Unique to CMU, the Decision Science BS equips you to model how people judge risks, value outcomes, and act under uncertainty. Courses span behavioral economics, cognitive modeling, and data visualization; labs test vaccine-uptake messaging with VR simulations or design debiasing tools for financial planners. Graduates become UX researchers, behavioral-insight consultants, or policy innovators armed with experiments and algorithms.
Prospect-theory parameter estimation from large-scale online gambling data
Design of choice-architecture nudges to boost renewable-energy plan adoption
VR study on spatial framing effects in evacuation route decisions
Cognitive-agent simulation of supply-chain disruptions and human mitigation tactics
Behavioral audit of fintech app defaults influencing savings rates
Eye-tracking experiment on information overload in medical consent forms
Dynamic Bayesian network predicting consumer switching in subscription services
Interactive dashboard coaching small-business owners on pricing heuristics
RCT comparing visual vs. numeric risk communication for genetic testing
Reinforcement-learning model mirroring human exploration-exploitation trade-offs
Policy brief integrating behavioral insights into wildfire evacuation messaging
Moral-dilemma game measuring value trade-offs in autonomous-vehicle ethics
Gamified training module teaching probabilistic thinking to middle-schoolers
Decision-tree analysis of venture-capital term-sheet negotiations
Forecasting tournament using Brier scores to teach calibration skills
Social-network experiment on peer effects in charitable giving cascades
Predictive model of panic-buying using sentiment analysis of social media
Evaluation of AI decision aids on physician diagnostic confidence
Agent-based model of rumor spread under varying cognitive biases
Toolkit for automatically generating debiased default options in web forms
Engineer better choices through behavioral insight and analytics at CMU.
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