Older News

May 2005

Welcome to Alex Ihler and Mike Duff who recently joined the DataLab as postdoctoral researchers. Alex received his PhD from MIT in 2005 and is working on NSF-supported research on statistical learning algorithms with applications in geoscience and biology. Mike is an NIH postdoctoral fellow and is working on algorithms for learning gene regulalatory networks.

March 2005

Congratulations to Sergey Kirshner who recently graduated with his Phd. Sergey's thesis was on new techniques for modeling time-dependent data using inhomogeneous hidden Markov models, and the application of these models to rainfall data - Sergey is continuing to work on this research as a postdoctoral fellow in the DataLab.

October 2004

The DataLab will be participating in a new NIH-funded project at UC Irvine called the Transdisciplinary Imaging Genetics Center . The research will focus on developing novel data analysis techniques for combining imaging and genetics data.

August 2004

The DataLab has received funding for a new 3-year NSF-funded research project that will investigate new mathematical models, statistical learning algorithms, and software tools for assisting scientists in analyzing complex data sets.

June 2004

Congratulations to Scott Gaffney who graduated with a Phd, with a thesis that focused on algorithms for probabilistic alignment and clustering of curve data, with applications to cyclone trajectory. Scott recently took a research position at Yahoo!.

May 2004

DataLab collaborator Suzana Camargo of the International Research Institute for Climate Prediction, Columbia University, presented new results on probabilistic clustering of Pacific cyclones, at the 26th Conference on Hurricances and Tropical Meteorology. This work uses curve clustering algorithms developed in the DataLab by recent Phd graduate Scott Gaffney.

May 2004

The DataLab group will have three papers at this year's UAI conference in Banff, Canada, in July. Postdoc Michal Rosen-Zvi, and graduate students Seyoung Kim and Sergey Kirshner, will each be presenting their research results at the conference.

March 2004

Congratulations to DataLab student Scott Gaffney, who successfully defended his Phd thesis entitled Probabilistic curve-aligned clustering and prediction with regression mixture models.

January 2004

Join us at 3:30 every Friday this quarter in CS 432 for "Tea-Time Talks", with informal 15 minute technical presentations on machine learning and related ideas, in addition to tea and cookies.

September 2003

The DataLab (in conjunction with Professor Rina Dechter and Professor Hal Stern) is sponsoring a Fall 2003 Seminar Series in AI and Statistics. Talks are every 2nd week in the Fall quarter on Tuesdays at 4pm in CS 432. See you there!

August 2003

Modeling the Internet and the Web: Probabilistic Methods and Algorithms, is a new graduate text published in June 2003 by Wiley, authored by Pierre Baldi, Paolo Frasconi, and Padhraic Smyth.

August 2003

A number of Phd students from the DataLab will be attending and presenting papers at various conference papers this summer including ICML 2003 and ACM SIGKDD 2003 in Washington DC, UAI 2003 in Acapulco, Mexico, and the Workshop on Statistical Inference, Computing and Visualization for Graphs at Stanford.

August 2003

DataLab Phd students Joshua O Madadhain and Scott White, ICS Phd student Danyel Fisher, and ICS undergraduate Yan-Biao Boey, have released JUNG (JAVA Universal Graph/Network Framework) which is an open-source Java API that provides a a common and extendible language for the modeling, analysis, and visualization of data that can be represented as a graph or network. The toolkit supports a variety of graph drawing, graph drawing, and graph data analysis algorithms.

July 2003

Professor David Van Dyk has just joined the new UCI Statistics Department from Harvard and teams up with Professor and Chair Hal Stern in the new department. David's research interests are in computational statistics, the EM algorithms, Bayesian statistics, hierarchical models, mixture models, and related areas and applications.

September 2002

There are 2 new seminar series related to machine learning and data mining that the DataLab is helping to organize - please feel free to attend!

The 2002-2003 Large-Scale Data Analysis Seminar Series is underway, with an exciting line-up of speakers. This series is jointly sponsored by the DataLab, the ICS Department, and the newly-founded Department of Statistics at UCI.

The departmental AI/Machine Learning Seminar Series has weekly talks every Thursday at 4pm in ICS 432.

December 2002

Congratulations to Xianping Ge, who graduated with a Ph.D. in December 2002 and took a position at Google.

July 2002

Dasha Chudova received the best research paper award at the Eighth International ACM Conference on Knowledge Discovery and Data Mining, July 2002, for the paper Pattern discovery in sequences under a Markov assumption , jointly authored with Padhraic Smyth.

June 2002

Congratulations to Dima Pavlov and Igor Cadez who received their Phds in the Information and Computer Science department at UCI in June 2002, and are the first Phd students to graduate from the DataLab.

June 2001

The 33rd Symposium on the Interface of Computer Science and Statistics was held near the UCI campus, June 13th-16th, 2001, and there was an exciting program of talks and events. The DataLab helped to organize this meeting in terms of the program, planning, Web support, and other activities.

March 2001

Xianping Ge, Phd student in the DataLab, was awarded an IBM Graduate Fellowship (March 2001).

March 2001

The DataLab was awarded a new 3-year NSF grant for research on Digital Behavior

October 2000

Igor Cadez, Phd student in the DataLab, was awarded a Microsoft Research Fellowship.

September 2000

Xianping Ge received an outstanding paper award at the annual AEC/APC Symposium for his paper (with Padhraic Smyth) on the application of hidden Markov models to end-point detection in semiconductor process data.

August 2000

The paper by Ge and Smyth on segmental hidden Markov models received the runner-up award for best research paper at the Sixth ACM SIGKDD Conference.