At MPI-IS, we answer fundamental questions about intelligence and how to create intelligent behavior in machines and pioneer new solutions by combining research in hardware, software, and theory. With a strong commitment to interdisciplinary collaboration, we seek to advance the field by exploring how computational, physical, and social intelligence can work together to solve complex real-world problems. Research at our institute is organized into six departments and numerous independent research groups, each with a different focus, led by our faculty of Directors, Group Leaders, and Max Planck Fellows.
The problems studied in the department can be subsumed under the heading of empirical inference, i.e., inference performed on the basis of empirical data. This includes inductive learning (estimation of models such as functional dependencies that generalize to novel data sampled from the same underlying distribution), or the inference of causal structures from statistical data (leading to models that provide insight into the underlying mechanisms, and make predictions about the effect of interventions). Likewise, the type of empirical data can vary, ranging from biomedical measurements to astronomical observations. Our department is conducting theoretical, algorithmic, and experimental studies to advance study of empirical inference.
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Have you noticed that computers can show beautiful images and play clear sounds, but they don't let you physically touch digital items? Similarly, most robots are surprisingly unskilled at physically interacting with the real world and with people.
Led by Katherine J. Kuchenbecker, the MPI-IS Haptic Intelligence department aims to elevate and formalize our understanding of touch cues while simultaneously discovering new opportunities for their use in interactions between humans, computers, and machines.
We leverage scientific knowledge about the sense of touch to create haptic interfaces that enable a user to interact with virtual objects and distant environments as though they were real and within reach. One key insight in this endeavor has been that tactile cues, such as high-frequency tool vibrations and the making and breaking of contact, convey rich mechanical information that is necessary to make the interaction feel real. This research led us to realize that autonomous robots can also benefit from attending to the dynamic tactile cues that occur as they manipulate objects in their environment and engage in social physical interaction with humans.
Our research uses Computer Vision to learn digital humans that can perceive, learn, and act in virtual 3D worlds. This involves capturing the shape, appearance, and motion of real people as well as their interactions with each other and the 3D scene using monocular video. We leverage this to learn generative models of people and their behavior and evaluate these models by synthesizing realistic looking humans behaving in virtual worlds.
This work combines Computer Vision, Machine Learning, and Computer Graphics.
The department aims to understand the underlying principles of physical intelligence of single and collectives of biological organisms at milli- and micrometer length scales, and realize advanced physical intelligence capabilities on small-scale mobile robots using such principles. As the societal and translational research mission, the team aims to apply these tiny robots as minimally invasive and implantable wireless medical robots inside our body to revolutionize medicine and healthcare. The highly interdisciplinary team has expertise in robotics, micro/nanotechnology, materials science, engineering, physics, biology, chemistry, and medicine. Until 2023, Metin Sitti headed the Physical Intelligence Department. He is now President of Koç University and a Guest Scientists at MPI-IS
The Robotic Materials Department aims to fundamentally challenge current limitations of robotic hardware, using an interdisciplinary approach that synergizes concepts from soft matter physics and chemistry with advanced engineering technologies, to devise robotic materials capable of creating intelligent machines that mimic the astonishing versatility and adaptability of organisms in nature. Our department investigates three broad areas of research including soft robotics, functional materials and energy capture, with the current focus on soft electrostatic actuator systems based on multi-phase, multi-layer dielectrics. We aim to rapidly bring our discoveries from fundamental materials science, all the way to the development of bioinspired and wearable robotic systems.
At Social Foundations of Computation, we build scientific foundations for machine learning and artificial intelligence in the social world. To chart and implement a society’s norms and expectations, we start from concepts and work our way towards applications. Challenging existing problem formulations when necessary, we think through how the use of machine learning distributes societal resources and opportunity. Computational tools to critically evaluate - and possibly contest - algorithmic systems and their impacts are a key component of our work. Our ultimate goal is to promote a positive role of artificial intelligence in society.
Former Departments & Research Groups
As part of the Max Planck Society, we are committed to sharing our research findings with the scientific community and the public. Our researchers publish their results in top-tier journals and at conferences, making our knowledge and discoveries accessible to everyone.
List of publications
Our institute offers a range of doctoral programs that provide aspiring researchers with diverse opportunities to explore the fields of AI, machine learning, computer vision, and robotics. Through our partnerships with renowned universities, we offer collaborative pathways to complete your studies and obtain a doctoral degree.
Our programs, including the International Max Planck Research School for Intelligent Systems (IMPRS-IS), the Max Planck ETH Center for Learning Systems (CLS) program, and the ELLIS PhD program, offer a unique blend of research and academic experience, with opportunities to work with leading experts and collaborate with other institutions.
Learn more about our doctoral programs