Dept. of Signal Processing and Acoustics
School of Electrical Engineering
esa DOT ollila AT aalto DOT fi
Esa Ollila received the M.Sc. degree in mathematics from the University of Oulu, in 1998, Ph.D. degree in statistics with honors from the University of Jyvaskyla, in 2002, and the D.Sc.(Tech) degree with honors in signal processing from Aalto University, in 2010. From 2004 to 2007 he was a post-doctoral fellow and from August 2010 to May 2015 an Academy Research Fellow of the Academy of Finland. He has also been a Senior Lecturer at the University of Oulu. Currently, he is an Associate Professor of Signal Processing at Aalto University. He is also an adjunct Professor (statistics) of Oulu University. Fall-term 2001 he was a Visiting Researcher with the Department of Statistics, Pennsylvania State University, while the academic year 2010-2011 he spent as a Visiting Post-doctoral Research Associate with the Department of Electrical Engineering, Princeton University.
Shahab Basiri, doctoral student, since 4/2014.
Muhammad Naveed Tabassum, doctoral student, since 1/2016.
Elias Raninen, doctoral student since 6/2017.
Jari Miettinen, post-doctoral fellow, since 8/2017 (jointly supervised with Prof. Sergiy Vorobyov)Alumni
Aqib Ejaz, M.Sc. student, 12/1014 - 5/2015.
Alireza Razavi, post-doctoral fellow, 8/2011- 8/2012.
Statistical Learning / Statistical Signal Processing / Machine Learning / Tensor decompositions / Robust statistics / Big Data / Medical imaging / Regularized and penalized optimization / Sparse regression / Covariance matrix estimation / Blind source separation / Independent Component Analysis / Compressed sensing
Nov 22, 2017 I am teaching a course Advanced Topics in Statistical Learning that starts at Jan 9th, 2018. See you there!
Nov 19, 2017 Returned from a 3-day visit to University of Bern (Switzerland). Thanks to Prof. Lutz Duembgen for hosting.
Aug 30, 2017 My group has two papers at EUSIPCO 2017 (Kos, Greece). Hope to see you there!
Aug 1, 2017 Jari Miettinen started as a post-doctoral fellow. Wellcome!
June 4, 2017 I am visiting for two weeks the Riken Brain Science Institute at Tokyo. Thanks to Prof. Andrzej Cichocki for hosting.
ELEC-E5470 Advanced Topics in Statistical Learning P, Spring 2018, Spring 2017.
ELEC-E5430 Signal Processing for Large Scale Data Analysis L, Spring-2017, Spring 2016.
ELEC-C5210 Satunnaisprosessit tietoliikenteessä (random processes), Spring-2018, Spring 2017
Alternative derivation of FastICA with novel power iteration algorithm
Shahab Basiri, Esa Ollila and Visa Koivunen, IEEE Signal Processing Letters, vol. 24, no 9, 2017.
Matlab code (with examples and manual) for powerICA method.
Enhanced bootstrap method for statistical inference in the ICA model
Shahab Basiri, Esa Ollila and Visa Koivunen, Signal Processing, vol. 138, pp. 53-62, 2017
Multichannel sparse recovery of complex-valued signals using Huber's criterion
Esa Ollila, in Proc. Int'l Workshop on Compressed Sensing Theory and its Applications to Radar, Sonar and Remote Sensing (CoSeRa'15), Pisa, Italy, June 16-19, 2015, pp. 32-36. Matlab code
Robust antenna array processing using M-estimators of pseudo-covariance
Esa Ollila and Visa Koivunen, in Proc. IEEE Int.'l Symp. Personal, Indoor and Mobile Radio Communications (PIMRC'03), Beijing, China, Sept. 7-10, 2003, vol. 3, pp. 2659-2663.
Adjusting the generalized likelihood ratio test of circularity robust to non-normality
Esa Ollila and Visa Koivunen, in Proc. 10th IEEE Int.'l Workshop on Signal Processing Advances in Wireless Communications (SPAWC'09), Perugia, Italy, June 21-24, 2009, pp. 558 - 562.
Also includes code for GLRT of circularity introduced in Generalized complex elliptical distributions
Matlab routines for CES distribution and related circularity detectors introduced in Complex elliptically symmetric random variables - generation, characterization and circularity tests.
C program (fast) and an R routine (that calls the C code) to compute the multivariate regression estimates based on multivariate Oja ranks introduced in Estimates of regression coefficients based on lift rank covariance matrix.