Decision Science and Control (DeSCon) Lab
We study the fundamental mathematics of interactive decision-making,
applied to a variety of contexts including infrastructure
optimization, epidemiology, and the distributed control of multiagent
systems.
Current Projects
- Socially-Networked Autonomy: How Should Machines
Interact With Society?
This NSF-funded
project studies decision design methodologies for autonomous
agents that are networked with and interacting among human beings
in societal systems. The core question is this: how should a
system planner design the routing policies of autonomous vehicles
to have the greatest positive impact on overall network traffic
congestion, even if human drivers react in a self-interested way
to the behavior of the autonomous vehicles? Supported by NSF
ECCS 2013779.
- Optimizing the Life-Cycle Impacts of COVID-19 Policy
Interventions. This project asks how leaders can make
public policy decisions regarding the COVID-19 pandemic in a
scientific way that is locally appropriate and properly accounts
for both near-term and longer-term costs of policy interventions.
This project combines rigorous mathematical modeling, innovative
approaches to data collection, and input from policymakers, to
develop a decision aid framework that weighs the costs and
benefits of various policy interventions at a local level and
tailors interventions to the locale considering the effects of
specific indicators such as urbanization, economic distress, and
availability of regional healthcare. Supported by NSF
DEB 2032465.
- Value-based Access Control System using Path Security
(with PI Dr.
Gedare Bloom). This NSA-funded project investigates novel
theories, policies, and mechanisms for access control that
presumes client credentials are inherently risky. Our approach
relies on state-of-the-art advances being made in path-based
security for Internet routing. The focus of path-based mechanisms
is to enable path selection by senders and path validation back to
the sender (source) by intermediate routers and the destination.
Our objective is to design, implement, and enforce higher-level
access control decisions built upon this baseline to protect
digital assets within the (destination) network from malicious
source nodes that can pass traditional user authentication
mechanisms due to stolen credentials.
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Current Graduate Students
- Joshua Seaton 2019-Present
- Pam Russell 2019-Present
- Brandon Collins 2020-Present
- Colton Hill 2021-Present
- Will Wesley 2022-Present
Current Undergraduate Researchers
- Brendan Gould, 2021-Present
- Sonia Karsanbhai, 2021-Present
Past Masters Thesis Students
- Ryan Young, 2020, First employment: The MITRE Corporation
- Joshua Seaton, 2021. First employment: DeSCon
Lab
Past Undergraduate Researchers
- Brandon Collins, 2018-2020. First employment: DeSCon
Lab
- Joseph Mazzocco, 2019. First employment: Raytheon