Kim Drnec

Innovative Human Factors Engineer and Cognitive Neuroscientist. Natural team leader, resulting in transformative Human Machine Interfaces and Human Machine Teaming solutions. Subject matter expert at knowledge elicitation and analysis, having developed a unique quantitative method of analyzing primarily qualitative data. Proven record of effective multi-disciplinary collaboration, and creative application of theory in novel ways, in fast paced, results driven environments. Passionate inquisitiveness fosters a maintenance of a state-of-the-art technical expertise in theoretical advances and evolving research questions in disparate domains. Notable cognitive flexibility permits a rapid understanding of quintessential theoretical points, and synthesis of technical material from disparate domains often resulting in new theoretical questions. Independent thinking drives initiative and willingness to take calculated risks in formulating hypotheses and designing high-risk, high-reward research programs. Proud to have led research and development of HMIs and HMTs in the DoD environment working for warfighters to keep them safe and effective. Essentially, I offer the abilities necessary to approach challenges in myriad domains in a unique way that can often result in significant leaps of progress.

1. Drnec, K., Marathe, A. R., Lukos, J. R. & Metcalfe, J. S. From Trust in Automation to Decision Neuroscience: Applying Cognitive Neuroscience Methods to Understand and Improve Interaction Decisions Involved in Human Automation Interaction. Front. Hum. Neurosci. 10, (2016).

2. Drnec, K., Marathe, A. R., Metcalfe, J. S. & Schaefer, K. The importance of psychophysiological methods in identifying and mitigating degraded situation awareness. in 2016 IEEE International Multi-Disciplinary Conference on Cognitive Methods in Situation Awareness and Decision Support (CogSIMA) 97–101 (IEEE, 2016). doi:10.1109/COGSIMA.2016.7497794.

3. Metcalfe, J. S. et al. Building a framework to manage trust in automation. in Micro- and Nanotechnology Sensors, Systems, and Applications IX vol. 10194 101941U (International Society for Optics and Photonics, 2017).

4. Gremillion, G. M. et al. Analysis of trust in autonomy for convoy operations. in Micro- and Nanotechnology Sensors, Systems, and Applications VIII vol. 9836 98361Z (International Society for Optics and Photonics, 2016).

5. Clark, R., Feldon, D., Van Merrienboer, J. J. G., Yates, K. & Early, S. Cognitive task analysis. Handbook of Research on Educational Communications and Technology 577–593 (2008).

6. Bisantz, A. M. & Vicente, K. J. Making the abstraction hierarchy concrete. International Journal of Human-Computer Studies 40, 83–117 (1994).

7. DEVCOM, A. R. L. Predicting human behavior with advanced computational neuroimaging techniques. (2000).

8. Marathe, A. R., Files, B. T., Canady, J. D. & Drnec, K. A. Heterogeneous Systems for Information-Variable Environments (HIVE). 180 (2017).

9. Drnec, K. et al. The Role of Psychophysiological Measures as Implicit Communication Within Mixed-Initiative Teams. in Virtual, Augmented and Mixed Reality: Interaction, Navigation, Visualization, Embodiment, and Simulation (eds. Chen, J. Y. C. & Fragomeni, G.) 299–313 (Springer International Publishing, 2018). doi:10.1007/978-3-319-91581-4_22.

10. Metcalfe, J., Lance, B., Marathe, A., Drnec, K. & Germillion, G. Enhancing resilience through estimating and adapting to human variability: A case study in measurement and management of trust in automation. (2015).

11. Drnec, K. & Metcalfe, J. S. Paradigm Development for Identifying and Validating Indicators of Trust in Automation in the Operational Environment of Human Automation Integration. in Foundations of Augmented Cognition: Neuroergonomics and Operational Neuroscience (eds. Schmorrow, D. D. & Fidopiastis, C. M.) 157–167 (Springer International Publishing, 2016). doi:10.1007/978-3-319-39952-2_16.

12. Rivet*, B., Souloumiac, A., Attina, V. & Gibert, G. xDAWN Algorithm to Enhance Evoked Potentials: Application to Brain–Computer Interface. IEEE Transactions on Biomedical Engineering 56, 2035–2043 (2009).

13. Drnec, K. A. Electroencephalography (EEG) and measures of nociception in cattle. (2013).

Certificate of Ethics and Law, Cambridge University, UK

• Cognitive neuroscience society (https://www.cogneurosociety.org/)
• Organization for Computational Neuroscience (https://www.cnsorg.org/)
• Society for Neuroscience (https://www.sfn.org/)
• Big Brothers and Big Sisters Organization

• USDA NIFA Grant no. 2009-65120-05791
• OHSA Educational Grant
• Golhaber Travel Grant