Dr. Lusine Mkrtchyan

Since March 2018 Lusine Mkrtchyan works as a postdoctoral researcher in the University of Luzern. Her work is focused on the methodological and technical advancements of configurational comparative research methods to be applied for a Swiss National Science Foundation project ACCORds supervised by Professor Alrik Thiem. Currently she studies different minimization algorithms and their potential use for qualitative comparative analysis. She is also interested in sequential complex causal structures to incorporate the temporal dimension in QCA methods by means of analyzing not only the order of causal conditions but also the previous states of certain conditions (having more dynamic nature). As in her previous research at ETH Zurich and Paul Scherrer Institute, she worked on probabilistic modelling (Bayesian Belief Networks) and fuzzy logic applications, a part of her research will be dedicated to studying the relationships of QCA and other cross-disciplinary methods.     

Selected Publications

Mkrtchyan, L., Podofillini, L., & Dang, V. N. (2016). Methods for building conditional probability tables of bayesian belief networks from limited judgment: an evaluation for human reliability application. Reliability Engineering & System Safety, 151, 93-112.

Mkrtchyan, L., Podofillini, L., & Dang, V. N. (2015). Bayesian belief networks for human reliability analysis: A review of applications and gaps. Reliability engineering & system safety, 139, 1-16.

Baraldi, P., Podofillini, L., Mkrtchyan, L., Zio, E., & Dang, V. N. (2015). Comparing the treatment of uncertainty in Bayesian networks and fuzzy expert systems used for a human reliability analysis application. Reliability Engineering & System Safety, 138, 176-193.

Lazzerini, B., & Mkrtchyan, L. (2011). Analyzing risk impact factors using extended fuzzy cognitive maps. IEEE Systems Journal, 5(2), 288-297.

Turcanu, C., Mkrtchyan, L., Nagy, A., & Faure, P. (2015). Can belief structures improve our understanding of safety climate survey data? International Journal of Approximate Reasoning, 66, 103-118.

Mkrtchyan, L., León, M., Depaire, B., Ruan, D., & Vanhoof, K. (2012). Clustering of fuzzy cognitive maps for travel behavior analysis. In Management Intelligent Systems (pp. 57-66).