Program

Wednesday, October 10

8:00-8:30 Morning Coffee  
8:30 - 8:45 Welcome    
8:45 - 10:00 Networks 1  
  Kevin Xu The Block Point Process Model for Continuous-time Event-Based Dynamic Networks
  Haiyan Wang Combining network theory and partial differential equation to improve influenza predictions
  Yajun Mei Adaptive and Rapid Spatial-Temporal Threat Detection Over Networks
  Abel Rodriguez A Record Linkage Model Incorporating Relational Data
10:00-10:30 Coffee Break  
10:30-12:00 Applications  
  Jeffrey Brantingham My Crime Problem is Not Like Your Crime Problem
  Ansu Chatterjee Bayesian supervised learning from social unrest data with measurement errors and  nonignorable missing values
  Robert McAndrew Modeling internet anomalies arrivals with a new class of Hawkes processes
  Peter Chin Spectral and Differential Geometric Understing of Graphs and its Applications
  Andrea Bertozzi Levy Flights, Truncated Levy Flights, and finite size effects in residential burglary models
12:00-1:00 Lunch  
1:00-2:30 Methodology 1   
  James Murphy Unsupervised Geometric Learning: Theory and Applications
  Haomin Zhou Optimal Transport on Graphs with Applications
  Thomas Strohmer Compressive Deep Learning on Constrained Devices
  Rong Chen iGroup: Statistical inference based on individualized grouping  
  Qiang Qiu Regularized Deep Learning with Geometry and Structures
2:30-2:45 Coffee Break  
2:45-4:15 Networks 2  
  Jie Gao Discrete Ollivier Ricci Flow for Community Detection on Networks
  Chinmay Hegde Event Detection in Networks using Steiner Tree Methods
  Vince Poor What Do Network Motifs Tell Us about Robustness and Reliability of Complex Networks?
  James Wilson Dynamic network monitoring using random graph theory and statistical process monitoring
  George Michailidis Estimation of Change Points in Temporally Evolving Networks
4:15-4:30 Coffee Break  
4:30-5:00 Data challenges  
  Joseph Chang A Set of Data Association Challenge Problems for Algorithms for Threat Detection Program
  Dimitris Manolakis Event Detection in Time Series:  A Traffic Data Challenge

Thursday, October 11

8:15-8:45 Morning Coffee  
8:45-10:00 Methodology 2  
  Shannon Stiverson Clustering Algorithms on the Grassmann Manifold with Applications 
  Latifur Khan Multistream Regression and Classification
  Guanqun Cao M-based simultaneous inference for the mean function of functional data
  Elchanan Mossel Being Corrupt Requires Being Clever, But Detecting Corruption Doesn't
10:00-10:30 Coffee Break  
10:30-12:00 Time-dependent modeling
  Yao Xie Sequential learning of temporal point processes
  Austin Benson Sampling methods for counting temporal motifs
  Shyam Ranganathan Forecasting threats due to polarization using spatio-temporal topic flows
  Michael Baron Change-point detection in geospatial sequences of social events
  George Mohler Spatial ranking, embedding, and interventions for heterogenous human activity data
12:00-1:15 Lunch    
1:15-2:30 Joint session  
  Alexander Vladimirsky Time-dependent Surveillance-Evasion Games Under Uncertainty.
  Georgios Fellouris Sequential change detection and control
  Maxim Bichuch Optimal Electricity Distribution Pricing under Risk and High Photovoltaics Penetration
  Barry Lee Multigrid Coarse-Graining of Dynamical Power Grid Models
2:30-2:45 Coffee Break  
2:45-4:00 Poster Highlights - Lighting Talks
4:00-6:00 Poster Session (joint with AMPS)
ATD Anna Aboud A Dual Kaczmarz Algorithm
  Benjamin Bagozzi Predicting violence with big data
  Chencheng Cai TBD
  Elliot Cartee Surveillance-Evasion Mean Field Games
  Shen-Shyang Ho A Martingale-based Approach for Flight Behavior Anomaly Detection
  Michael Kallitsis Detection and Identification of Anomalies in Network Streams
  Bumsu Kim Dynamic Topic Modeling: Spatiotemporal Analysis of Los Angeles Twitter Data
  Hao Li Nonparametric Self-exciting Processes and Network Reconstruction
  Shuang Li Learning point processes via reinforcement learning
  Yang Li Proximity condition for SDP relaxation of k-means
  Markus Plack Dynamic Topic Modeling: Spatiotemporal Analysis of Los Angeles Twitter Data
  Aviva Prins Analyzing Youth Program Effectiveness in Gang Reduction Using Dynamic Mode Decomposition
  Yanglei Song Asymptotically optimal sequential multiple testing
  Stilian Stoev Detection and Identification of Anomalies in Network Streams
  Xuetong Sun Conflict Analytics: A data-driven approach for understanding and predicting violence
  Selena Shuo  Wang Latent space models for heterogeneous multi-mode networks
  Haoyan Zhai Path Planning in Unknown Environments Using Optimal Transport Theory
  Yujie Zhao Rapid Detection of Sparse and Temporal-consistent Hot-spot
  Shixiang Zhu Crime Series Detection from Large-Scale Police Report Data
  Dongmian Zou Graph Convolutional Neural Network via Scattering
AMPS Guanqun Cao M-based simultaneous inference for the mean function of functional data
  Julio Castrillon Stochastic Collocation and Analytic Regularity of High Dimensional Power Networks
  Yixiang Deng TBD
  Asim Dey Development of synthetic power grid networks
  Yonatan Dukler Motif Based Structural Graph Convolutional Nets For Network Embeddings
  Xiaoyuan Fan TBD
  Aditya Maheshwari Regression Monte Carlo for microgrid management
  Enrique Mallada TBD
  Enrique Pereira Batista Mulrigrid for the Solution of Nonlinear Power Flow Equations
  April Sagan A Decentralized Matrix Completion Algorithm for Voltage Estimation
  Yixuan Sun Local Feature Sufficiency Exploration for Preventive Security-constrained Optimal Power Flow Dispatch Considering Multiple Areas