Understanding intelligence is one of the great scientific challenges of our time. But, in spite of extensive research efforts spanning many scientific disciplines, our understanding of intelligence remains fragmented and incomplete. Science of Intelligence will fundamentally advance our understanding of intelligence, integrate and unify theories, concepts, and insights from existing intelligence-related disciplines, catalyze progress in these disciplines, and - perhaps most importantly - advance our ability to construct intelligent technological artifacts for applications of societal importance.
Rasha Abdel Rahman
HU Berlin, Psychology
Rasha Abdel Rahman is a psychologist. She investigates basic cognitive processes, with a special interest in the multi-faceted aspects of semantic processing and learning. She focuses on semantic influences on visual perception of faces and objects, language production and comprehension. Integrating these fields, she is conducting studies on the interface between visual perception, semantics, emotion, and language during social communication. She employs behavioral and electrophysiological methods.
TU Berlin, Philosophy
Sabine Ammon is a philosopher with a focus on philosophy of engineering science and design research. She has experience in the dynamics of knowledge in the design sciences with a special interest in the epistemic interrelation of artefacts (such as images, models, prototypes), simulation, concepts, and theories in processes of science building.
TU Berlin, Robotics
Oliver Brock represents the synthetic discipline robotics. He has extensive experience in building real-world robotic systems, contributing also to related disciplines, including perception and machine learning. Within the fields of robotics, he is a leader in leveraging collaborations with analytical disciplines, in particular psychology and behavioral biology, to work towards an understanding of embodied intelligence.
HU Berlin, Adaptive Systems
Verena Hafner represents the synthetic discipline of robotics. She focuses on sensorimotor interaction and development. She has investigated open-ended development and social interaction in artificial agents that attracted high interest in the cognitive and developmental robotics community and she has substantial experience in interdisciplinary cooperation.
HU Berlin, Psychology
John-Dylan Haynes is an expert in several fields of cognitive neuroscience that are relevant for SCIoI. He has worked on executive processes, such as the neural mechanisms of intentions and volitional control, on conscious and unconscious information processing and on information flow between brains during communication. He has also investigated neurotechnological applications, especially whether it is possible to decode a person’s thoughts from patterns of their brain activity.
TU Berlin, Computer Vision
Olaf Hellwich contributes to the autonomous acquisition of prior knowledge from visual experience and the application of the priors learned from that experience. He posseses expertise in feature extraction, learning of object models from features, 3D object reconstruction, and most recently deep learning.
Max Planck Institute for Human Development, Lifespan Psychology
Ralph Hertwig studies human cognitive abilities, bringing together concepts and methods from psychology, neuroscience, economics, philosophy, biology, and mathematics. He investigates how biological cognitive strategies (heuristics) arise, perform, and vary under natural resource constraints. His work spans individual and group cognition.
HU Berlin, Biology
Jens Krause’s research will be part of the behavioral biology component of SCIoI. He and his group have developed an interactive robotic fish which is recognised by live fish as a conspecific. This robot is used to investigate basic principles of collective behavior and collective cognition. In particular they are interested in the way in which group-living organisms process information to deal with environmental challenges and how they come to collective decisions that are adaptive. Their interactive robot can embody the algorithms that they identified in biological agents and thereby allows them to test their validity. In order to give their robots realistic behaviour (as fish) they address the issues of dimensionality reduction and cursive interaction which are central to SCIoI.
TU Berlin, Philosophy of Embodiment
Miriam Kyselo is a philosopher and cognitive scientist. Her expertise lies in enactive, extended, and embodied cognition. She develops a cross-disciplinary model of the self and addresses the question how bodily and social processes relate to individual agency. In her work, she combines analytic philosophy, phenomenology, psychology, neuroscience, and robotics.
U Potsdam, Educational Science
Rebecca Lazarides is an educational researcher with interests in learning and instruction, motivational and cognitive learning processes in adolescence, gendered socialization processes and motivational development in education. Her research connects the fields of educational psychology, educational science, motivational and cognitive psychology. Within SCIoI, she will investigate the role of instruction and feedback for cognitive learning processes, intrinsic motivation, and attention.
FU Berlin, Behavioral Biology
Lars Lewejohann is a behavioral biologist with a broad experience in analyzing behavioral systems, including exploration, learning and memory, emotions, and social behavior. In his research, he already routinely employs methods from the synthetic disciplines.
TU Berlin, Psychology
Marianne Maertens’ research bridges the areas of computer science and psychology. Her key competencies are in experimental research methods and the study of human vision. To SCIoI, she will provide the empirical expertise to study perception, learning and (inter)action at the system level.
TU Berlin, Neural Information Processing
Klaus Obermayer will contribute in machine learning and computational neuroscience by studying reward-based learning, reinforcement learning, and decision making both in artificial systems and in human subjects, the latter in collaboration with the experimental partners of the planned cluster. He will also examine the emergence of sensory representations and how they interact with decisions in the perceptual domain.
TU Berlin, Artificial Intelligence
Manfred Opper represents the synthetic disciplines AI and machine learning. He applies methods of probability theory, statistical physics, and information theory to the analysis of the collective behaviour of systems which are composed of a large number of entities. Examples of such systems are learning and inference algorithms, neural networks and interacting agents.
Max Planck Institute for Human Development, Psychology
Thorsten Pachur is a psychologist. He studies the cognitive foundations of decision making. In particular, he is interested in understanding how the human mind, given informational and computational constraints, can master an uncertain world.
HU Berlin, Philosophy of Mind
Michael Pauen is a philosopher with a focus on the philosophy of mind. As the academic director of an interdisciplinary graduate school, he has extensive experience in interdisciplinary research and training. Having a specific interest in philosophical and psychological aspects of human sociality, he will focus on social intelligence both in humans and in artificial systems.
TU Berlin, Control
Jörg Raisch represents the discipline control. His research interests include both methodological and applied aspects of control. In the context of SCIoI, his work on abstraction-based synthesis of discrete event and hybrid control systems, on consistent control hierarchies, and on consensus-based control of multiagent systems will be particularly relevant.
HU Berlin, Active Vision and Cognition
Martin Rolfs represents the analytic discipline psychology. His research builds on the premise that any deep understanding of sensation and perception requires studying its key processes in observers that actively explore their environment. He investigates selective processes in active vision. His research combines eye tracking, motion tracking, psychophysics, computational modeling, EEG, and studies of clinical populations.
HU Berlin, Behavior Modeling
Pawel Romanczuk works at the interface of applied mathematics, theoretical physics, and behavioral biology. He focuses on collective behavior of organismic systems. His research bridges analytical and synthetic sciences to study self-organization, evolutionary adaptations, and functional dynamical behavior.
TU Berlin, Sociology
Ingo Schulz-Schaeffer represents the discipline of sociology of technology and innovation. He has experience in research on the social shaping of technology with a special interest in the shaping of technological innovations by socio-technical scenarios and their prototypical realizations.
TU Berlin, Modeling of Cognitive Processes
Henning Sprekeler represents the analytical discipline computational neuroscience. He has extensive expertise in computational modelling of synaptic plasticity and its consequences for behavioural learning and the formation of memories. He has also worked on the self-organised development of high-level sensory representations, an essential prerequisite for intelligent behaviour.
FU Berlin, Behavioral Biology
Christa Thöne-Reineke represents the analytical discipline of behavioral biology. She has extensive experience in laboratory animal science and animal models, especially in animal behavior as read out for severity assessment and animal welfare. She will study the costs and benefits of cognition and the influence of emotion and well-being on animal behavior.
Architecture of attentional processes in active vision
PI: Martin Rolfs
This project bridges the analytic disciplines psychology and neuroscience with synthetic approaches (i.e., computational models).
We aim at a better understanding of selective processes that promote efficient resource allocation for perception, memory, and motor control in active vision.
Collective intelligence and decision making with application to medical information processing
This project bridges the areas of psychology, biology and has immediate implications for all domains in which individuals and collectives of individuals make consequential decisions such as in medical diagnostics.
The key question is under what circumstances does it pay to combine the intelligence of individuals because the collective can outperform the best individual.
Communication: interplay between verbal, visual and social-emotional influences
Image copyright: © SEPS:Curtis Publishing, Indianapolis
Human communication involves the simultaneous processing of information from different modalities and the coordinated use of core verbal and non-verbal cognitive functions, including language production and comprehension, face identity and expression perception, semantic and emotion processing, and social cognition. The project aims at understanding and describing these core functions and their interactions from a social-communicative perspective.
Deep learning with robotic priors; combining deep learning and algorithms
PI: Oliver Brock
Image copyright: CC-BY-SA
This project lies at the intersection of robotics and machine learning. The goal is to enable robots to learn in a data-efficient way by providing certain prior knowledge. More specifically, we provide the robot with algorithms and let it learn to use those using deep learning.
Effects of social learning environments on cognitive development
This field of research investigates the role that social learning environments (e.g., instructional settings) play for developmental dynamics in human cognition. It bridges the areas of psychology, educational sciences and robotics by developing mathematical models of processes that define the transfer between teachers and learners.
Influence of emotions on information processing
Integrating complex environmental and social information into decision making can be facilitated by reducing dimensionality through emotions. By analysing and experimentally testing living as well as artificial model organisms we will explore possibilities of cost-reduction in artificial cognition (e.g., battery, memory, processor and sensory capabilities).
Influences of prior knowledge on face and object perception
The project combines psychological and neuroscientific approaches to understand how effects of different domains of knowledge (e.g., linguistic, functional-semantic, social and affective knowledge) on low and high-level stages of face and object perception.
Investigating the Dynamics of Self and Social Cognition
This project combines philosophical inquiries on self and social cognition with research in developmental robotics. Drawing on research from philosophy and human psychology, we aim at a better understanding of the dynamics and processes of group cognition and collaboration in synthetic multi-agent scenarios.
Iterative learning control to adapt neuroprostheses to individual users
PI: Jörg Raisch
This project uses Iterative Learning Control (ILC) to develop adaptive neuroprostheses that can be used in stroke rehabilitation. It aims at automatically adjusting the intensity of artificial muscle stimulation to induce near physiological repetitive movements. Standard ILC, however, requires rather strict assumptions as, e,g., identical duration of all cycles in periodic motions. As this is rarely true in biomedical applications, an integral part of this project has been to appropriately extend the underlying theory.
Life transitions and adaptive development of socio-cognitive characteristics
The project connects theoretical approaches from educational science, psychology, sociology and robotics by studying how the interaction between a learner and a teacher during life transitions affect the development of socio-cognitive characteristics.
Manual dexterity in humans and robotic systems and associated cognitive abilities
Human grasping skills are far superior to those of robots. We investigate the principles that lead to this superior performance in human grasping and work towards transferring these principles to robotic systems. Our key hypothesis is that human grasping performance crucially depens on the purposeful exploitation of contact with the environment.
Models of collective cognition in swarms
The project connects the synthetic disciplines of computer science, applied mathematics and theoretical physics with behavioral biology. This is done by exploring collective decision making and information processing in animal groups, developing mathematical models, and extracting biologically inspired algorithms of collective cognition.
Physical Exploration Challenge
PI: Oliver Brock
One of the hallmarks of human development is exploratory behavior. In this project, we develop robots that explore the degrees of freedom in their environment (door handles, drawers, scissors, etc.). To generate such behavior we have to address questions of representation, action selection, and embodiment.
Shape priors for 3D object recognition
PI: Olaf Hellwich
3D object recognition requires comparison of currently perceived shape with a priori information. In ongoing research, we learn shape priors from training objects showing that the estimated shape prior is capable to express fine details to a certain degree. By applying shape priors to technical measurements the accuracy and completeness of reconstructed models can be significantly increased. Future work will investigate how humans make use of shape priors when perceiving shape, and how technical representations differ from biological ones.
Studying Science of Intelligence
The Master track Science of Intelligence provides an ideal learning experience for future SCIoI researchers. It offers training on intelligence-related topics (perception, reasoning, learning, etc.) from the complementary perspectives of computer science and psychology. This prepares Master’s students for bridging synthetic and analytic disciplines. The experience gained in this training program will inform the design of the SCIoI curricula for the Master’s program. If you are already enrolled as a Master Student in Computer Science at TU Berlin have a look at the curriculum which focusses on SCIoI-related topics.