Download Kristin Völk – Curriculum Vitae

Kristin Völk
Curriculum Vitae
Personal Information
Name
Address
Date of Birth
Nationality
Gender
Phone
E-mail
Kristin Völk
12 Kean House, SE17 3TG London, United Kingdom
21.07.1986
German
Female
+44 7748 338200
[email protected]
Languages
German mother tongue
English fluent
Education
Master of Philosophy studies in Theoretical Neuroscience
09/2012 - Present Gatsby Computational Neuroscience Unit, University College London
Target Degree Master of Philosophy, expected April 2015
Project Predictiveness and prediction in classical conditioning: a Bayesian statistical
model (working title)
Supervisor: Peter Dayan
Master of Science in Neural Systems and Computation
09/2010 - 09/2012 ETH Zürich
Master Thesis Self-Organization of Spinal Reflexes in a Biologically Motivated Simulation
Framework
Supervisor: Prof. Tobi Delbruck
Advisors: Prof. Fumiya Iida, Dr. Hugo Gravato Marques
1. Short Project Spike-Based Reward-Modulated Hebbian Learning of Decision Making
Supervisor: Dr. Daniel Kiper
Advisor: Dr. Michael Pfeiffer
2. Short Project Self-Organization of Spinal Reflexes in an Agonist-Antagonist Muscle Model
through Musculoskeletal Interactions
Supervisor: Prof Tobi Delbruck
Advisors: Prof. Fumiya Iida, Dr. Hugo Gravato Marques
12 Kean House – SE17 3TG London, United Kingdom
H +44 7748 338200 • B [email protected]
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Bachelor of Science in Computer Science
04/2007 - 09/2010
10/2006 - 03/2007
Minor Subject
Bachelor Thesis
TU Munich
Saarland University
Mathematics
Gait Improvement of a Humanoid Robot with Reinforcement Learning
Supervisor: Prof. Dr. Jürgen Schmidhuber
Advisor: Dipl. Inf. Thomas Rückstieß
Secondary School
09/1996 - 06/2006 Arnold-Gymnasium Neustadt b. Coburg
Term Paper Flexible Robot Control with Artificial Neural Networks
Qualification High School Diploma (Abitur)
Primary School
09/1992 - 07/1996 Erich-Luther Schule, Rödental/Mönchröden
Skills
Programming Python, Java, Matlab, C, SML, Assembler, Microcontroller programming in C
Electronics Schematics and Layout (mainly for AVR microcontrollers with sensor inputs and
DC motor/servo control) in CadSoft EAGLE, Assembly, Test and Debugging
Mechanics Designing parts with the CAD software Pro/ENGINEER Wildfire, knowledge
about the CNC milling process for aluminium and carbon fibre parts
Project Organisation Experience in project management (during a software project involving ∼40
students I had the opportunity of organising a team of 5 software developers,
while also being involved in the project’s overall software engineering decisions),
experience with agile software development (Scrum)
Publications/Posters
2013 Handbuch Kognitionswissenschaft; chapter IV.12 Neuronen, Algorithmen, Kognition; J.B. Metzler
08/2012 Self-organization of Spinal Reflexes Involving Homonymous, Antagonist and
Synergistic Interactions; In 12th International Conference on Simulation of
Adaptive Behavior (SAB 2012)
06/2012 Self-Organization of Spinal Reflexes through Soft Musculoskeletal Interactions;
In 4th IEEE RAS/EMBS International Conference on Biomedical Robotics
and Biomechatronics (BioRob 2012)
04/2012 A spiking neural network implementation of Bayesian learning and decision
making; ZNZ-Symposium (Neuroscience Center Zurich)
Internships
09/2009 - 10/2009 Max Planck Institute of Neurobiology Martinsried/Munich, Visual Coding
Group (Group Leader: Tim Gollisch)
07/2006 Loewe Opta GmbH Kronach
08/2005 - 09/2005 LivingLogic AG Bayreuth
12 Kean House – SE17 3TG London, United Kingdom
H +44 7748 338200 • B [email protected]
2/6
Awards
08/2008 Final acceptance into the German National Academic Foundation
01/2007 Preliminary acceptance into the German National Academic Foundation
2001 - 2007 multiple participations in “Jugend forscht” (German young scientist contest)
2006 Jugendpreis des Förderkreises der Mikroelektronik (Award donated by the
fundraising group for microelectronics)
Activities/Engagements
06/2014 Co-taught “Scientific Programming in Python” at UCL
Since 05/2011 Mentor for the CyberMentor project, supporting girls interested in natural
sciences and engineering
04/2008 Exhibition of my 2007 “Jugend forscht” project at the booth of the BMBF
(German Federal Ministry of Education and Research) at the “Hannover Messe
Industrie”
Since 2008 Judge for the German young scientist contest “Jugend forscht”
Research Experience
This section outlines the content of my current and previous research experiences.
Current Research
Working Title Predictiveness and prediction in classical conditioning: a Bayesian statistical
model
Description Classical conditioning is a rather pure form of prediction learning. Here we
focus on one of its critical facets that still lacks a statistical treatment, namely,
that conditioned stimuli (CSs) not only make different predictions, but also
can be differentially predictive. That is, some stimuli (and whole stimulus
dimensions) are relevant as predictors in one or more contexts; other stimuli
are not. We formalize the notion of predictiveness in a generative model in
which each CS is awarded two (hidden) random variables. One is a binary
indicator variable indicating the stimulus’ predictiveness; the other a realvalued weight indicating the current association between the stimulus and the
outcome (which is assumed to evolve according to the conventional dynamics
underpinning the Kalman filter). The net prediction is then generated according
to weights associated with those CSs that are both present and predictive. This
model reproduces standard conditioning paradigms like Blocking, BackwardsBlocking, Overshadowing and Latent Inhibition and offers new explanatory
values for the same.
12 Kean House – SE17 3TG London, United Kingdom
H +44 7748 338200 • B [email protected]
3/6
Master Thesis
Title Self-Organization of Spinal Reflexes in a Biologically Motivated Simulation
Framework
Description Based on experimental evidence we hypothesise that spinal reflexes self-organise
based on a correlation-based learning rule, which exploits the motor and sensor
activations following spontaneous muscle twitches (SMTs). It was the aim of the
thesis to test this hypothesis. Therefore we designed a simplified musculosceletal
model of the human leg using Matlab and the Simulink and SimMechanics
toolboxes. Given this model, we implemented biologically realistic muscle sensor
models and a spiking neural network model with a spike-timing based learning
rule. We verified that with the spiking-neural network implementation at least
parts of the reflex circuitry could be learned. Hence, we concluded that it
is indeed possible to self-organize these reflexes based on a self-organization
paradigm guided by SMTs.
2. Short Project (Zürich)
Title Self-Organization of Spinal Reflexes in an Agonist-Antagonist Muscle Model
through Musculoskeletal Interactions
Description This project is the precursor to my Master’s thesis. Here we developed the
musculoseletal model of the human leg using Matlab and the Simulink and
SimMechanics toolboxes. Furthermore, we verified that the non-spiking version
of the correlation-based learning rule would produce the desired output given
a simple agonist-antagonist muscle arrangement.
1. Short Project (Zürich)
Title Spike-Based Reward-Modulated Hebbian Learning of Decision Making
Description How near-optimal decision making under uncertainty for input and reward
signals can arise from local synaptic and neuronal mechanisms is an important
open question. Pfeiffer et al. presented in 2007 a neural circuit architecture in
which associations between sensory inputs, actions, and a stochastic reward
signal were learned with a Hebbian rule applied to pre-processed input. This
project is a spiking neural network implementation of this architecture. By
theoretical analysis and simulations, it was shown that the novel spike-triggered
learning rule matches the mathematical properties of the original model, such as
Bayes-optimal integration of multiple reward-predicting cues, and near-optimal
action selection.
12 Kean House – SE17 3TG London, United Kingdom
H +44 7748 338200 • B [email protected]
4/6
Bachelor Thesis
Title Gait Improvement of a Humanoid Robot with Reinforcement Learning
Description The application of reinforcement learning (RL) algorithms to complex learning
task in continuous state-action spaces is a still unsolved problem. Here, we
first investigate the performance of two algorithms from the Q-Iteration family
(neural fitted Q-Iteration (NFQ) and neural fitted Q-Iteration for continuous
actions (NFQCA)) on the standard cart pole benchmark problem. On this
relatively easy task NFQ outperformed NFQCA. The second part of the
thesis was concerned with building a fully-automated learning framework
for a real-world humanoid robot. Here an industrial robot arm was used to
track the humanoid robot, prevent damage in case of falling and to transport
the humanoid back to a predefined starting position. We used two different
regression algorithms to approximating the current, static walking behaviour of
the humanoid robot. A very promising approximation was achieved with locally
weighted projection regression (LWPR), while neural networks performed
poorly. It is the aim of future work to improve the robots gait by adapting
NFQCA to work with LWPR.
Jugend forscht
“Jugend forscht” is a German contest for young scientists and is structured into three levels. The first
is the regional level, the second the state level and the third the federal level. The winner in each
category (e.g. mathematics, engineering, biology, physics...) moves on to the next level. Here I want
to outline the two last projects with which I participated.
State level
2006
Title
Category
Awards
Bavaria
Flexible Robot Control with Artificial Neural Networks
Engineering
2nd place on state level, award sponsored by the metal and electrical industry
Description In this project I built a three wheeled robot (two actuated), which learned
to avoid obstacles by using artificial neural networks, trained with a back
propagation algorithm. The robot was built by myself, including the design
of the microcontroller circuit and the mechanics. In order to illustrate the
workings of the neural networks I developed a simulator in C, which used
colour coding to display the current activations of the single neurons.
Federal level
2007 Germany
Title An approach towards a self-adapting humanoid robot
Category Engineering
Awards 2nd place on federal level, award sponsored by the metal and electrical industry,
award for the best project in the area of neurosciences sponsored by the German
Neuroscience Society
12 Kean House – SE17 3TG London, United Kingdom
H +44 7748 338200 • B [email protected]
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Description This project involved mainly the design of my own humanoid (two-legged)
robot. This robot was equipped with twenty servo motors: two for each ankle
joint, one for each knee, three for each hip joint, two for the torso, two for each
shoulder joint and one for each elbow. The feet were designed in such a way
that resistance strain gauges could measure the weight distribution over the
feet. I designed the mechanical parts (consisting of aluminium and carbon fibre)
in the CAD software ProENGINEER. These parts were then manufactured on
a CNC mill. Additional I designed a circuit board to enable communications
between the robot and a PC. Finally the robot was made able to walk by
following a predefined set of rules.
12 Kean House – SE17 3TG London, United Kingdom
H +44 7748 338200 • B [email protected]
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