Environmental and Industrial Machine Learning Group
News
02 Apr 2011: Papers accepted at ESANN'11
Congratulations for the following papers which have been accepted at ESANN'11: (1) Federico Montesino Pouzols and Amaury Lendasse, "Adaptive Kernel Smoothing Regression for Spatio-Temporal Environmental Datasets" and (2) Li Yao, Amaury Lendasse and Francesco Corona, "Locating Anomalies Using Bayesian Factorizations and Masks".
02 Apr 2011: Paper accepted at ICANN'11
Congratulations to Dusan Sovilj. His paper entitled "Multistart Strategy using Delta Test for Variable Selection" has been accepted to ICANN'11.
02 May 2010: DMIN'10
Laura Kainulainen is awarded a full DMIN’10 student sponsorship! Congratulations to Laura and thanks again to DMIN'10 organizers.
21 Apr 2010: Paper accepted at DMIN'10
Congratulations to Laura Kainulainen, Qi Yu, Yoan Miche, Emil Eirola, Eric Severin and Amaury Momo Lendasse for their paper accepted to DMIN'10 as a Regular Research Paper (publication in the proceedings and oral formal presentation). Title: Ensembles of Locally Linear Models: Application to Bankruptcy Prediction.
06 Mar 2010: Qi Yu
We are happy to tell that Qi Yu gave birth to a beautiful baby. Congratulations to the mother and the father.
Environmental and Industrial Machine Learning Group
The Environmental and Industrial Machine Learning (EIML) group is a sub-group of the Adaptive Informatics Applications (AIA) group. It is part of both the Department of Information and Computer Science and the Adaptive Informatics Research Centre, Centre of Excellence of the Academy of Finland.
The EIML group is based on the former Time Series Prediction and Chemoinformatics group, and is developing new Machine Learning techniques:
- to model environment (using e.g. time series prediction, variable selection and ensemble modeling)
- to solve industrial problems (for example in the fields of chemometrics, electricity production and distribution, bankruptcy prediction and information security.
Personnel
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Alumni (Doctors, Postdocs)
Visitors and Former Students
Benoit Frenay, Alberto Guillen, Jin Hao, Milan Jurik, Yongnan Ji, Laura Kainulainen, Tuomas Kärnä, Fernando Mateo, Nima Reyhani, Eric Séverin, Li Yao, Zhanxing Zhu.Courses
Current
- T-61.5010 Information Visualization P, Spring 2012
Previous
- T-61.3040 Statistical Signal Modeling, Autumn 2011
- T-61.9910 Special Course in Computer and Information Science I P - Machine Learning for Corporate Finance, Autumn 2011
- T-61.5010 Information Visualization P, Spring 2011
- T-61.3040 Statistical Signal Modeling, Autumn 2010
- T-61.6010 Special Course in Computer and Information Science I P - Evolving Intelligent Systems, Methodology and Applications, Autumn 2010
- T-61.5010 Information Visualization P, Spring 2010
- T-61.6010 Special Course in Computer and Information Science I P - Hilbert-Huang Transform and its Applications, Autumn 2009
- T-61.6020 Special Course in Computer and Information Science II P - Bankruptcy Prediction, Autumn 2009
- T-61.6010 Special Course in Computer and Information Science I P - High Dimensional Data Analysis, Autumn 2008
Projects
Current
- Automaqua: Automation technologies for wastewater treatment plants in the era of data explosion
- BONUS+ ERA-Net Project AMBER: Assessment and Modelling of Baltic Ecosystem Response
- FP7-PEOPLE IEF: Developing Nonlinear Tools for Environmental Modeling and Chemoinformatics
Past
- CHESS: Developing chemometrics with the tools of information technology
Events
- In September 2008, we organized the ESTSP'08 conference on time series prediction.
- In February 2007, we organized the ESTSP'07 conference on time series prediction.