Priyam Das

Priyam Das is a cognitive scientist and recent PhD graduate from the University of California, Irvine (2024). Their research focuses on cognitive aging, cognitive training efficacy, and the application of behavioral science to educational technologies. They hold a BA in Cognitive Science from UC Berkeley (2018).

Key research interests include understanding how aging impacts learning processes, designing interventions to bridge age-related cognitive performance gaps, and leveraging AI for optimizing human decision-making. Notable projects involve analyzing Lumosity user data to study extended practice effects in older adults and developing cognitive tutors to combat present bias in planning behaviors.

Priyam has contributed to 10 peer-reviewed publications between 2018-2024, with a focus on adaptive learning strategies, resource-rational planning models, and cognitive training methodologies. Their work integrates behavioral experiments, computational modeling, and data-driven educational tools.

Technical skills include proficiency in Python (NumPy/SciPy/pandas), Jupyter workflows, and web-based experimental design (JavaScript/HTML/CSS). They are an active GitHub contributor with repositories showcasing behavioral science experiments and data analysis pipelines.

Labs/Teams: Collaborates with MADLABatUCI on skilled decision-making tasks and contributed to the LASER Institute's educational research initiatives.