Zhenzhen Wang

Profile

Professor in the School of Software Engineering at Jinling Institute of Technology, Nanjing, China. PhD in Computer Software Theory and Application, Southeast University, Nanjing, China (2009). Postdoctoral researcher in the Department of Computer Science at Nanjing University (2009–2012).

Research interests include Markov decision processes, preference modelling, swarm intelligence, human cognition, and software testing. Author of over 50 peer-reviewed journal and conference papers, and two books: Thinking Model of Cognitive Behavior and Software Testing: Principles, Models, Verification and Practice.

I am currently a Visiting Scholar at the University of Reading, hosted by Prof. Slawomir J. Nasuto in the Brain Embodiment Lab. My research is on Stochastic Modeling of Human Decision-Making and Cognitive Behavior.

Research

My research focuses on developing formal mathematical and computational models to understand the mechanisms underlying human cognition, inspiration, and decision-making.

One line of my work is the development of a novel measure-valued Markov decision process (MV-MDP) framework, in which cognition is modeled as a probabilistic distribution over the state space rather than a point-based transition system. This approach captures the “area-like” exploratory nature of human thinking, incorporating not only logical reasoning but also intuition, estimation, and pre-articulated mental states. The framework also incorporates anticipatory decision-making, where expected future outcomes influence present choices.

Additional work explores simplified and cognitively grounded models of fuzzy reasoning, proposing naïve constructions of membership functions that reflect key characteristics of human thinking, such as limited cognitive capacity and hierarchical reasoning structures.

Overall, this work explores frameworks that integrate stochastic processes, such as Brownian motion and measure-valued models, with decision-theoretic structures like generalized Markov decision processes, trying to capture the interaction between conscious and unconscious thinking.

This research aims to bridge mathematical modeling, cognitive science, and artificial intelligence, providing new insights into how inspiration arises and how human-like intelligence can be formally represented and simulated. This research is conducted in collaboration with Prof. Slawomir J. Nasuto at the University of Reading.