1. What Else is Important in AI we Did not Cover?
Ontologies and the Semantic Web
Logical Reasoning and Theorem Proving
Distributed Artificial Intelligence
Multi-Agent Systems
Robotics
Philosophical Foundation of AI
Natural Language Understanding
Knowledge in Learning
UH-DAIS

2. 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

3. Looking for 1-2 Students for Master Thesis
Students should begin working on their thesis Jan. 16 or May 31, 2017: Areas of Interest include:
Spatio-Temporal Clustering, Interestingness Hotspot Discovery, and Change Analysis in Spatial Datasets
Design and Implementation of a Water Level Prediction and Flood Warning System for Harris County
Disaster Computing—Using AI Planning for Absorbing and Recovering from Critical Component Failures, starting May 31, 2016.
Educational Data Mining: Early Warning System for Failing Students/Student Self-Assessment System
Event Detection in Spatio-temporal Datasets already gone!
If you are interested, send me an by December 31, 2016, and I will be selecting students by January 15, Send me an , even if you want to start June 1, 2017!
UH-DAIS

4. Interestingness Hotspot Discovery Framework
Objectives
Identify hotspot seeds
Grow hotspot seeds by adding neighboring objects
Remove redundant hotspots using a graph-based approach
Find scope of hotspots
Find interesting contiguous regions in spatial data sets based on the domain expert’s notion of interestingness which is captured in an interestingness function
Allow plugin interestingness functions to be used
with point based, polygonal or gridded datasets
Remove redundant overlapping hotspots
and find the scope of each hotspot.
Develop algorithms to create neighborhood graph
for point based datasets.
By Fatih Akdag and Christoph F. Eick
Air pollution dataset low-variation hotspots
Earthquake dataset correlation hotspots
Point-based and Polygonal datasets
Gridded dataset

5. 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

6. 1d: Spatio-temporal Event Detection
Example: Event Detection System Architecture

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