## News

**September 26, 2022**. New publication. Our paper ‘Spectral Subsampling MCMC for Stationary Multivariate Time Series with
Applications to Vector ARTFIMA Processes’ (with Matias Quiroz, Robert Kohn and Robert Salomone) has been accepted for publication in *Econometrics & Statistics*.

**September 19, 2022**. New publication. Our paper ‘Dynamic Mixture of Experts Models for Online Prediction’ (with Parfait Munezero and Robert Kohn) has been accepted for publication in *Technometrics*.

**June 14, 2022**. Gave a seminar in the AI4Research seminar series at Uppsala University on the topic ‘Adventures in Gaussian Processes’. slides and demo video

**June 9, 2022**. In PhD grading committee for Osama Muhammad’s PhD thesis Robust Machine Learning Methods at Uppsala University.

**Spring 2022**. I am chair of the scientific committee for the bi-annual NordStat conference in Mathematical Statistics, organized by Chalmers University in Gothenburg in June 19-22, 2023.

**Feb 11, 2022**. Gave a guest lecture on Bayesian regression for engineering students at Royal Institute of Technology (KTH). Slides and code available here.

**Jan 28, 2022**. New publication. Our paper ‘Robust Real-Time Delay Predictions in a Network of High-Frequency Urban Buses’ (with Hector Rodriguez-Deniz) has been accepted for publication in *IEEE Transactions on Intelligent Transportation Systems*.

**Jan 20, 2022**. New paper ‘Bayesian Prediction with Covariates Subject to Detection Limits’ with Caroline Svahn. arXiv.

**Jan 3, 2022**. Our paper ‘A Multilayered Block Network Model to Forecast Large Dynamic Transportation Graphs: an Application to US Air Transport’ (with Hector Rodriguez-Deniz and Augusto Voltes-Dorta) has been accepted for publication in *Transportation Research Part C: Emerging Technologies*.

**Dec 18, 2021**. Gave a talk on our paper ‘Bayesian Optimization of Hyperparameters when the Marginal Likelihood is Estimated by MCMC’ at the CFE2021 conference in London (but online). The slides for the talk are here.

**Dec 18, 2021**. Organized a session on spatiotemporal data at CMStatistics2021 in London (but online).

**Dec 14, 2021**. New paper ‘Local Prediction Pools’ with Oscar Oelrich and Sebastian Ankargren. arXiv.

**Dec 8, 2021**. New paper: ‘Bayesian Modeling of Effective and Functional Brain Connectivity using Hierarchical Vector Autoregressions‘ (with Bertil Wegmann, Anders Lundquist and Anders Eklund). arXiv

**Nov, 2021**. Taught a regression and time series course on the basic undergradudate level in Swedish. Slides and other material are in this github repo.

**Sept 23, 2021**. New paper: ‘Dynamic Mixture of Experts Models for Online Prediction’ (with Parfait Munezero and Robert Kohn). arXiv

**Sept 24, 2021**. In PhD grading committee for Samuel Wiquist’s PhD thesis Simulation-based Inference: From Approximate Bayesian Computation and Particle Methods to Neural Density Estimation at Mathematical Statistics, Lund University.

**June 27, 2021**. New publication: ‘Spatial 3D Matérn priors for fast whole-brain fMRI analysis’ (with Per Sidén, Finn Lindgren, David Bolin and Anders Eklund) has been accepted by Bayesian Analysis. arXiv

**June 25, 2021**. New paper: ‘Robust Real-Time Delay Predictions in a Network of High-Frequency Urban Buses’ (with Hector Rodriguez-Deniz). arXiv

**June 2, 2021**. Gave a keynote talk (online) at the CEDAS conference in data science in Bergen. Topic: this tweet.

**May, 2021**. Teaching newly developed Machine Learning course at the masters’ programme in Statistics at Stockholm University. course web page

**March 13, 2021**. New publication: ‘The Block-Poisson estimator for optimally tuned exact subsampling MCMC’ (with Matias Quiroz, Minh-Ngoc Tran, Robert Kohn and Khue-Dung Dang) has been accepted for publication by *Journal of Computational and Graphical Statistics*. Here is the arXiv version.

**Feb 12, 2021**. Gave a guest lecture on Bayesian Regression at KTH. slides.

**Jan 27, 2021**. Gave a seminar on ‘Spectral subsampling MCMC for multivariate time series’ at Humboldt University (zoom).

**Dec 21, 2020**. Attended CMStatistics2020 where I organized a session on ‘Bayesian model comparison’ and presented a talk on ‘Spectral subsampling MCMC for multivariate time series’.

**Dec 15, 2020**. I gave a seminar at Chalmers University on ‘Spectral subsampling MCMC for multivariate time series’.

**Dec 15, 2020**. I was on the grading committee for Xiuming Liu’s PhD defense of the thesis Statistical Data Analysis for Internet-of-Things: Scalability, Reliability, and Robustness at Department of Information Technology, Uppsala University.

**Dec 11, 2020**. My PhD student Parfait Munezero successfully defended his PhD thesis ‘Bayesian Sequential Inference for Dynamic Regression Models’ in Statistics at Stockholm University. Helga Wagner was faculty opponent.

**Nov 4, 2020**. I got a 3.3 MSEK grant from the Swedish Research Council (VR) for developing Bayesian methods for large-scale data.

**Oct 1, 2020**. I am now Associate Editor for Bayesian Analysis.

**Sept 18, 2020**. My PhD student Per Sidén successfully defended his PhD thesis ‘Scalable Bayesian spatial analysis with Gaussian Markov random fields’ in Statistics at Linköping University. Håvard Rue was faculty opponent.

**June 30, 2020**. Evaluated Jonas Wallin’s promotion to senior lecturer in Statistics and Lund University.

**June 10, 2020**. Webinar for Swedish Statistical Association on how to change Statistics education. slides

**June 1, 2020**. New publication: ‘Spectral Subsampling MCMC for Stationary Time Series’ (with Rob Salomone, Matias Quiroz, Robert Kohn and Minh-Ngoc Tran) has been accepted by ICML2020. arXiv

May 20, 2020. Seminar at Statistics, Stockholm University on ‘Spectral Subsampling MCMC for Large-Scale Time Series’.

May 12, 2020. New publication: ‘Physiological Gaussian Process Priors for the Hemodynamics in fMRI Analysis’ (joint with Josef Wilzén and Anders Eklund) accepted by *Journal of Neuroscience Methods*.

April-May, 2020. Teaching a PhD course in Advanced Bayesian Learning, 7.5 credits. github repo

April 23, 2020. New paper: ‘Bayesian Optimization of Hyperparameters when the Marginal Likelihood is Estimated by MCMC’ with Oskar Gustafsson and Pär Stockhammar. arXiv

April 22, 2020. Faculty opponent on Muhammad Osama’s PhLic thesis ‘Machine Learning for Spatially Varying Data’ in Automatic Control in Uppsala.

March 10, 2020. New paper: ‘When are Bayesian model probabilities overconfident?’ (with Oscar Oelrich, Shutong Ding, Måns Magnusson and Aki Vehtari). arXiv

March 6, 2020. I was on the grading committee for Sergeii Voronov’s PhD thesis ‘Machine Learning Models for Predictive Maintenance’ in Vehicular Systems.

March 1, 2020. I wrote an invited article (in Swedish) for the member magazine of the Swedish Statistical Association about how Machine Learning is a threat to Statistics, and why that it is great thing. article

Feb 6, 2020. I am giving a guest lecture at KTH on Bayesian Regression.

Jan 7, 2020. New publication: ‘Anatomically informed Bayesian spatial priors for fMRI analysis‘ (with David Abramian, Per Sidén, Hans Knutsson and Anders Eklund) will appear in IEEE International Symposium on Biomedical Imaging (ISBI2020). arXiv

Dec 15, 2019. Gave a talk at CFE2019 in London on Recent Developments in Subsampling for Large-Scale Bayesian Inference. slides

Dec 14, 2019. Organized a session on Spatial Statistics at CMStatistics2019 in London.

Nov 29, 2019. New paper A Bayesian Dynamic Multilayered Block Network Model with Hector Rodriguez-Deniz and Augusto Voltes-Dorta. arXiv

Nov 2019. Teaching new course in Machine Learning at Linköping University for participants from the industry. course page

Nov 1, 2019. New paper ‘Spectral Subsampling MCMC for Stationary Time Series‘. (with Rob Salomone, Matias Quiroz, Robert Kohn and Minh-Ngoc Tran).

October 25, 2019. New paper ‘Anatomically informed Bayesian spatial priors for fMRI analysis‘ (with David Abramian, Per Sidén, Hans Knutsson and Anders Eklund).

October 11, 2019. Member of grading committee for Sebastian Ankargren’s PhD thesis in Statistics ‘AR Models, Cointegration and Mixed-Frequency Data’ at Uppsala University.

October 2, 2019. Gave a talk at Stockholm University on ‘Statistics and AI’ for high school students.

September 30, 2019. Gave a presentation at a meeting organized by the Cramér Society about Machine Learning courses in Statistics education at Linköping and Stockholm University.

June 18, 2019. New publication: ‘Hamiltonian Monte Carlo with Energy Conserving Subsampling’ will appear in Journal of Machine Learning Research (with Khue-Dung Dang, Matias Quiroz, Robert Kohn, Minh Ngoc Tran).

May 20, 2019. Gave a talk ‘The Core of AI is Statistics’ for master students in Statistics at a meeting organized by the Swedish Statistical Association. slides

May 15, 2019. New publication: ‘Real-Time Robotic Search using Structural Spatial Point Processes‘ (with Olov Andersson, Per Sidén, Johan Dahlin and Patrick Doherty) has been accepted for Uncertainty in Artificial Intelligence (UAI2019).

April 13-15, 2019. Gave a talk at the CronosMDA2019 conference in Limassol, Cyprus.

March 26, 2019. New paper ‘Real-Time Robotic Search using Hierarchical Spatial Point Processes‘ (with Olov Andersson, Per Sidén, Johan Dahlin and Patrick Doherty).

March 14, 2019. My student Måns Magnusson won the Cramer prize for best PhD thesis in Statistics and Mathematical Statistics in Sweden with his thesis ‘Scalable and Efficient Probabilistic Topic Model Inference for Textual Data’.

March 11-14, 2019. Gave a series of lectures on Bayesian Machine Learning at the 2019 Winter Course in Statistics. Here is my material.

Feb 14, 2019. Gave a talk about Bayesian Prediction and Decision Making at iZettle, Stockholm. slides

Feb 14, 2019. Gave guest lecture about Bayesian regression for engineering students at KTH. slides and some code.

Feb 13, 2019. Gave lectures about Bayesian inference as a part of the PhD course Statistical Inference, 15 credits, at Stockholm University. slides

Jan 17 - Feb 3, 2019. Visited Robert Kohn and Matias Quiroz at UNSW, Sydney.

Dec 21, 2018. Member of the PhD graduation committee for Björn Holmqvist’s PhD thesis ‘Gaussian Process Models of Social Change’ at Mathematics, Uppsala University. Faculty opponent: Ian Vernon.

Dec 19, 2018. Gave the talk ‘Optimal Tuning of Subsampling Hamiltonian Monte Carlo‘ at Division of Mathematical Statistics, Stockholm University. Slides.

Dec 7, 2018. Member of the PhD graduation committee for Ivar Simonsson’s PhD thesis ‘Exact inference in Bayesian networks and applications in forensic statistics’ at Chalmers University. Faculty opponent: Steffen Lauritzen.

Nov 28, 2018. Gave a talk on ‘Gaussian Processes with Applications’ at the Statistics Department at Stockholm University. Slides.

Nov 10, 2018. New paper: Modeling Text Complexity using a Multi-Scale Probit (with Johan Falkenjack and Arne Jönsson) [arXiv]

Oct 23, 2018. I gave a popular science presentation on ‘How to teach machines to think’ (in Swedish) to final year high school students.

Oct 23, 2018. I am now main supervisor for Munezero Parfait and Oscar Oelrich, both PhD students in Statistics at Stockholm University.

Oct 15, 2018. Started as deputy member of board for the National Supercomputer Centre (NSC) at Linköping University.

Oct 1, 2018. I will teach the 2019 Winter Course in Statistics, with Corinna Cortes (Google Research, NY) and Edward Kennedy (CMU). This year’s topic is Machine Learning.

Sept 30, 2018. Per Sidén and I contributed an invited discussion of the article “Bayesian Spatiotemporal Modeling Using Hierarchical Spatial Priors, with Applications to Functional Magnetic Resonance Imaging” for Bayesian Analysis. Paper

Sept 1, 2018. New publication: DOLDA a regularized supervised topic model for high-dimensional multi-class regression, Computational Statistics (with Måns Magnusson and Leif Jonsson) [arXiv]

August 20, 2018. New publication: Subsampling MCMC – An Introduction for the Survey Statistician, Sankhya A (with Matias Quiroz, Robert Kohn , Minh Ngoc Tran and Khue-Dung Dang) [arXiv]

August 17, 2018. I gave a talk at Statisticon about the machine learning courses at LiU.

August 1, 2018. I am now Professor of Statistics at Stockholm University. I will split my time between Linköping and Stockholm University.

June 24-29, 2018. I attended ISBA2018 in Edinburgh.

June 21, 2018. Gave a talk on our paper ‘The Block-Poisson Estimator for Optimally Tuned Exact Subsampling MCMC’ at Ecosta2018 in Hong Kong. Slides are here.

June 5, 2018. My student Måns Magnusson successfully defended his PhD thesis in Statistics at Linköping University. Jordan Boyd-Graber was faculty opponent.

May 8, 2018. I gave the talk ‘The Block-Poisson Estimator for Optimally Tuned Exact Subsampling MCMC’ at the Mathematics department in Uppsala. Here are the slides.

April, 26. Gave a talk ‘Bayesian Statistics – what it is and what it can do for you’ at the Division for Enviromental Change at Linköping University. Slides here.

April 6, 2018. I evaluated Fredrik Lindsten for the Docent title in Electrical Engineering at Uppsala University.

March 10, 2018. New publication: Tree Ensembles with Rule Structured Horseshoe Regularization, Annals of Applied Statistics, 2018 (with Malte Nalenz) [arXiv]

Feb 3, 2018. New publication: Efficient Covariance Approximations for Large Sparse Precision Matrices, Journal of Computational and Graphical Statistics (with Per Sidén, Finn Lindgren and David Bolin) [arXiv]

Feb 3, 2018. New publication: Speeding Up MCMC by Efficient Data Subsampling, Journal of the American Statistical Association (with Matias Quiroz, Robert Kohn and Minh Ngoc Tran) [arXiv]

Nov, 30, 2017. I evaluated Jenny Häggström for the Docent title in Statistics at Umeå University.

Oct 27, 2017. Talk at the Cramér Society, Stockholm. Slides.

Oct 26, 2017. Keynote at ESOBE2017. Slides.

Oct 25, 2017. One-day ESOBE2017 course at Maastricht University on ‘ML for Econometricians’. Slides, suggested reading, some code and software available in this GitHub repo.

Oct 6, 2017. New publication: Bayesian Rician Regression for Neuroimaging, Frontiers in Neuroscience (with Bertil Wegmann and Anders Eklund) [arXiv]

Aug 22, 2017. New paper: Physiological Gaussian Process Priors for the Hemodynamics in fMRI Analysis (with Josef Wilzén and Anders Eklund). [arXiv]

Aug 4, 2017. New paper: Hamiltonian Monte Carlo with Energy Conserving Subsampling (with Khue-Dung Dan, Matias Quiroz, Robert Kohn and Minh Ngoc Tran). [arXiv].

July 10, 2017. New publication: Urban Network Travel Time Prediction via Online Multi-Output Gaussian Process Regression, IEEE International Conference on Intelligent Transportation Systems (ITSC2017) (with Héctor Rodgríguez-Déniz, Erik Jenelius).

July 9, 2017. New publication: Sparse Partially Collapsed MCMC for Parallel Inference in Topic Models, Journal of Computational and Graphical Statistics (with Måns Magnusson, Leif Jonsson and David Broman).

June 2, 2017. New publication: Bayesian Diffusion Tensor Estimation with Spatial Priors, International Conference on Computer Analysis of Images and Patterns (CAIP), 2017 (with Guan Xu, Per Sidén, Bertil Wegmann, Anders Eklund, Evren Özarslan and Hans Knutsson).

May 26, 2017. New paper: Efficient Covariance Approximations for Large Sparse Precision Matrices (with Per Sidén, Finn Lindgren and David Bolin) [arXiv]

May 14, 2017. I am now an Associate Investigator in Australian Research Council Center of Excellence for Mathematical and Statistical Frontiers (ACEMS).

April 28, 2017. New publication: A Bayesian Heteroscedastic GLM with Application to fMRI Data with Motion Spikes, NeuroImage (with Anders Eklund and Martin Lindquist). Journal Version.

April 11, 2017. I am reviewing for NIPS2017.

March 25, 2017. New publication: Speeding up MCMC by Delayed Acceptance and Data Subsampling, Journal of Computational and Graphical Statistics (with Matias Quiroz, Minh Ngoc Tran and Robert Kohn). [arXiv]

March 6, 2017. I am on the Scientific Programme Committee for CMStatistics2017 in London Dec 16-18. I will also be organizing the session Scalable Bayesian methods for large data problems.

Feb 16, 2017. New paper: Tree Ensembles with Rule Structured Horseshoe Regularization (with Malte Nalenz) was posted on [arXiv].

Feb 2, 2017. I gave a talk about sparse parallel Gibbs sampling for topic models at a symposium on topic models with practitioners from the humanities, social and computer science. Slides

Jan 27, 2017. I am reviewing for ICML2017.

Jan 20, 2017. New publication: ‘Bayesian Heteroscedastic Regression for Diffusion Tensor Imaging’ (with Bertil Wegmann and Anders Eklund) will appear as a chapter in the Springer book ‘Modeling, Analysis, and Visualization of Anisotropy’.

Dec 21, 2016. New paper: Bayesian Non-central Chi Regression for Neuroimaging (with Bertil Wegmann and Anders Eklund) is available on [arXiv] and bioRxiv.

Dec 19, 2016. My previous PhD student Matias Quiroz received a very generous 3-year Wallander post doc scholarship grant following a nomination from our department.

Dec 9-12, 2016. I co-chaired, attended and organized a machine learning session at CMStatistics2016 in Seville, Spain.

Dec 3, 2016. New paper: A Bayesian Heteroscedastic GLM with Application to fMRI Data with Motion Spikes (with Anders Eklund and Martin Lindquist). bioRxiv

Nov 14, 2016. New publication: Fast Bayesian Whole-Brain fMRI Analysis with Spatial 3D Priors, NeuroImage (with Per Sidén, Anders Eklund and David Bolin).

Oct 21, 2016. I was on the grading committee for Jonas Hallgren’s PhD thesis Inference in Temporal Graphical Models in Mathematical Statistics at KTH.

Sept-Oct, 2016. I designed and taught our new master/phd course in Advanced Machine Learning with our new STIMA lecturer Jose M. Pena.

Sept 26, 2016. I was on the grading committee for Cheng Zhang‘s PhD defence of her thesis Structured Representation Using Latent Variable Models in Computer Science at KTH.

Sept 6, 2016. New publication: Intrusion-Damage Assessment and Mitigation in Cyber-Physical Systems for Control Applications, International Conference on Real-Time Networks and Systems, 2016 (with Rouhollah Mahfouzi, Amir Aminifar, Petru Eles and Zebo Peng).

August 15-18, 2016. I gave a talk at the biannual Smögen Workshop on spatial statistics. More importantly, I bravely took cold ocean baths at 7 AM every morning.

July 4, 2016. Keynote at Melbourne Bayesian Econometrics Workshop.

July 3, 2016. I gave this year’s masterclass in Computational Methods for Large-Scale Bayesian Inference at the University of Melbourne.

June 26-30, 2016. Organization of Human Brain Mapping (OHBM1016) conference, Geneva, Switzerland.

June 19, 2016. New publication: Automatic Localization of Bugs to Faulty Components in Large Scale Software Systems using Bayesian Classification, IEEE International Conference on Software Quality, Reliability & Security, 2016 (with Leif Jonsson, David Broman, Måns Magnusson, Kristian Sandahl and Sigrid Eldh).

June 12-18, 2016. ISBA2016. World meeting for Bayesian Statistics, Sardinia, Italy.

June 6, 2016. New paper: Fast Bayesian whole-brain fMRI analysis with spatial 3D priors with Per Sidén, Anders Eklund and David Bolin. [arXiv].

May 20, 2016. Workshop on Machine Intelligence and Autonomous Systems, Rio de Janeiro, Brazil.

May 19, 2016. AIMday in Belo Horizonte, Brazil.

May 16-18, 2016. Participated in SACF Brazil-Sweden excellence seminars in Brasilia.

April 12, 2016. We received a 27 MSEK SSF Smart Systems grant (main PI Patrick Doherty).

March 29, 2016. New paper: Exact Subsampling MCMC with Matias Quiroz and Robert Kohn. [arXiv].

March 8, 2016. New paper: Block-Wise Pseudo-Marginal Metropolis-Hastings with Minh Ngoc Tran, Robert Kohn and Matias Quiroz. [arXiv]

Feb 16, 2016. I gave a talk at Ericsson-LiU event (strategic collaboration agreement, see http://goo.gl/CeVjvQ) about finding bugs in large computer codes using supervised multi-class regression topic models.

Feb 2, 2016. New version of ‘Speeding Up MCMC by Efficient Subsampling’, now with a correlated PMMH approach to subsampling and comparison against all major competing subsampling methods.

Jan 31, 2016. New paper ‘DOLDA – a regularized supervised topic model for high-dimensional multi-class regression’ with Måns Magnusson and Leif Jonsson. arXiv.

Jan 15, 2016. I am co-chair for CMStatistics2016 which takes place in Sevilla in mid December.

Jan 15-28, 2016. I was on a research visit to University of New South Wales, Sydney.

Nov 12, 2015. I gave a one-day course on Bayesian analysis of VARs, State-space models and DSGEs at the National Institute of Economic Research (Konjunkturinstitutet).

Nov 6, 2015. I was on the examination committee for Tohid Ardeshiris PhD thesis ‘Analytical Approximations for Bayesian Inference’ in Automatic Control at Linköping University.

Oct, 2015. I evaluated Carl-Henrik Ek for Associate Professor in machine learning at KTH.

Oct, 2015. I am now co-supervisor of Olov Andersson (Robotics), Johan Falkenjack (Machine learning for readability of natural language), Chandan Roy (Cyclone forecasting using ANN) and Sarah Alsaadi (Psychometrics), all at Linköping University.

Sept 9, 2015. I am giving a talk on Learning from Big Data at the workshop Big data: Building data strategies for central banks in light of the data revolution organized by Sveriges Riksbank.

Sept 7, 2015. My student Matias Quiroz defends his PhD thesis in Statistics at Stockholm University. Opponent is Prof. Bani Mallick at Texas A&M University.

Sept 2, 2015. I am now associate editor for Part B: Statistics of the new Elsevier journal Econometrics & Statistics.

New paper: Scalable MCMC for Large Data Problems using Data Subsampling and the Difference Estimator (with Matias Quiroz and Robert Kohn). [arXiv]

New paper: Efficient approximate Bayesian inference for models with intractable likelihoods (with Johan Dahlin and Thomas Schön). [arXiv]

New paper: Parallelizing LDA using Partially Collapsed Gibbs Sampling (with Måns Magnusson, Leif Jonsson and David Broman). [arXiv]

New publication with main author Arian Maghazeh (and co-authors Unmesh Bordoloi, Petru Eles and Zebo Peng): Perception-Aware Power Management for Mobile Games via Dynamic Resolution Scaling, IEEE/ACM International Conference on Computer-Aided Design (ICCAD).

I am reviewing for NIPS2015.

I am a member of the Scientific Committee for the conference CMStatistics2015. I am also organizing a session there on Statistical Analysis of Text.

I am giving a talk on April 14 at Chalmers Machine Learning Summer School. Here are my slides.

A major revision of: Speeding Up MCMC by Efficient Data Subsampling (with Matias Quiroz and Robert Kohn) is available on [arXiv].

I am giving a talk at Bayes@Lund2015. Here are my slides.

I am reviewing for AIStats2015.

My student Matias Quiroz was given the Young Scientist Award at LinStat2014

Per Sidén joins our neuroimaging group as my new PhD student. Welcome Per!

My former PhD student Feng Li was awarded the 2014 Cramér prize for best PhD thesis in Statistics and Mathematical Statistics.

Feng’s video presentation was presented at the annual meeting.

New PhD course Advanced Bayesian Learning starts on March 26. I am teaching it jointly with Thomas Schön and José M. Pena.

New paper: Bayesian Inference in Structural Second-Price Auctions with both Private-Value and Common-Value Bidders (with Bertil Wegmann)

New publication: BROCCOLI: Software for Fast fMRI Analysis on Many-Core CPUs and GPUs. Frontiers in Neuroinformatics (with Anders Eklund, Paul Dufort and Stephen LaConte)

I received a 5.5 million SEK grant from the Swedish Research Council for the project Statistical Analysis of fMRI data.