Robert Hubal, Ph.D.
Associate Professor
PHONE(762) 233-1763
hubal@email.unc.edu
ADDRESS
302 Pharmacy Lane, , , Chapel Hill, NC, 27599
DOWNLOAD CV
Robert Hubal has general interest in the intelligent use of technology to better train and assess knowledge and skills. He is active in projects involving areas such as adaptive learning, linguistic analysis, behavior modeling, and machine learning. He has past experience developing embodied conversational agents for interaction skills training and situated assessment; conducting cost-effectiveness studies of simulation training systems; conducting expertise, linguistic codability, and mental modeling studies; investigating adaptive intelligent tutoring; implementing patterns of life into the portrayal of activity within game-based environments; and investigating visual analytics and representation.
Hubal’s research has centered on four overlapping areas:
Technology Assisted Learning
Hubal has extensive experience in developing situated training and assessment systems, always working with subject-matter experts to design the most appropriate and focused systems. Examples include evaluating the cost-effectiveness of simulation training systems; developing adaptive intelligent tutoring; developing intelligent virtual advisors; developing an information-processing model of experts’ knowledge and skill; exploring augmented cognition and user-sensing technologies for simulation training systems.
Hubal, R.C., & Helms, R.F. (1998). Advanced learning environments. Modern Simulation & Training, 5, 40-45. ERIC Number: ED415348
Frank, G., Hubal, R., & O’Bea, M. (2007). Using competency definitions to adapt training for mission success. Proceedings of I/ITSEC (pp. 1262-1270). Arlington, VA: NDIA.
Hubal, R. (2012). The imperative for social competency prediction. In S.J. Yang, A.M. Greenberg, & M. Endsley (Eds.), Proceedings of the International Conference on Social Computing, Behavioral-Cultural Modeling, & Prediction (pp. 188-195). Heidelberg, Germany: Springer-Verlag. DOI: 10.1007/978-3-642-29047-3_23
Hubal, R., & Pina, J. (2012). Serious assessments in serious games. International Journal of Gaming and Computer-Mediated Simulations, 4(3), 49-64. DOI: 10.4018/jgcms.2012070104
Intelligent Virtual Humans
Hubal has developed behavioral software that enables virtual humans to act and behave realistically in controlled learning contexts. Applications developed include assessing medical practitioners in history taking for both asthmatic and pediatric patients; training civilian police officers in how to handle mentally disturbed individuals; training telephone and field interview staff in obtaining respondent participation. Developed virtual vignettes to assess social functioning deficits in at-risk youth. Investigated models of cultural daily activities and patterns of life integrated into simulations of intelligent virtual humans.
Hubal, R.C., Frank, G.A., & Guinn, C.I. (2003). Lessons learned in modeling schizophrenic and depressed responsive virtual humans for training. Proceedings of the Intelligent User Interface Conference (pp. 85-92). New York, NY: ACM Press. DOI: 10.1145/604045.604062
Paschall, M.J., Fishbein, D.H., Hubal, R.C., & Eldreth, D. (2005). Psychometric properties of virtual reality vignette performance measures: A novel approach for assessing adolescents’ social competency skills. Health Education Research: Theory and Practice, 20(1), 61-70. PMID: 15253996
Hubal, R.C., Fishbein, D.H., Sheppard, M.S, Paschall, M.J., Eldreth, D.L., & Hyde, C.T. (2008). How do varied populations interact with embodied conversational agents? Findings from inner-city adolescents and prisoners. Computers in Human Behavior, 24(3), 1104-1138. PMID: 19412316
Hubal, R., Folsom-Kovarik, J., Woods, A., Jones, R., & Carbone, J. (2015). Patterns of life in the foreground and background: Practical approaches to enhancing simulation-based interaction skills training. Proceedings of the Behavior Representation in Modeling and Simulation Conference (pp. 75-83). The BRIMS Society.
Healthcare Simulation
Hubal has developed a number of applications focuses specifically on medical and clinical settings. Approaches are to train clinicians on difficult content and skills, augment their practices by providing simulation environments to capture important diagnostic details, and improve patients’ understanding of processes and procedures.
Hubal, R.C., Kizakevich, P.N., Guinn, C.I., Merino, K.D., & West, S.L. (2000). The virtual standardized patient–Simulated patient-practitioner dialogue for patient interview training. Studies in Health Technology and Informatics, 70, 133-138. PMID: 10977526
Fishbein, D.H., Herman-Stahl, M., Eldreth, D.L., Paschall, M.J., Hyde, C., Hubal, R., Hubbard, S., Williams, J., & Ialongo, N. (2006). Mediators of the stress-substance use relationship in high-risk urban adolescents. Prevention Science, 7(2), 113-126. PMID: 16791520
Hubal, R.C., & Day, R.S. (2006). Informed consent procedures: An experimental test using a virtual character in a dialog systems training application. Journal of Biomedical Informatics, 39(5), 532-540. PMID: 16464644
Hourani, L.L., Kizakevich, P.N., Hubal, R., Spira, J., Strange, L.B., Holiday, D.B., Bryant, S., & McLean, A.N. (2011). Predeployment stress inoculation training for primary prevention of combat-related stress disorders. Journal of CyberTherapy & Rehabilitation, 4(1), 101-116.
Kizakevich, P.N., Hubal, R., Brown, J., Lyden, J., Spira, J., Eckhoff, R., Zhang, Y., Bryant, S., & Munoz, G. (2012). PHIT for Duty, a mobile approach for psychological health intervention. Studies in Health Technology and Informatics, 181, 268-272. PMID: 22954869
Visual Analytics, Emotion, and Representation
Hubal has investigated visual analytics, which allow for looking at data prospectively and visually. He has studied approaches to deriving mental models to ultimately develop training to encourage adaptive thinking about test, measurement, and diagnostic equipment, with the intent to develop an approach to modeling the structure and process of knowledge and skills and to determine an approach to identifying differences between experts’ models and novices’ models. Interested in modeling emotion in and extracting emotion from dialog. Developed a process model for alternative representations and investigated the interaction between expertise and representation.
Guinn, C., & Hubal, R. (2003). Extracting emotional information from the text of spoken dialog. Proceedings of the Workshop on Assessing and Adapting to User Attitudes and Affect: Why, When and How? Johnstown, PA: User Modeling, Inc. DOI: 10.1.1.119.5549
Hubal, R., Frank, G., Guinn, C., & Dupont, R. (2004). Integrating a crisis stages model into a simulation for training law enforcement officers to manage encounters with the mentally ill. In E. Hudlicka & L. Canamero (Eds.), Proceedings of the Workshop on Architectures for Modeling Emotion: Cross-Disciplinary Foundations, AAAI Spring Symposium Series (pp. 68-69). New York, NY: ACM Press.
Hubal, R., & Day, R.S. (2006). Understanding the frequency and severity of side effects: Linguistic, numeric, and visual representations. Proceedings of the Workshop on Argumentation for Consumers of Healthcare, American Association for Artificial Intelligence Spring Symposium Series (pp. 69-75). New York, NY: ACM Press.
Hubal, R.C. (2009). Mental models for effective training: Comparing expert and novice maintainers’ mental models. Research Report 1898. Arlington, VA: U.S. Army Research Institute for the Behavioral and Social Sciences.
Hubal, R., Mitroff, S.R., Cain, M.S., Scott, B., & DeWitt, R. (2010). Simulating a vigilance task: Extensible technology for baggage security assessment and training. Proceedings of the IEEE Conference on Technologies for Homeland Security (pp. 543-548). Los Alamitos, CA: IEEE. DOI: 10.1109/THS.2010.5654982
1987-1990 Andersen Consulting, New York, NY
1996-2012 RTI International, Research Triangle Park, NC
2012-2016 Soar Technology, Inc., Ann Arbor, MI
Human Factors and Ergonomics Society (HFES)
International Association of CyberPsychology, Training, and Rehabilitation (iACToR)
National Defense Industrial Association (NDIA)
Society for Simulation in Healthcare (SSIH)
Cognitive Science Society
Computers in Human Behavior
Cross-Cultural Decision-Making Conference
Human Factors and Ergonomics Society
IEEE Transactions on Learning Technologies
IEEE Visual Analytics Science and Technology (VAST) Challenge
International Conference on Intelligent User Interfaces
International Conference on Social Computing, Behavioral-Cultural Modeling, & Prediction
Journal of Biomedical Informatics
Journal of CyberTherapy & Rehabilitation
Military Medicine
Military Operational Medicine Joint Program Committee
National Institute on Mental Health
National Science Foundation
RTI Press
| TITLE | AGENCY | AWARD | DATES | ROLE |
| Responsive Virtual Human Technology | NSF | EIA-0121211 | 2001-2006 | PI |
| Neuropsychological And Emotional Deficits Predict Correctional Treatment Response | NIJ | 2002-MU-BX-0013 | 2002-2004 | Technical Lead |
| Collaborative Systems Involving Synthetic Characters And High-Risk Adolescents | NSF | IIS-0534211 | 2006-2009 | PI |
| Mental models for effective training: Comparing expert and novice maintainers’ mental models | ARI | W74V8H-04-D-0044, SubPR-04-06 | 2008-2009 | PI |
| Combat Stress Casualty Reduction: Development And Testing Of A Predeployment Stress Inoculation Training Program | ONR, USAMRMC | N00014-08-C-0504, N00014-12-C-0383 | 2008-2012 | Technical Lead |
| PHIT For Duty: A Personal Health Improvement Tool For Psychological Health & Traumatic Brain Injury | USAMRMC | W81XWH-11-2-0129 | 2011-2012 | Technical Lead |
| Cultural Urban Synthetic Characters And Their Patterns Of Life | PEO-STRI | W900KK-13-C-0053 | 2013-2014 | PI |
| AVANT: An Avatar-Based Neuropsychological Battery Administrator | TATRC | W81XWH-14-C-0016 | 2013-2016 | PI |
| CRAFT: Cognitive Resilience And Flexibility Training | ONR | N00014-15-P-1135 | 2015-2016 | Co-PI |
| INSTITUTION AND LOCATION | DEGREE | FIELD OF STUDY |
| Duke University | Ph.D. | Cognitive Psychology |
| North Carolina State University | M.S. | Computer Science |
| Massachusetts Institute of Technology | S.B. | Computer Science and Engineering |