Michael Hahsler

Michael Hahsler
Dept. of Engineering Management, Information, and Systems
Dept. of Computer Science and Engineering
Bobby B. Lyle School of Engineering, SMU
P. O. Box 750123, Dallas, TX 75275

office: Caruth Hall, suite 337, room 311
office phone: (214) 768-8878
office hours: TTh 12:30-2:00 p.m. or by appointment
e-mail: mhahsler (at) lyle.smu.edu

I am Assistant Professor of Engineering Management, Information, and Systems (EMIS) and (by courtesy) Computer Science and Engineering (CSE) at the Bobby B. Lyle School of Engineering, Southern Methodist University. I also serve as Director of the Intelligent Data Analysis Lab (IDA@SMU). Prior to this engagement I was Assistant Professor at the Department of Information Systems and Operations and a Core Researcher at the Research Institute for Computational Methods, both at the Vienna University of Economics and Business, Austria.

My research is focused on applying statistical methods and combinatorial optimization to data analysis, data mining, data visualization and analytics. My team's current research projects are “Temporal Relationships Among Clusters in Data Streams (TRACDS)” (NSF IIS-0948893) and “Position Sensitive P-Mer Frequency Clustering with Application to Classification and Differentiation” (NIH R21HG005912). Our research on hurricane intensity prediction was featured in the article “Discovery: New Forecasting Algorithm Helps Predict Hurricane Intensity and Wind Speed” (Dec. 5, 2011) by the National Science Foundation.

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Teaching

Spring 2013 courses
- Hahsler, M., "EMIS 2360: Engineering Economy", Lyle School of Engineering, SMU.
- Hahsler, M., "EMIS 5/7390 & CSE 5/7331: Introduction to Data Mining", Lyle School of Engineering, SMU.
All lecture notes

Research

Research interests
- Data mining and business analytics: Recommender systems, association rule mining and data stream clustering
- Data visualization: Based on seriation (combinatorial optimization)
- Bioinformatics: Sequence alignment methods
- Digital information management: Digital and virtual libraries
- Software engineering: Reuse and design patterns
Publications and presentations
Current research projects
- TRACDS: Temporal Relationships Among Clusters in Data Streams funded by NSF (IIS-0948893).
- QuasiAlign: Position Sensitive P-Mer Frequency Clustering with Application to Classification and Differentiation funded by NIH (R21HG005912).
Current and graduated students
Service to the scientific community

Software

Association Rule Mining
- arules: A package for mining association rules and frequent itemsets. [ CRAN | R-Forge | description ]
- arulesViz: A package for visualizing association rules based on package arules. [ CRAN | R-Forge | description ]
- arulesSequences: Add-on for arules to handle and mine frequent sequences. [ CRAN ]
- arulesNBMiner: Add-on for arules to mine NB-frequent itemsets (see paper) and NB-precise rules. [ CRAN | R-Forge ]
Data Stream Mining
- rEMM: Implementation of the Extensible Markov Model (EMM) which adds a temporal component to data stream clustering by superimposing a dynamically adapting Markov Chain. This research is supported by NSF Grant 0948893. [ CRAN | R-Forge | description ]
- stream: Infrastructure for data stream mining. [ CRAN | R-Forge | description ]
Bioinformatics
- QuasiAlign: Efficient sequence alignment using alignment-free methods. [ R-Forge ]
- RAlign: Interfaces several popular tools for sequence alignment (clustalw, kalign), data base search (BLAST) and classification (rdp). [ R-Forge (subproject of QuasiAlign) ]
Combinatorial Optimization
- seriation: Infrastructure for seriation with an implementation of several seriation/sequencing techniques to reorder matrices, dissimilarity matrices, and dendrograms. [ CRAN | R-Forge | description ]
- TSP: Basic infrastructure and some algorithms for the traveling salesperson problem (TSP). The package provides some simple algorithms and an interface to Concorde, currently the fastest TSP solver for the Traveling Salesperson Problem. [ CRAN | R-Forge | description ]
Recommender Systems
- recommenderlab: Provides the infrastructure to test and develop recommender algorithms. Currently the focus is on recommender systems for binary data. [ CRAN | R-Forge | description ]

Miscellaneous

Gridhunt2: a small game used to teach students basic OO concepts (encapsulation, composition, inheritance and polymorphism) using C++.
pix2tn: A simple thumbnail generator implemented in Perl.
Find me in: google, google scholar, ACM DL, MS Academic Research, arnetminer, dblp, launchpad, linkedin, mendeley, R-forge