Keywords: AI, Machine learning, neuroimaging, neuroinformatics, neural network, kunstig intelligens, Big data, sociale medier

Lars Kai Hansen

Professor, Head of Section Cognitive Systems

Department of Applied Mathematics and Computer Science - DTU Compute
Location: Richard Petersens Plads B321, Office 012.

Postal address: Richard Petersens Plads B324, Technical University of Denmark, DK 2800 Kgs Lyngby, DENMARK. Tel: (+45) 4525 3889;
E-mail: lkai AT dtu.dk -Twitter: @Tweetteresearch

 

Google scholar profile

ELLIS Fellow – European Laboratory for Intelligent Systems

 

Director THOR Center for Neuroinformatics - EEG in the Classroom. Smartphone EEG brain scanner. Brede search engine.

 

https://media.springernature.com/w306/springer-static/cover-hires/book/978-3-030-28954-6Explainable AI: Interpreting, Explaining and Visualizing Deep Learning.  

Eds. Wojciech Samek, Grégoire Montavon, Andrea Vedaldi, Lars Kai Hansen & Klaus-Robert Müller (2019)

 

 

Talks –videos and pdfs

Keynote 2021 Northern Lights Deep Learning Workshop “Explainable AI –recent results and open problems” (Tromsø "North Pole" Jan 18, 2021) pdf.

Invited talk Opening of the Center for Ear-EEG “Neuroscience in the wild - or wild neuroscience in DK?”  (Aarhus Feb 28, 2020) pdf.

Keynote 2020 KERMES Workshop “Kernels in Copenhagen: Variance inflation, explainability & spontaneous symmetry breaking” (Santander, Feb 20, 2020) pdf.

Invited talk Institut DATAIA Paris-Saclay “Phase transition in PCA with missing data” (Paris Nov 27, 2019) pdf.

Invited talk at 2019 European Society for Organ Transplantation’s (ESOT) congress “Explainable AI in health care” (Copenhagen Sep 16, 2019) pdf.

Keynote Intelligent Systems Conference 2018 “Safe AI -Trust and privacy in intelligent systems” (London Sep 6, 2018) Video.

MLSP 2018 IEEE Workshop Tutorial “Opening the Black Box How to Interpret Machine Learning Functions and Their Decisions” (Aalborg Sep 17, 2018) pdf.

Swartz Center for Computational Neuroscience “Exploring the limits to EEG " (UC San Diego, Jan 9, 2018) pdf.

Oticon Eriksholm Research Center: “Neuroscience in the Wild: Neurotechnology for 24/7 brain state monitoring” (Snekkersten, DK, Nov 14, 2017) pdf.

Berlin Deep Learning Workshop: “Deep debugging (Berlin, Germany, Jun 23, 2017)

Psychology Colloquium: “EEG in Wild” (Zurich, Mar 20, 2016) University of Zurich pdf.

ICANN 2016 Workshop on Interpretation in machine learning (Barcelona, Spain, Sep 6, 2016) “Resampling Based Design, Evaluation and Interpretation of Neuroimaging Modelspdf

Neuroimaging Mechanisms of Behavior Change “EEG brain state monitoring in the wild” (Atlanta May 11, 2016)  video  pdf

Keynote: SPLINE 2016 Workshop on Sensing and Learning for Intelligent Machines (Aalborg, Jul 6, 2016). “Sensing the deep structure of signalspdf

Dept. of Computer Science, University College London (May 7, 2015). “Variance inflation in high dimensional learningpdf

IBM Almaden Research Center (San Jose, Jan 21, 2015) “Quantified livingpdf

Plenary talk IEEE Int. Workshop on Machine Learning for Signal Processing 2014 (Reims, France, Sep 24, 2014). “Real-time brain imaging in the wildpdf 

IPAM Workshop on Multimodal Neuroimaging (UCLA, March 6, 2013)  "Mobile Real-Time EEG Imaging" pdf

Facebook (Palo Alto, Jan 22, 2013). “The Cognitive Components of Digital Mediapdf

Keynote 10th Int. Workshop on Adaptive Multimedia Retrieval (Royal School of Library, Oct 24, 2012).  The Cognitive Components of Digital Mediapdf

BBCI Summer School (TU Berlin, Sep 21, 2014). “Resampling based methods for design and evaluation of neurotechnologyWeb site w. slides

Keynote 9th Sound and Music Computing Conference (Aalborg Univ., Jul 14).  The Cognitive Components of Audio Spacespdf

SICSA Summer School (Glasgow Univ., Jun 13, 2012).  Personal State DecodingLink (pdf’s, code)

Keynote 3rd Workshop on Cognitive Information Processing CIP 2012 (Spain, May 30). “Attention as a machine learning problempdf

Lund University, Institutionen för Psykologi Seminar (Sweden, Mar 30 2012) .Cognitive  representations: What can we learn from machine learning?pdf

Google MTV Tech Talk (CA USA, Jan 27 2012). “Good Friends, Bad News - Affect and Virality in Twitterpdf

 

AI: Visions & critique

Børsens kronik Tuesday May 15, 2018 (n Danish).

BusinessMinds New Year celebration -talk, Jan 4, 2017. ”Quantified human behavior pdf

Politikens Kronik Fredag 9. august 2013 (in Danish). Indeni, udenpå (udvidet version, med referencer).

DTU MAN IPU Seminar:  Big Data – Big Science   March 12, 2014 (pdf)  

The Innovation Fund Denmark funded national partnership ”Danish Center for Big Data Analytics driven Innovation (DABAI)”.

Politikens Kronik Monday 12. november 2001 (in Danish) about the 3-year-old Google and the potential of machine learning and understanding.

 

Other current research issues:

Understanding Deep Learning. Affect and virality in Twitter. Top-down attention as a machine learning problem. Small samples in high-dimensions (variance inflation) Cognitive component analysis. Functional neuroimaging (with access to the 'lyngby' toolbox). Modeling EEG using PARAFAC

Publications:  300+ papers in journals, books, and conferences Google scholar profile   Publications in DTU Orbit    One page CV

Brief biography: LKH has a PhD in physics (University of Copenhagen, 1986). He worked on industrial vision/neural nets from 1987-1990, with Andrex Radiation Products A/S. With the Technical University of Denmark since 1990, full professor 2000. Since 2008 Head of Section, Cognitive Systems, DTU Compute, Technical University of Denmark. 2011 Excellence professorship, Univ. Carlos III Madrid, Spain. Member of the Danish Council for Independent Research | Technology and Production Sciences (FTP) 2011-2014. Member of Danish Council for Independent Research’s Expert Committee | Digital technologies 2019. Member of Novo Nordisk Foundation’s committee for Natural Science and Technology 2020-.

Since 1981 married to Connie Bork - poetry in Danish. Our amazing Sara Bork and Alexander Bork

Key results:

N. Ipsen, L.K.Hansen: Phase transition in PCA with missing data: Reduced signal-to-noise ratio, not sample size!

Proc. of the 36th Int. Conf. on Machine Learning, PMLR 97:2951-2960 (2019).

 

T.J. Abrahamsen, L.K. Hansen: A Cure for Variance Inflation in High Dimensional Kernel Principal Component Analysis. Journal of Machine Learning Research 12:2027−2044, (2011)

 

D. J. Jacobsen, L. K. Hansen, K. H. Madsen: Bayesian Model Comparison in Nonlinear BOLD fMRI Hemodynamics. Neural Computation 20:738-755 (2008).

 

R. K. Olsson and L. K. Hansen: Linear State-Space Models for Blind Source Separation

Journal of Machine Learning Research 7:2585—2602 (2006).

 

M. Moerup, L. K. Hansen, C. S. Hermann, J. Parnas, S. M. Arnfred: Parallel Factor Analysis an exploratory tool for wavelet transformed event-related EEG. NeuroImage 29(3): 938-947 (2006).

 

M. McKeown, L.K. Hansen, and T.J. Sejnowski: Independent Component Analysis for fMRI: What is Signal and What is Noise? Current Opinion in Neurobiology Vol.13(5) 620-629 (2003).

 

P.A.d.F.R. Hojen-Sorensen, O. Winther, and L.K. Hansen: Mean Field Approaches for Independent Component Analysis. Neural Computation 14:889-918 (2002).

 

U. Kjems, L.K. Hansen, J. Anderson, S. Frutiger, S. Muley, J. Sidtis, D. Rottenberg, and S.C. Strother. The Quantitative Evaluation of Functional Neuroimaging Experiments: Mutual Information Learning Curves. NeuroImage 15(4): 772-786 (2002)

 

S.C. Strother, J. Anderson, L.K. Hansen, U. Kjems, R. Kustra, J. Sidtis, S. Frutiger, S. Muley, S. LaConte, and D. Rottenberg: The Quantitative Evaluation of Functional Neuroimaging Experiments:  The NPAIRS Data Analysis Framework. NeuroImage 15(4):747-771 (2002).

 

L.K. Hansen: Bayesian Averaging is Well-Temperated. In Proceedings of NIPS*99, S.S.\ Solla et al. (eds.), 265-271 (2000)

 

N. Lange, S.C. Strother, J.R. Anderson, F.AA. Nielsen, A.P. Holmes, T. Kolenda, R. Savoy, L.K. Hansen: Plurality and Resemblance in fMRI Data Analysis. NeuroImage, 10(3): 282-303 (1999).

 

L.K. Hansen, J. Larsen, F.AA. Nielsen, S.C. Strother, E. Rostrup, R. Savoy, N. Lange, J.J. Sidtis, C. Svarer, O.B. Paulson: Generalizable Patterns in Neuroimaging: How Many Principal Components? NeuroImage 9: 534-544 (1999).

 

L.K. Hansen and P. Salamon: Neural Network Ensembles.

IEEE Transactions on Pattern Analysis and Machine Intelligence 12: 993-1001 (1990).

 

For students

 

Main supervisor (PhD-student, research area, funding):

Jia Qian

Federated learning

EU FORA

Petr Taborsky

Machine learning

Telenor

Jonathan Foldager

Quantum machine learning

Oticon Foundation

Former Phd-students: 

Jeppe Nørregaard

ITU

Niels Ipsen

Novo Nordisk

Damian Kowalczyk

Microsoft

Sirin Gangstad

UNEEG

Frans Zdyb

 

Laura Rieger

DTU Energy

Georgios Arvanitidis

Max Planck Institute for Intelligent Systems

Andreas Trier Poulsen

Widex

Simon Kamronn

Systematic

Michael Riis Andersen

DTU

Sofie Therese Hansen

EEG source localization

Rasmus Troelsgaard

Audio informatics

Bjarne Fruergaard

Vestas

Kasper Winther Jørgensen

Hvidovre Hospital DRCMR

Toke Jansen Hansen

Apple Inc.

Trine Abrahamsen

Novo Nordic

Tue Herlau

DTU Compute

Peter Mondrup Rasmussen

Aarhus University

Carsten Stahlhut

Novo Nordisk

Marcin Szewczyk

Anders Petersen

Teknologisk Institut

Ling Feng

Rigshospitalet, Copenhagen

Andreas Brinch Nielsen

Alipes A/S

Rasmus Elsborg Madsen

Hyposafe A/S

Tim Dyrby

Hvidovre Hospital MR

Morten Moerup

DTU Compute

Kristoffer Hougaard Madsen

Hvidovre Hospital MR

Tue Lehn Schioeler

Rambøll

Rasmus K. Olsson

GN Netcom

Esben Hoegh Rasmussen

Rigshospitalet 

Mads Dyrholm

Jabra

Kaare Brandt Petersen

SAS Institute

Irene Klaerke Andersen

CFIN Aarhus

Lars Nonboe Andersen

SIMRAD, NORWAY

Peter Magnus Noergaard

WIDEX

Torben Fog

M.A.N. B&W

Maarten Keijzer

Vrije Universiteit, Amsterdam

Preben Kidmose

WIDEX

Thomas Kolenda

CODEGROUP

Thomas Fabricius

Chora A/S

Ulrik Kjems

OTICON

Bjorn Steen Larsen

 

Mads Hintz Madsen

MediaTek

Niels Moerch

Fingerprints

Karam Sidaros

Hvidove Hospital

Peter A. Philipsen

Bispebjerg Hospital

Nikola Schou

 

Pedro Hoejen Soerensen

Foss

Peter Toft

NOKIA

Thorkild Find Petersen

Bruel & Kjaer, ATV

Finn Aarup Nielsen

IMM

Siggi Sigurdsson

Oticon

Robin de Nijs

Medical signal processing

Morten With Pedersen

Foss

Claus Svarer

Rigshospitalet

Anna Szymkowiak

Datamining, SAXO Bank

Joaquin Quinonero

Facebook

Sune Lehmann

DTU Compute

Daniel Jacobsen

Decision3, Thorshavn

Frederik Brink Nielsen

ISG Denmark

Kristian Klinkby

 

 

Early work on Independent Component Analysis (ICA)

see also the publication repository , or NEC's citeseer

Return to Section for Cognitive Systems homepage.