IGERT trainees will each complete three team-based, four-credit training modules -- one per quarter -- starting in Winter of their first year. The training modules supplement the two required courses. They provide a quick introduction to research and a uniform preparation for trainees entering the program from diverse backgrounds into different academic departments. We encourage trainees to partner with students from a different background each quarter, and to rotate through modules from different areas of Network Science. For example, a trainee could complete a module on dynamics and control in the first quarter, on social networks in the second quarter, and the final one on Cyberinfrastructure.
Module Index
- M1: Spectral Analysis of Dynamic Graphs
- M2: Analysis of Topic Networks
- M3: Understanding Scalability of Distributed Estimation Algorithms
- M4: Analyzing the Connectome of C. elegans
- M5: Model Reduction of Biochemical Networks
- M6: Modeling Network Evolution in Metric Spaces
- M7: Discovery of the Emerging Dynamical Phenomena in Distributed Systems
- M8: Structure and Stability of Bacterial Transcription Networks
- M9: Determining Polarizing Entities and Opinions in Online Networks
- M10: Network Science of Teams
- M11: Symbolic Execution with a Graph Database
- M12: Network Stability in Food Webs
- M13: Modeling Rhetoric
- M14: An Empirical Analysis of Sexual Networks and Pregnancy in Ghana
- M15: Narrative (Counter-)Mobilizations in U.S. Same-Sex Marriage Struggle
- M16: Learning Path Generation
- M17: Models of Social Power Evolution
- M18: Speeding up graph processes on graphs embedded in latent spaces
- M19: A Privacy Model for Life Cycle Inventory Databases
- M20: Sociological Approach to Learning Path Generation
- M21: Epidemic Propagation Over Contact Networks
- M22: Information Networks in the Moral Narrative Analyzer (MoNA)
- M23: Approximate Nearest Neighbor Problem in High Dimensions with Constraints
- M24: The Value of Information in Zero-Sum Games
- M25: Modeling Gene Network Evolution
- M26: Embedding a Network into Latent Space
- M27: Understanding and Modeling Complex Network Processes
- M28: Modeling Structural Balance in Networks
- M29: FLoRa Framework
- M30: General Framework for Learning Node Embeddings
- M31: Development of a Reader Network
- M32: The Dynamics of Functional Brain Networks
- M33: First Order Linear Temporal Logic as a Query Language
- M34: Communication Across Networks and Submodular Function Maximization
- M35: A Domain-independent Framework for Learning Accurate Models from Time Varying Networks
- M36: Investigating Dynamic Frontoparietal Network Allegiance Under Cognitive and Perceptual Load
- M37: Plant Fungi Interactions
- M38: Modeling Yeast Evolution through Yeast-Fly Interactions
- M39: A Game-theoretic Approach to Mapping Optimality
- M40: Artificial Intelligence for Autonomous Interstellar Spacecraft Novelty Detection
- M41: Heterosexual network structure and experiences of sexual discrimination ...
- M42: Modeling Alzheimer’s Disease State Dynamics
- M43: Semantic Construction Through Twitter in the Colombian Peace Process
- M44: Motif distributions in daily Bitcoin transaction graphs
- M45: Predicting health scores from EEG data
- M46: Reinforcement learning for agent modeling
- M47: Visualizing Unknown Variables at Varying Scales in a GIS
- M48: Mapping slums using machine learning, remote sensing, and volunteered geographic information
- M49: A Network-based approach to the robotic simulation of bipedal locomotion
- M50: Theoretical Conditions for the Regions of Attraction in Kuramoto Systems
- M51: Interpreting Discourse in the Humanities
- M52: Using Stochastic Simulation to Inform the Design of Emergency Intervention Trials...