDHEESH
ATHUL SUDHEESH
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Summary
Summary
Learning Scientist @ Pearson. Lead developer of pgdcm R package. Co-founder & Visiting Scientist @ Cognitive Informatics & Statistics (COINS) Lab,The University of Texas at Dallas.
Won 3 awards for research excellence, and 2 awards for technological innovation.
Research Interests: Bayesian Network models of cognition & learning, Philosophy of Measurement in educational & psychological assessments, Causal Inference.
Thinks like a scientist. Solves like an engineer.
Top Skills
Top Skills
Data Science & Machine Learning
Explainable AI
Causal Inference
Bayesian Inference
Probabilistic Graphical Modeling
User Profiling & Cognitive Modeling
Survey Design
Psychometric Analysis
Personalized User Experience
Cognitive Assessment Task Design
Research Software Development
Version Control
Statistical Programming
Technical Documentation
High Performance Computing
Education
Education
PhD, Cognition & Neuroscience
School of Behavioral & Brain Sciences, UT Dallas
Richardson, Dallas
PhD, Cognition & Neuroscience
School of Behavioral & Brain Sciences, UT Dallas
Richardson, Dallas
Dissertation: A Comparative Analysis of Psychometric Probabilistic Graphical Models for Student Engagement Classification.
2019 - 2025
2019 - 2025
MS, Applied Cognition & Neuroscience
School of Behavioral & Brain Sciences, UT Dallas
Richardson, Dallas
MS, Applied Cognition & Neuroscience
School of Behavioral & Brain Sciences, UT Dallas
Richardson, Dallas
2016 - 2018
2016 - 2018
B.Tech, Electronics & Communicaions Engineering
University of Kerala
India
B.Tech, Electronics & Communicaions Engineering
University of Kerala
India
2010-2014
2010-2014
Professional Experience
Professional Experience
Research Scientist,
Pearson
Remote
Research Scientist,
Pearson
Remote
June 2025 - Present
June 2025 - Present
Visiting Scientist,
Cognitive Informatics & Statistics Lab, UT Dallas
Richardson, Dallas
Visiting Scientist,
Cognitive Informatics & Statistics Lab, UT Dallas
Richardson, Dallas
Dec. 2025 - Present
Dec. 2025 - Present
Research Scientist,
Cognitive Informatics & Statistics Lab, UT Dallas
Richardson, Dallas
Research Scientist,
Cognitive Informatics & Statistics Lab, UT Dallas
Richardson, Dallas
May 2019 - May 2025
May 2019 - May 2025
Research & Psychometric Intern,
Edmentum Inc.
Remote
Research & Psychometric Intern,
Edmentum Inc.
Remote
June 2023 - Aug. 2023
June 2023 - Aug. 2023
Machine Learning Consultant,
ZEP Informatics LLC
Richardson, Dallas
Machine Learning Consultant,
ZEP Informatics LLC
Richardson, Dallas
March 2019 - May 2019
March 2019 - May 2019
Research Assistant,
Cognitive Informatics & Statistics Lab, UT Dallas
Richardson, Dallas
Research Assistant,
Cognitive Informatics & Statistics Lab, UT Dallas
Richardson, Dallas
July 2018 - March 2019
July 2018 - March 2019
Data Science Consultant,
Brand Elevation Partners LLC
Richardson, Dallas
Data Science Consultant,
Brand Elevation Partners LLC
Richardson, Dallas
May 2018 - July 2018
May 2018 - July 2018
Machine Learning Intern,
Cognitive Informatics & Statistics Lab
Richardson, Dallas
Machine Learning Intern,
Cognitive Informatics & Statistics Lab
Richardson, Dallas
Jan 2018 - May 2018
Jan 2018 - May 2018
Co-founder & Chief Engineer,
Dionz Electronics
Kerala, India
Co-founder & Chief Engineer,
Dionz Electronics
Kerala, India
Jan 2018 - May 2018
Jan 2018 - May 2018
Publications
Publications
Research & Technical Reports
Research & Technical Reports
Bradshaw, L., Sudheesh, A., Schellman, M., & Sachdeva, R. (2025). Impact evaluation of Pearson Navvy Math in Arizona school districts. Pearson. [Paper Link]
Pre-prints
Pre-prints
- Sudheesh, A. (2024). The Changing Landscape of Validity-Centered Cognitive Learning-Instructional-Assessment Design Frameworks. https://doi.org/10.35542/osf.io/xe9qn [arXiv link]
Conference Proceedings
Conference Proceedings
Sudheesh, A., & Golden, R. M. (2021). Exploring Temporal Functional Dependencies Between Latent Skills in Cognitive Diagnostic Models. In Quantitative Psychology (pp. 253-262). Springer [Paper Link]
Talks
Talks
Sudheesh, A. Testing Assumptions in Longitudinal Cognitive Diagnostic Modeling. Psychology Lecture Series. University of Texas at Dallas, Richardson, TX., March 2021.
Sudheesh, A. Modeling Student Motivation and Guessing Behavior in Formative Assessments. 10th Texas Universities' Educational Statistics and Psychometrics Conference. University of North Texas, March 2024.
Invited Presentations
Invited Presentations
Golden, R. M., & Sudheesh, A. (2026). Using NIMBLE and iGraph for diagnostic classification Bayesian network modeling. [Workshop]. National Council on Measurement in Education (NCME) Annual Meeting, Los Angeles, CA, United States.
Conference Posters
Conference Posters
Sudheesh, A., & Golden, R. M. (2023). Testing CDM local independence assumptions using nested model selection criteria. Poster presented at the 2023 International Meeting of the Psychometric Society, College Park, Maryland. [Poster Link]
Sudheesh, A., & Golden, R. M. (2020). Exploring temporal functional dependencies between latent skills in summative assessments. Poster presented at the 2020 International Meeting of the Psychometric Society, Virtual. [Poster Link]
Software and other Relevant Outputs
Sudheesh, A., & Golden, R. M. (2026). pgdcm: An R Package for Probabilistic Graphical Diagnostic Classification Modeling (Version 0.1.0) [Computer software]. Zenodo. https://doi.org/10.5281/zenodo.19163915
Sudheesh, A. (2022). IJML: Introduction to Julia Machine Learning using Scikit-Learn [Open Access Textbook]. https://athulsudheesh.github.io/IJML/
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