1. Data Analysis and Intelligent Systems Lab
Its research is focusing on:
Spatial Data Mining
Clustering and Anomaly Detection
Classification and Prediction
GIS
Current Projects
Clustering Algorithms with Plug-in Fitness Functions and Other Non-Traditional Clustering Approaches
Analyzing and Doing Useful Things with Bio-aerosol Data
Interestingness Scoping Algorithms for the Analysis of Spatial and Spatio-temporal Datasets
Using Mixture Models for Anomaly Detection and Change Analysis
Taxonomy Generation—Learning Class Hierarchies from Training Data
Educational Data Mining (lead by Nouhad Rizk)
UH-DAIS

2. Research Areas and Projects
Data Analysis and Intelligent Systems Lab (UH-DAIS)
Its research is focusing on:
Data Mining
Data Science and Making Sense of Data
GIS (Geographical Information Systems)
AI (Artificial Intelligence)
2. Current and Planned Projects
Clustering Algorithms with Plug-in Fitness Functions, other Non-Traditional Clustering and Hotspot Discovery (HD) Approaches
Predicting and Understanding Flooding
Educational Data Mining (jointly with Nouhad Rizk)
Taxonomy Generation—Learning Class Hierarchies from Training Data
Fast Execution Frameworks for Agglomerative Algorithms just starting
Critical Infrastructure Resilience
More AI-related research projects: particularly Planning, and maybe Internet of Things and Games looking for new students!
UH-DAIS

3. 1b. Interestingness Hotspot Discovery
Objective: Find interesting contiguous regions in spatial data sets based on the domain expert’s notion of interestingness which is captured in an interestingness function
Methodology:
Identify hotspot seeds
Grow seeds by adding neighboring objects
Remove redundant hotspots using a graph-based approach
Find Scope of hotspots (polygonal boundary detection)
Data sets: Gridded, polygonal, point-based data sets
People: Fatih Akdag

4. 1.c Spatio-Temporal Clustering
Remark: Future Research will also investigate Spatio-Temporal Event Detection
Analyzing NYC Cab Pickup Data
People: Yongli Zhang and Karima Elgarroussi
UH-DAIS

5. 2. Predicting, Mapping, Understanding Flooding
ResearchTasks:
Predict Water Levels
Flood Vulnerability Mapping
Development of Flood Plans
Understand Causes of Flooding
People: Christariny Hutapea, Chong Wang, Yongli Zhang and Yue Cao
UH-DAIS

6. 3. Educational Data Mining (EDM)
People: Nouhad Rizk, Karthik Bibireddy, Rohith Jidagam and Alex Lam
UH-DMML

7. 6. Dr. Eick’s Resilience Work
In 2015, I was the PI of a large funded DHS project in which we designed an early warning system for bio-threats using “cheap” biosensors.
I am part of a large research group at UH whose research centers on “Making the Houston Harbor Smart and Resilient”.
Disaster analytics and understanding what makes communities resilient to absorb and recover from disasters.
Moreover, my research group is starting new research in critical infrastructure and community resilience that employs artificial intelligence planning techniques to come up with plans that absorb or recover from failure of critical components.
UH-DAIS