Fellow
"My core contribution to the platform focused on Domain-Specific RLHF (Reinforcement Learning from Human Feedback) and adversarial AI Red Teaming within creative media and user interface ecosystems. Leveraging a multi-decade background in instructional design and advanced digital asset production, I executed high-level model alignment tasks by stress-testing advanced generative engines for architectural and geometric vulnerabilities. This included crafting complex, highly constrained prompt matrices to identify and isolate instances of spatial coherence drift—such as linear perspective distortion on horizontal ground planes—and engineered precise, human-in-the-loop ground-truth calibration data to correct these structural errors. Furthermore, my work encompassed evaluating complex, nested user interface hierarchies to train multimodal systems on dynamic micro-interactions, dropdown occlusion parameters, and translucent UI elements, directly improving model reasoning and compliance across specialized, cross-modal datasets."