J M

Research focuses on hierarchical modeling, behavioral anchoring, and adaptive intelligence systems at the intersection of psychometrics, artificial intelligence, and computational cognition.

Background includes red team operations and government-sector research; experience in adversarial analysis, system vulnerability assessment, and behavioral modeling under uncertainty. Research approach centered on resilient, interpretable, and robust intelligent systems.

Work emphasizes experimental design and linguistic-cognitive inference; leveraging word association frameworks to generate predictive insights and structured hypothesis formation in complex environments. questions & gains; word association theory; new ideas; prediction and specific insights.

Research spans autonomous agents, embodied cognition, robotics, and machine learning, with focus on Truth Maintenance Systems (TMS/I-TMS) for dynamic belief revision in uncertain and adversarial conditions. Current work explores cognitive “DNA” architectures and epigenetic machine models for adaptive learning and representation.

Technical focus:

Parallel and distributed computation across scalable systems

Factor analysis, PCA, and stochastic modeling for latent structure discovery

Ph.D (c)

1) Researching parallelism — crucial to all layers of computing; [human] infrastructure, from smartphones, robots, to globally distributed systems. 2) Factor analysis, stochastic modeling and outliers, & Principle Component Analysis. 3) EPSRC observations in non-linear, and, linear analysis. 4) Behavioral structure - Particle Swarm Optimization; Intelligence.