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
ELLIS Fellow
– European Laboratory for Intelligent Systems
Director THOR Center for Neuroinformatics - EEG in the Classroom. Smartphone
EEG brain scanner. Brede search
engine.
Explainable 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
Models” pdf
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 signals” pdf
Dept.
of Computer Science, University College London (May 7, 2015). “Variance inflation in high dimensional
learning” pdf
IBM
Almaden Research Center (San Jose, Jan 21, 2015) “Quantified living” pdf
Plenary
talk IEEE Int. Workshop on Machine Learning for Signal Processing 2014 (Reims,
France, Sep 24, 2014). “Real-time brain
imaging in the wild” pdf
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 Media” pdf
Keynote
10th Int. Workshop on Adaptive Multimedia Retrieval (Royal School of Library,
Oct 24, 2012). “The Cognitive Components of Digital Media” pdf
BBCI
Summer School (TU Berlin, Sep 21, 2014). “Resampling based methods for design and
evaluation of neurotechnology”
Web site w.
slides
Keynote 9th Sound and Music Computing
Conference (Aalborg Univ., Jul 14). “The Cognitive Components of Audio Spaces”
pdf
SICSA Summer School (Glasgow Univ., Jun
13, 2012). “Personal State Decoding” Link (pdf’s,
code)
Keynote 3rd Workshop on Cognitive
Information Processing CIP 2012 (Spain, May 30). “Attention as a machine learning problem” pdf
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 Twitter” pdf
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).
Main supervisor (PhD-student, research area, funding):
|
Jia Qian |
Federated learning |
EU FORA |
|
Petr Taborsky |
Machine learning |
Telenor |
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Jonathan Foldager |
Quantum machine learning |
Oticon Foundation |
Former Phd-students:
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ITU |
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Niels Ipsen |
Novo Nordisk |
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Damian Kowalczyk |
Microsoft |
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DTU Energy |
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Max Planck Institute for
Intelligent Systems |
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Widex |
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Systematic |
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DTU |
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EEG source localization |
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Audio informatics |
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Bjarne Fruergaard |
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Apple Inc. |
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Novo Nordic |
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DTU Compute |
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Aarhus University |
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Novo Nordisk |
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Teknologisk Institut |
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Rigshospitalet,
Copenhagen |
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Alipes A/S |
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Rasmus Elsborg Madsen |
Hyposafe A/S |
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Hvidovre Hospital MR |
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DTU Compute |
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Hvidovre Hospital MR |
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Rambøll |
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Rasmus K. Olsson |
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Rigshospitalet |
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Kaare Brandt Petersen |
SAS Institute |
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SIMRAD, NORWAY |
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Peter Magnus Noergaard |
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M.A.N. B&W |
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Vrije Universiteit,
Amsterdam |
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WIDEX |
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CODEGROUP |
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Chora A/S |
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OTICON |
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Bjorn Steen Larsen |
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MediaTek |
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Hvidove Hospital |
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Bispebjerg Hospital |
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NOKIA |
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Thorkild Find Petersen |
Bruel & Kjaer, ATV |
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IMM |
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Oticon |
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Medical signal processing |
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Rigshospitalet |
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Datamining, SAXO Bank |
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Facebook |
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DTU Compute |
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Decision3, Thorshavn |
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ISG Denmark |
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Early work on
Independent Component Analysis (ICA)
see
also the publication repository
, or NEC's citeseer
Return to Section for
Cognitive Systems homepage.