1. Data-Driven Decision-Making
DEPARTMENT OF ENGINEERING MANAGEMENT AND SYSTEMS ENGINEERING
Data-Driven Decision-Making
Use Decision Science to develop human-centered approaches for big data and autonomous systems.
Grid Modernization,
Model and Simulate Socio-technical Systems
Perform risk, cost-benefit, uncertainty, sensitivity analysis
Predict impacts of behavioral interventions on system
Quantify Human Components of Complex Systems
Measure attitudes, risk perceptions, and perceptual abilities in the context of new technology and data access
Test Decision-Making Interventions
Design and assess randomized control trials to test human- computer interfaces, risk communications, and trainings in the lab and field
Evaluate Program Impacts
Use quasi-experimental techniques to evaluate the impact of government and industry programs to facilitate evidence- based decision-making
PoC: Casey Canfield, PhD Assistant Professor,
Engineering Management & Systems Eng.
BS Engineering: Systems, Franklin W. Olin College of Engineering PhD Engineering & Public Policy, Carnegie Mellon University
Autonomous Vehicles, Human-Machine Teams
Microgrid Operation
Technology
Process
People
Smart Communities, Data Governance
Keywords
Human Systems Integration, Evidence-Based Decision-Making, Randomized Control Trials, Smart Cities, Grid Modernization, Automation, Risk Analysis, Policy Analysis, Stakeholder Engagement
Recognitions
NSF Graduate Research Fellowship,
Society for Risk Analysis Security & Defense Student Merit Award,
Best Proposal, DOE Better Buildings Case Competition, 2014
CEC Research