Picture of  Patrick van der Smagt

Patrick van der Smagt

current: Head of AI Research, data lab, VW Group

Previous: Director of BRML labs
fortiss, An-Institut der Technischen Universität München
Professor for Biomimetic Robotics and Machine Learning, TUM

Chairman of Assistenzrobotik e.V.

In heading a research lab focussing on machine learning and its application in robotics, biomimetics and sensory data processing, my goal is to develop the techniques to model and use (human) movement.

The slides of my Keynote on end-to-end learning at the 2015 IROS conference are available here.

Visit my blog.


Best Paper Award, Int Conf on Neural Information Processing (ICONIP 2014)
King-Sun Fu Best 2013 Transactions on Robotics Paper Award (2014)
Harvard Medical School/MGH Martin Research Prize (2013)
Erwin Schrödinger Award, Helmholtz Gesellschaft (2012)
SfN BCI Award Finalist (2012)
TUM Leonardo da Vinci Award (2008)
IEEE Best Paper Awards
Beckmann Institute Fellowship (1995)
NACEE Fellowship

in the press

various sources, e.g. NY Times, May 16, 2012: on a brain-controlled robotics experiment
Bayerische Rundfunk, May, 2012: "Wenn Rechner immer intelligenter werden", Radio Wissen
n-tv, June 10, 2010: EMG-controlled robotics
pinc, May 18, 2009, "biorobotics"
Het Financieele Dagblad, May, 2009
Discovery Channel, April 2009: "Future Homes"
3Sat, April 22, 2007: "Z wie Zukunft"
RTLII, March, 2007: "Welt der Wunder"
Pro7, Nov. 5, 2006: "Wunderwelt Wissen"
Abendzeitung, Oct. 28, 2006: Bestnoten für Forscher und Unternehmen
ZDF: Heute Journal, Sep. 15, 2006: Interview
ORF: "Newton" Science report, April 30, 2006: report on advanced prostheses
Süddeutsche Zeitung, Mar. 03, 2006: "Künstliche Hand am Computer entwickelt"
Süddeutsche Zeitung, Jan. 26, 2006: "Direkter Draht zum Hirn"

We were and are funded by various sources, including:
DFG project "SPP autonomous learning" (2012-2015)
NEUROBOTICS (EC project, 2005-2009)
NINAPRO (Swiss project, 2010-2013)
SENSOPAC (EC project, 2006-2010)
STIFF (EC project, 2009-2011)
THE (EC project, 2010-2014)
VIACTORS (EC project, 2009-2012)

on publishing

In June 2012 I resigned as editor of Neural Networks (Elsevier). Having worked with Neural Networks for almost 20 years, I have come to realise that the publication model propagated by behind-paywall publishers no longer combines with my own views of publication DOs and DONTs.  In particular, I have decided to move away from classical publication methods towards open access publishing, now that such alternatives are maturing.

After so many years of research and publishing, it is clear that only a peer-to-peer (double-open) review system with open access to the publications can be fair and unbiased.

I am currently still editor of Biological Cybernetics, as the open access model is being supported by Springer. However, also that large publishing house will have to rethink their approach to scientific publication before long.

Reviewing is good.  But open publication is an alternative.  My blog is an attempt to solve, for my own benefit, this publication issue.

Title: The locally linear nested network for robot manipulation Proceedings of the IEEE International Conference on Neural Networks
Written by: Smagt P van der, Groen F, Groenewoud F van het
in: 1994
Volume: Number:
on pages: 2787--2792
how published:

pdf bibtex


Abstract: We present a method for accurate representation of high-dimensional unknown functions from random samples drawn from its input space. The method builds representations of the function by recursively splitting the input space in smaller subspaces, while in each of these subspaces a linear approximation is computed. The representations of the function at all levels (i.e., depths in the tree) are retained during the learning process, such that a good generalisation is available as well as more accurate representations in some subareas. Therefore, fast and accurate learning are combined in this method. The method, which is applied to hand-eye coordination of a robot arm, is shown to be superior to other neural networks.