Dr. Richard M. Golden

Dr. Golden’s current research area is the development and evaluation of principled measurement methodologies for assessing human knowledge, learning, reasoning, and problem solving. Such measurement methodologies include: Bayesian networks in Educational Assessment, Computational Psychometrics, Statistical Machine Learning. Measurement methodologies are evaluated using both new and archival data from classroom environments, intelligent tutoring environments, and augmented/virtual reality environments.

In addition, to support the development of such measurement methodologies, Dr. Golden’s research interests include developing new methods for estimation, inference, model selection, and model misspecification detection using asymptotic statistical theory.

Dr. Golden received his BS in both electrical engineering and psychology from the University of California at San Diego.  Dr. Golden received his MS in electrical engineering and his PhD in experimental psychology as a graduate student in the lab of Dr. James A. Anderson at Brown University. During the time period 1986-1987, Dr. Golden was an Andrew Mellon Fellow at the University of Pittsburgh Learning, Research, and Development Center (LRDC). From 1987-1990, Dr. Golden was an NIH Postdoctoral Scholar in Dr. David E. Rumelhart’s lab at Stanford University.

Athul Sudheesh

Athul is the cofounder of COINS Lab along with Dr. Richard M. Golden.

Athul is an engineer turned researcher with 8+ years of experience in Statistical Machine Learning. He joined the Cognition & Neuroscience PhD program in 2019 and specializes in Probabilistic Graphical Models, Causal Machine Learning, and Bayesian Modeling. For his thesis project, Athul developed a novel theoretical framework for building and testing causal theories of student learning and is investigating how student engagement impacts their assessment performance in intelligent tutoring systems. Athul’s broader research interests include investigating the cognitive and metacognitive factors affecting learning in adults, as well as measurement and modeling issues in educational assessments. He’s also an expert in research software development and has published several open-source software packages for COINS Lab.

Athul is also the recipient of Matthew K. Weddle Fellowship in Cognition & Neuroscience and Bio-Behavioral Sciences Research Award at UT Dallas.

Ritesh Malaiya

Ritesh is a PhD student in cognition and Neuroscience. He has a master’s degree in applied cognition and neuroscience from The University of Texas at Dallas and a bachelor’s degree in computer engineering from Bharati Vidyapeeth University, Pune, India. He is interested in Educational Psychology and Computational Psychometrics research areas. He has worked as a Data Scientist in Banking domain and as a Software Development Engineer in Retail domain working mostly towards building backend algorithms to support Business processes.

Currently, in COINS lab, he is involved in developing probabilistic models to capture the evolution of students skills as they progress through the semester.

Reyhaneh Hosseinpour

Reyhaneh is a PhD student in the Cognition and Neuroscience program, with a bachelor’s degree in statistics from Shahid Beheshti University in Tehran, Iran. Her studies concentrate on Educational Psychology and Computational methods. Her research includes creating techniques for detecting model misspecification in Cognitive Diagnostic Models using Information Matrix Test methods. Additionally, she is actively engaged in research on clinical reasoning within augmented reality learning environments, aiming to improve training and assessment strategies for health professionals to ensure they provide the highest quality of patient care in digital health education.

Hima Praveen

Hima Praveen is an undergraduate Cognitive Science major. Hima is working on the application of Cognitive Diagnostic Models to assessment of medical students in an augmented reality environment.

Suvel Muttreja

Suvel Muttreja is an undergraduate Cognitive Science major. Suvel is working on integrating Natural Language Processing machine learning algorithms to support the assessment of medical students in an augmented reality environment.

Jeremy Gelwix

Jeremy Gelwix is currently a graduate student in the Applied Cognition and Neuroscience program at UTD. Jeremy is working on an intelligent graphical user interface to support expert knowledge solicitation to support Cognitive Diagnostic Modeling.

Dona Lontok

Dona Lontok is currently a graduate student in the Applied Cognition and Neuroscience program at UTD. Dona working on integrating Natural Language Processing machine learning algorithms to support the assessment of medical students in an augmented reality environment.

Wei Chen (Wade) Huang

Wade is currently a graduate student in the Applied Cognition and Neuroscience program at UTD. Wade is working on integrating Natural Language Processing machine learning algorithms to support the assessment of medical students in an augmented reality environment.

Suryoun (Chrissy) Lee

Chrissy is currently a graduate student in the Computer Engineering program at UTD. Chrissy is working on integrating Natural Language Processing machine learning algorithms and emotion detection to support the assessment of medical students in an augmented reality environment.

Kaitlyn Endres

Kaitlyn is currently a graduate student in the Applied Cognition and Neuroscience program at UTD. Kaitlyn is working on the integration of Artificial Intelligence Natural Language Processing algorithms into the process of assessing medical students in an augmented reality environment.

Rohan Vishal Rachamadugu

Rohan Rachamadugu is a graduate student in Computer Science at UTD. Rohan is working on causal inference in Bayesian networks using ASSISTMENTS data.

Sanjana Kotha

Sanjana Kotha is currently an undergraduate Computer Science major. Sanjana is working on the integration of Artificial Intelligence Natural Language Processing algorithms into the process of assessing medical students in an augmented reality environment.