Members

Felix Wichmann

Group Leader

+49 7071 29 70421
Room no. 10-5/A24
felix.wichmann[at]uni-tuebingen.de
Office Hours

Research:
My laboratory investigates human perception combining psychophysical experiments with computational modelling. Currently we have four research foci: First, to improve our image-based model of early spatial vision. Second, to connect early spatial vision with mid-level vision: perceived lightness, brightness and contrast in relation to surface reflectance and illumination in images of real scenes. Third, we investigate differences and similarities between deep convolutional neural networks and human object recognition. Fourth, we explore connections between causality from a perceptual as well as a machine learning perspective.
 

Felix Wichmann received his B.A. (1994) and DPhil (1999) in Experimental Psychology from the University of Oxford. After post-doctoral research at the University of Leuven (2000-2001), he worked as a research scientist in the Empirical Inference Department at the Max Planck Institute for Biological Cybernetics in Tübingen (2001-2007). From 2007 to 2011 he was Associate Professor (W2) at the Technical University of Berlin and since 2011 he is Full Professor (W3) at the Eberhard Karls Universität Tübingen.

Silke Gramer

Administration
+49 7071 29 70420
Room no. 10-5/A21
silke.gramer[at]uni-tuebingen.de

Uli Wannek

Senior Research Scientist 
+49 7071 29 70580
Room no. 10-7/A3
uli.wannek[at]uni-tuebingen.de

Research:
Accurate measurements need an accurate experimental setup and precise control devices as well as reliable software. My interest is precision psychophysics and so I administer our pool of fine instruments and servers, help improving our psychophysics lab, and then am able to perform exciting experiments.

Uli studied Physics at the Eberhard Karls Universität Tübingen and received his Diplom (thesis in Universitäts Augenklinik Tübingen) in 1994. In 1999 he finished his PhD in Biology at the Max Planck Institut für biologische Kybernetik in Tübingen. From 1998 until 2011 he worked as an electronic engineer in the Institut für physikalische Chemie of the Johannes Gutenberg Universität in Mainz. Since 2012 he is a Senior Scientist in the Faculty of Science, Department of Computer Science at the Eberhard Karls Universität and Bernstein Center for Computational Neuroscience in Tübingen.

Lukas Huber

Co-supervised PhD student @ NIP and Prof. Dr. Fred Mast, University of Bern
+49 7071 29 70420
Room no. 10-29/A3
lukas.s.huberspam prevention@unibe.ch

Research:
Successful recognition and categorisation both demand the availability of robust mental representations of objects. In contrast to machines, humans learn such representations from relatively little visual input. In his PhD project, Lukas uses a combination of psychophysical experiments and comparison-based machine learning methods to investigate the process in which such representations are learned. More specifically, he studies how brain-internal generative processes, such as mental imagery, may act as a biological form of data augmentation that facilitates the data-efficient acquisition of robust object representations.

Lukas received his B.Sc. and M.Sc. in Psychology from the University of Bern, Switzerland. His PhD project, "Creating to perceive: The role of mental imagery in visual object recognition and categorisation", is founded by a career grant from the Swiss National Science Foundation (SNSF) and is jointly supervised by  Felix Wichmann (Neural Information Processing, University of Tübingen) and Fred Mast (Cognitive Psychology, Perception and Research Methods, University of Bern).

Maryam Jannati

PhD student @ NIP
+49 7071 29 70581
Room no. 10-5/A19
maryam.jannatispam prevention@uni-tuebingen.de

Research:
Improvement and extending current early vision models rely on experimental psychophysical measurements to accurately represent brain function and behavior. However, comprehensive and meaningful datasets from classical gratings experiments to natural scene images and different types of noises are lacking for evaluating them. I design psychophysics experiments, collect and analyse behavioral data to assess early spatial vision with high precision of the physical properties of the stimuli, experimental setup, and equipment. By that, I intend to improve the evaluation of the standard model of human early spatial vision. Moreover, I aim to extend this standard model to imitate physiological properties of the primary visual cortex, such as asymmetric responses to dark and light signals.

I earned my B.Sc. and M.Sc. in Clinical Psychology from Shiraz University and Shahid Chamran University of Ahvaz, Iran. My interest in experimental and computational studies and the human brain led me to gain another M.Sc. in Cognitive Neuroscience from the University of Trento, Italy. My PhD is supervised by Prof. Felix Wichmann and is funded by the BBVA Foundation research program, Spain.

Thomas Klein

Co-supervised PhD student @ NIP and Wieland Brendel's lab
+49 7071 29 70582
Room no. 10-31/A4
t.kleinspam prevention@uni-tuebingen.de

Research:
Modern Machine Learning systems like Deep Neural Networks perform surprisingly well on hard visual tasks like object recognition and classification. But we do not yet understand the intermediate representations learned by these systems, which makes it hard to explain their decisions. This is a problem, because we cannot entrust AI-systems with important tasks in the real world if we don’t understand them. I work at the intersection of psychology and robustness research to develop methods that can help us better understand neural networks.

Thomas studied Cognitive Science (2015-2019) and Computer Science (2020-2022) at Osnabrück University before joining NIP as a PhD student. He is jointly supervised by Felix Wichmann (Neural Information Processing) and Wieland Brendel (Robust Machine Learning).

Jannik Reichert

PhD student @ NIP
+49 7071 29 70582
Room no. 10-31/A4
jannik.reichertspam prevention@uni-tuebingen.de

Research:
The standard model of human early spatial vision is based on channels for spatial frequency and orientation followed by contrast gain control. My work focuses on improving and extending this model to accommodate psychophysical data in an image-computable manner and account for the multitude of recurrent connections in the primary visual cortex as well as integrating the model into a longer pipeline of human vision from the retina to higher-level processing.

Before joining the Neural Information Processing group in Tübingen, I studied Computer Science (BSc) at Technische Universität Berlin with an exchange year at École polytechnique fédérale de Lausanne (EPFL) and Mathematics and Foundations of Computer Science (MSc) at the University of Oxford. I am a doctoral student in CS@max planck – The Max Planck Graduate Center for Computer and Information Science supervised by Felix Wichmann.

Marvin Theiß

PhD student @ NIP
+49 7071 29 70581
Room no. 10-5/A19
marvin.theissspam prevention@uni-tuebingen.de

Representational similarity analysis is one of many metrics used to assess the representational alignment of two or more decision-making systems by quantifying the similarity of activity patterns extracted from these systems. Many of these alignment metrics have been used extensively to compare the intermediate representations learned by deep neural networks with neural data collected from primates and humans, often finding a high degree of alignment between the two. Recently, however, several studies have highlighted some of the methodological limitations of these metrics. I am interested in developing improved metrics that allow us to make more robust and meaningful inferences about the alignment between computational models and the human visual system.

Marvin studied Mathematics (BSc & MSc) at the University of Marburg. After a short stint in the asset management industry, he returned to university to earn a degree in Mind, Brain and Behavior (MSc) from the University of Giessen. Prior to joining NIP, Marvin spent three months as a project research intern at the Gatsby Computational Neuroscience Unit at University College London. A scholar of the International Max Planck Research School for Intelligent Systems (IMPRS-IS), he is supervised by Felix Wichmann.

Peter Brederlow

Student research assistant @ NIP since 11/2025

Ben Fausten

Student research assistant @ NIP since 11/2025

Florian Seuffert

Student research assistant @ NIP since 04/2024

Matilda Wehling

Student research assistant @ NIP since 04/2024