Matthias

Matthias Bethge

Publications, Email, Homepage, Phone: +49 7071 29 89017
Group Leader
My research goal is to understand how the brain makes sense of its high-dimensional sensory input. In particular, I seek to understand the formation of distributed neural representations in the visual system by studying deep neural networks, natural image statistics, unsupervised learning, and neural population coding, and by developing new data-analysis tools.
Heike

Heike König

Email, Phone: +49 7071 29 89018
Secretary
Judith

Judith Lam

Email, Homepage, Phone: +49 7071 29 89019
Bernstein Coordinator
At the Bernstein Center Tübingen, scientists from various disciplines, including theoretical and experimental neurobiology, machine learning, and medicine, collaborate in order to analyze the basis of inference processes in the brain. In particular, a main research goal is to understand the coordinated interaction of neurons during information processing.
Wieland

Wieland Brendel

Publications, Email, Phone: +49 7071 29 88910
Postdoc
My research goal is to close the gap between the visual information processing in humans and machines. One of the most striking differences is the susceptibility of Deep Neural Networks (DNNs) to almost imperceptible perturbations of their inputs. Getting machines closer to humans will require fundamentally new concepts to learn causal models of the world. My work aims to quantify the robustness of DNNs, to identify the causes for their susceptibility and to devise solutions by drawing inspiration from Neuroscience and Computer Vision.
Alexander

Alexander Ecker

Publications, Email, Phone: +49 7071 29 88908
Postdoc
I want understand how neural systems perform visual perception. At the interface of computer vision and neuroscience, I try to understand both, how the human visual system works and how to teach computers to make sense of images. I use an interdisciplinary approach that combines methods from machine learning and computer vision with behavioral studies and neuronal population recordings in the brain. My work is driven by the idea that we can advance artificial intelligence by understanding how biological systems implement intelligent behavior.
Alexander

Alexander Mathis

Publications, Email, Homepage
Postdoc
I am a Marie Curie fellow in the lab of Professor Venkatesh Murthy at the Department of Molecular and Cellular Biology at Harvard University and with Professor Matthias Bethge at the Bernstein Center for Computational Neuroscience at the University of Tuebingen. My main research interests comprise active sensing, odor-guided navigation and optimal coding.
Mackenzie

Mackenzie Mathis

Publications, Email, Homepage
Postdoc
My goal is to reverse engineer the neural circuits that drive adaptive motor behavior. To this end I am currently working on understanding neural population coding in the sensorimotor cortex collected during a skilled motor behavior in mice, and using deep learning methods for markerless tracking. My work in the Bethge lab is funded by Project ALS (Women & the Brain Fellowship for Advancement in Neuroscience).
Tom

Tom Wallis

Publications, Email, Homepage
Postdoc
How do we visually experience the world around us in a coherent way, simply from the patterns of photons hitting our retinae? While it seems effortless to us, the formation of this representation by the brain is decidedly difficult to explain. I am working with Prof. Bethge and Prof. Felix Wichmann investigating the mechanisms of visual representation using psychophysics and computational modelling.
Christian

Christian Behrens

Publications, Email
Graduate Student
I work on neural coding in the retina and data analysis.
Alexander

Alexander Böttcher

Publications, Email, Phone: +49 7071 29 88905
Graduate Student
My aim is to understand how the activity of sensory neurons leads to decisions taken by the brain. In particular, I am interested in neural population coding of the primary somatosensory cortex.
Santiago

Santiago Cadena

Publications, Email
Graduate Student
Christina

Christina Funke

Publications, Email
Graduate Student
Leon

Leon Gatys

Publications, Email, Phone: +49 7071 29 88907
Graduate Student
Deep convolutional neural networks are the first artificial systems that rival biology in terms of difficult perceptual inference tasks such as object recognition. At the same time, their hierarchical architecture and basic computational properties admit a fundamental similarity to real neural systems, making them compelling candidate models for studying visual information processing in the brain. Thus in my PhD project I seek to infer the neural organisation of visual perception from high-performing convolutional neural networks.
David

David Klindt

Publications, Email
Graduate Student
Matthias

Matthias Kümmerer

Publications, Email, Phone: +49 7071 29 88909
Graduate Student
Learning what properties of an image are associated with human gaze placement is important both for understanding how biological systems explore the environment and for computer vision applications. Recent advances in deep learning for the first time enable us to explain a significant portion of the information expressed in the spatial fixation structure. My interest is twofold: I want to create better models for predicting human fixations in different tasks and on the other hand make use of these models to increase our understanding of how humans perform this task from a neuroscientific and psychophysical standpoint.
Claudio

Claudio Michaelis

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Graduate Student
Jonas

Jonas Rauber

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Graduate Student
Ivan

Ivan Ustyuzhaninov

Publications, Email
Graduate Student
Pranav

Pranav Mamidanna

Email
Research Assistant
Oliver

Oliver Eberle

Publications, Email
Master Student
?

Marissa Weis

Publications, Email
Master Student
University of Tuebingen BCCN CIN MPI