Enhanced Computational Modeling of Human Navigation in Urbanized Environments Fellowship
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Research Topic Description, including Problem Statement:
An extensive body of work has sought to model the navigational modalities of human beings in urbanized environments by leveraging agent-based computational modeling (ABM) techniques. However, this literature has assumed simple travel distance cost-optimization strategies, encoded in the decision-rules followed by individual model agents (cf. the canonical Dijkstra algorithm). Recent, groundbreaking research leveraging anonymized en masse data collection has revealed that human beings rather employ more complex decision-rules in their navigational choices.
This project seeks to address the problem: how can we more accurately model human navigation to better inform large-scale models of human mobility in urbanized environments? The project will support development of novel computational approaches that more accurately reproduce real-world navigational choices now revealed in empirical data. Candidates for consideration will demonstrate deep competence in large-scale modeling of human mobility in urbanized environments, leveraging advanced computational techniques.
Example Approaches:
Empirically-informed large-scale agent-based computational modeling of human mobility in urbanized environments, leveraging research-grade high-performance computing resources for model development, testing and evaluation.
Relevance to the Intelligence Community:
DNI Priority 4: Promoting expertise, data, science, and innovation. Drawing on external and internal expertise, developing new expertise, consistently promoting knowledge as a resource and underlying on evidence-driven insights to innovate.
IC STG Goal 4: Create the Future Operational Landscape. Find, create, and deploy scientific discoveries and new technologies, nurturing innovative thought, advancing tradecraft, and improving mission and business processes.
Identified IC S&T Needs addressed by the proposed work are:
- Develop/enhance theoretical concepts related to activity-based intelligence.
- Develop/enhance computational methods for analysis of geospatial information to detect anomalies.
- Develop/enhance computational methods related to the interdisciplinary field of human geography for discovery of complex patterns and processes.
- Develop/enhance capabilities to flag anomalies within massive data sets.
Key Words: human mobility, human navigation, human trajectory analysis, agent-based modeling.
Postdoc Eligibility
- U.S. citizens only
- Ph.D. in a relevant field must be completed before beginning the appointment and within five years of the appointment start date
- Proposal must be associated with an accredited U.S. university, college, or U.S. government laboratory
- Eligible candidates may only receive one award from the IC Postdoctoral Research Fellowship Program
Research Advisor Eligibility
- Must be an employee of an accredited U.S. university, college or U.S. government laboratory
- Are not required to be U.S. citizens
- Citizenship: U.S. Citizen Only
- Degree: Doctoral Degree.
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Discipline(s):
- Chemistry and Materials Sciences (12 )
- Communications and Graphics Design (4 )
- Computer, Information, and Data Sciences (17 )
- Earth and Geosciences (21 )
- Engineering (27 )
- Environmental and Marine Sciences (14 )
- Life Health and Medical Sciences (46 )
- Mathematics and Statistics (11 )
- Other Non-Science & Engineering (2 )
- Physics (16 )
- Science & Engineering-related (1 )
- Social and Behavioral Sciences (30 )
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