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BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230511T100000
DTEND;TZID=Europe/Berlin:20230511T110000
DTSTAMP:20260404T093726
CREATED:20230320T101238Z
LAST-MODIFIED:20240813T102328Z
UID:14994-1683799200-1683802800@www.scienceofintelligence.de
SUMMARY:Lauren Sumner-Rooney
DESCRIPTION:More details to follow. \nThis talk will take place in person at SCIoI. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-lauren-sumner-rooney/
CATEGORIES:Thursday Morning Talk
ATTACH;FMTTYPE=image/png:https://www.scienceofintelligence.de/wp-content/uploads/2023/03/Rooney-1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230506T100000
DTEND;TZID=Europe/Berlin:20230506T180000
DTSTAMP:20260404T093726
CREATED:20230418T103954Z
LAST-MODIFIED:20240813T102333Z
UID:15214-1683367200-1683396000@www.scienceofintelligence.de
SUMMARY:“Future of Air - Speculative Workshop Series” - Es liegt was in der Luft (in German)
DESCRIPTION:Workshop title: Es liegt was in der Luft \nTheme: Stage and the Environment\nWhere: Hochschule für Schauspielkunst Ernst Busch \n\n\nIm Anthropozän\, dem sogenannten ‘Zeitalter des Menschen’\, ist die Umwelt zur Bühne geworden. Auf dieser Bühne zeigen sich ökologische Ausnahmezustände und drohende klimatische Kipppunkte. Unsere Rolle ist es\, auszuhandeln\, wie es weitergehen kann: Der Verlauf der erdgeschichtlichen Erzählung liegt in unserer Verantwortung. \nWas passiert\, wenn wir klimatische Experimente in den Verhandlungsraum der Bühne holen? Wie kommen dort individuelle Erfahrungen\, statistische Daten und verkörpertes Wissen zusammen? Im Workshop suchen wir nach neuen Klima-Fiktionen\, die andere Geschichten von Emission\, von reisendem Staub und vom Wolkenmachen erzählen können. \nMit Inputs von Studierenden des Masterstudiengangs Spiel + Objekt \nAb 16 Jahren\, kostenfrei. \nRegistrierung offen bis zum 27.04.2023 \n\n\n  \nAbout the workshop series:\nAir is invisible. Air surrounds us and connects us – as people and as living beings. Air is material. What happens when we become aware of air? What\ndoes air tell us? How can we deal with it – now and in the future\, individually and as societies? In the workshop series „Futures of Air“ we invite you to speculate about the futures of air – together with researchers from the Clusters of Excellence „Matters of Activity“ and „Science of Intelligence“. In three independent co-design workshops\, we explore the properties of air as a material\, negotiate its role in our lives\, and imagine possible (and impossible) futures with it. We are looking for people ages 16 and up who are interested in speculating with us – people interested in materials\, experimenters and the curious. \nFurther information and registrationat: www.collactive-materials.de \n 
URL:https://www.scienceofintelligence.de/event/future-of-air-speculative-workshop-series-es-liegt-was-in-der-luft-in-german/
CATEGORIES:External Event
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230504T160000
DTEND;TZID=Europe/Berlin:20230504T173000
DTSTAMP:20260404T093726
CREATED:20230119T093257Z
LAST-MODIFIED:20250212T103308Z
UID:14071-1683216000-1683221400@www.scienceofintelligence.de
SUMMARY:Guillermo Gallego (Science of Intelligence)\, "Event-based Vision at the TU Berlin Robotic Interactive Perception Lab"
DESCRIPTION:More details to follow.
URL:https://www.scienceofintelligence.de/event/pi-lecture-with-guillermo-gallego-2/
LOCATION:MAR 2.057
CATEGORIES:PI Lecture
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230504T100000
DTEND;TZID=Europe/Berlin:20230504T110000
DTSTAMP:20260404T093726
CREATED:20230320T100436Z
LAST-MODIFIED:20250603T125924Z
UID:14992-1683194400-1683198000@www.scienceofintelligence.de
SUMMARY:Radoslaw Cichy\, “Deep Neural Networks As Scientific Models of Vision”
DESCRIPTION:Abstract: \nArtificial deep neural networks (DNNs) are used in many different ways to address scientific questions about how biological vision works. In spite of the wide usage of DNNs in this context\, their scientific value is periodically questioned. I will argue that DNNs are good in three ways for vision science: for prediction\, for explanation\, and for exploration. I will illustrate these claims by recently published or still ongoing projects in the lab. I will also propose future steps to accelerate progress. \nThis talk will take place in person at SCIoI. \nPhoto kindly provided by Radoslaw Cichy. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-radoslaw-cichy/
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230427T130000
DTEND;TZID=Europe/Berlin:20230427T160000
DTSTAMP:20260404T093726
CREATED:20230418T091533Z
LAST-MODIFIED:20241007T112900Z
UID:15186-1682600400-1682611200@www.scienceofintelligence.de
SUMMARY:Girls' Day 2023 at SCIoI 
DESCRIPTION:It’s that time of year again! Every April\, school girls all over Germany visit scientific institutions to get inspiration for their future careers. SCIoI has participated in this event twice before\, and we will be hosting another group of girls this coming 27 April. The event will start with some inspiring talks by our members Maria Ott\, Julten Abdelhalim\, Vito Mengers & the RBO Team\, Magdalena Yordanova\, Nina Poth\, and Lea Musiolek. It will follow an interactive lab tour. Contact the Communication office if you would like to be involved in this exciting event. \nMore info here.
URL:https://www.scienceofintelligence.de/event/girls-day-at-scioi/
LOCATION:MAR 2.057
CATEGORIES:External Event
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230420T160000
DTEND;TZID=Europe/Berlin:20230420T173000
DTSTAMP:20260404T093726
CREATED:20230119T093158Z
LAST-MODIFIED:20240813T102404Z
UID:14068-1682006400-1682011800@www.scienceofintelligence.de
SUMMARY:Marcel Brass (Science of Intelligence)\, "Social agency"
DESCRIPTION:Abstract: Sense of agency (SOA) refers to the experience of controlling one’s\nown actions and corresponding effects. Social agency refers to SOA in situations\nwhere other social agents are involved. This can refer to situations in which we\nact together or in the presence of other agents or to situations where we\ncontrol the behaviour of others. I will discuss the concept of social agency and\nits relevance for topics such as collective behaviour and human-machine\ninteraction. Furthermore\, I will provide some empirical examples of\ninvestigating social agency.
URL:https://www.scienceofintelligence.de/event/pi-lecture-with-marcel-brass-2/
LOCATION:MAR 2.057
CATEGORIES:PI Lecture
ATTACH;FMTTYPE=image/jpeg:https://www.scienceofintelligence.de/wp-content/uploads/2023/01/20201020-SCIOI-Marcel2.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230420T100000
DTEND;TZID=Europe/Berlin:20230420T110000
DTSTAMP:20260404T093726
CREATED:20230320T095113Z
LAST-MODIFIED:20250603T125937Z
UID:14987-1681984800-1681988400@www.scienceofintelligence.de
SUMMARY:Friedhelm Hamann (Science of Intelligence)\, “Applications of Event Cameras: Animal Behavior Quantification in the Wild”
DESCRIPTION:Abstract: \nEvent cameras are novel bio-inspired sensors that naturally respond to motion in the scene. They have promising advantages\, namely a high dynamic range\, little motion blur and low latency. But how can we leverage these advantages for vision tasks such as animal behavior quantification? In this talk I will  present two applications developed at the Robotic Interactive Perception lab\, where we used event cameras to address practical problems\, from low-level vision (background-oriented schlieren imaging\, a technique for visualizing air flow) to high-level vision (animal behavior quantification in the wild). \nThis talk will take place in person at SCIoI. \nPhoto by Steve Johnson on Unsplash \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-scioi-project-36/
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230413T100000
DTEND;TZID=Europe/Berlin:20230413T110000
DTSTAMP:20260404T093726
CREATED:20230320T094941Z
LAST-MODIFIED:20250603T125951Z
UID:14984-1681380000-1681383600@www.scienceofintelligence.de
SUMMARY:Nina Poth (Science of Intelligence)\, “Exploring the Prospects for a Prediction-Oriented View of Intelligence”
DESCRIPTION:Abstract: It has recently been proposed that a minimal condition of intelligence is the ability to form accurate predictions (Tjøstheim & Stephens 2021). In this talk\, I evaluate the promise of this view for integrating intelligence research across subdisciplines within the cognitive and life sciences. I argue that this view combines two desirable features: (1) it allows us to subsume key dimensions identifying intelligent behaviour\, such as goal-directedness\, adaptiveness\, generality\, and flexibility (Coelho Mollo 2021; Glock 2019)\, under a unifying conceptual framework; (2) it combines well with a non-symbolic approach to representation at various degrees of abstraction (Gärdenfors 2004). Thereby\, the predictive view provides opportunities for sharing concepts and transforming problems across research on artificial and biological intelligence. However\, an outstanding issue with this approach is its current lack of insight into the relevant mechanisms and functional interactions generating intelligent behavior. I respond to this challenge by discussing a set of available research heuristics for mechanism discovery (Poth 2022).\n\nReferences \nCoelho Mollo\, D. (2022). Intelligent Behaviour. Erkenntnis\, 1-17.\nGärdenfors\, P. (2004). Conceptual spaces as a framework for knowledge representation. Mind and Matter\, 2(2)\, 9-27.\nGlock\, H. J. (2019). Agency\, intelligence and reasons in animals. Philosophy\, 94(4)\, 645-671.\nPoth\, N. (2022). Schema-centred unity and process-centred pluralism of the predictive mind. Minds and Machines\, 32(3)\, 433-459.\nTjøstheim\, T. A.\, & Stephens\, A. (2021). Intelligence as Accurate Prediction. Review of Philosophy and Psychology\, 1-25. \nThis talk will take place in person at SCIoI. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-nina-poth/
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230406T100000
DTEND;TZID=Europe/Berlin:20230406T110000
DTSTAMP:20260404T093726
CREATED:20221114T104605Z
LAST-MODIFIED:20240813T102441Z
UID:13325-1680775200-1680778800@www.scienceofintelligence.de
SUMMARY:Xing Li (Science of Intelligence)\, "Learning to Manipulate Articulated Objects From Human Demonstrations"
DESCRIPTION:Abstract: \nProgramming robots to manipulate articulated objects such as drawers\, doors\, or locks is a challenging task. One of the major reasons for this difficulty is that robots must physically interact with objects\, and even minor errors during manipulation can result in significant internal forces that may cause damage. \nWhile robots struggle with these manipulation tasks\, humans can effortlessly operate complex mechanisms with great reliability. Moreover\, humans can transfer their experience between objects of the same type\, resulting in remarkable generalization. This raises the question of how we can transfer these robust and general manipulation skills from humans to robots. \nIn this presentation\, we will introduce a viable solution to achieve this transfer in the context of manipulating articulated objects. Specifically\, we will demonstrate that a robot can acquire a manipulation policy that reliably manipulates various instances of the same type based on a single demonstration of a human opening an articulated object. \nFollowing the presentation\, we invite those who are interested to participate in an interactive session where we can discuss and share our experiences with controlling the robot with the soft hand in the robotics lab on the second floor. \nThis talk will take place in person at SCIoI. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-xing-li/
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230330T100000
DTEND;TZID=Europe/Berlin:20230330T110000
DTSTAMP:20260404T093726
CREATED:20230327T091603Z
LAST-MODIFIED:20240813T102500Z
UID:15096-1680170400-1680174000@www.scienceofintelligence.de
SUMMARY:Marah Halawa (Science of Intelligence)\, "Contrastive Learning Approaches for Computer Vision Applications"
DESCRIPTION:Abstract: \nThe recent success in Computer Vision has been mostly attributed to improved results using deep learning models trained on large labeled datasets. Many of these datasets have been labeled by humans. The labeling process\, however\, can be time-consuming\, and in many applications\, it may require expertise that could be costly to acquire. In order to address this requirement\, more research focus and effort have shifted toward unsupervised learning algorithms\, in order to utilize the ever-increasing quantities of unlabeled data. Self-supervised learning (SSL)\, in particular\, is a set of algorithms that specifically aim to learn rich data representations from unlabeled samples\, and it achieves comparable results to fully supervised methods on common benchmarks for image classification and segmentation. The idea behind SSL methods is to learn broad features from the signals that exist in unlabeled data. In other words\, to acquire more general information and knowledge\, and store them as neural network features that will be useful as prior knowledge for subsequent downstream supervised tasks (classification\, segmentation\, regression\, ..etc.). \nThere are two types of SSL methods. First\, self-prediction methods\, which predict some omitted parts (in purpose) of the data using the other existing part of the data\, such as jigsaw puzzle solving. Second\, contrastive learning methods\, which utilize similarities and dissimilarities\, or simply relations\, amongst data samples to form a classification problem\, such as SimCLR (simple contrastive learning of representations). Contrastive learning methods have proven effective as representation learners in applications of natural image classification. Nevertheless\, extending such algorithms to multiple application domains comes with challenges\, and we identify certain limitations in these approaches. Therefore\, in this talk\, we will focus on contrastive learning methods and how to apply them in several computer vision applications. We also discuss the challenges and limitations we identified and how to address them in project 29. \nThis talk will take place in person at SCIoI. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-marah-halawa-contrastive-learning-approaches-for-computer-vision-applications/
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230323T100000
DTEND;TZID=Europe/Berlin:20230323T120000
DTSTAMP:20260404T093726
CREATED:20230222T135409Z
LAST-MODIFIED:20240813T102507Z
UID:14755-1679565600-1679572800@www.scienceofintelligence.de
SUMMARY:Dr. Arlena Jung\, "Time Management & Resilience"
DESCRIPTION:Abstract: \nIn this talk\, Dr. Jung will focus on the three key principles of good time management: defining priorities\, managing expectations and developing routines that work. Following the lecture\, the participants have the opportunity to discuss their time management challenges in an individual coaching session. \nDefining Priorities: Dealing with high performance expectations in wide array of areas ranging from research to writing\, presenting\, networking and teaching is a key challenge for early-stage researches. In order to deal effectively with the in part conflicting expectations PhD students and early stage researchers need both the mindset and the self-confidence to define priorities. This means developing short and middle term goals that are both compatible with one’s own long-term goals and the expectations one’s “relevant other’s”. Without clear goals defining priorities and quality criteria become impossible tasks. That participants learn to understand the use of time management tools using the power of the 4 Zs to define SMART goals\, and integrating a “definition of done” into work packages\, milestones and at times even individual tasks. We also address the emotional challenge of dealing with in part conflicting goals\, roles and expectations. Together we discuss how ambiguity tolerance and strategic thinking can be used as key strengths in dealing with the multifaceted challenges but also opportunities of this career phase.  \nManaging Expectations: Complex interdependencies are an inherent part of the qualification phase of early stage research. Without the ability to manage expectations. PhD students have a very limited ability to actually turn their priorities into actionable plans. In this section of the lecture the participants are acquainted with key stakeholder-management tools such as the stakeholder-matrix and the systemic portrait. We\, however\, also discuss key communication skills needed to manage expectations effectively such as “7 shades of no”\, turning “yes” into a deliberate decision and creating solution  oriented dialogues. \nDeveloping routines that work: In order to use the limited resources available as effectively as possible early stage researchers need to learn to develop routines that work. This means figuring out what time management tools fit nicely both with their individual needs and their operational and conceptual tasks. In the last section of the lecture we present time management tools that help PhD students structure their working days and weeks ranging from the pomodoro and the ivy lee method to stimulus-response regulation practices and self-monitoring and self-evaluation methods.\n \n  \nThis talk will take place in person at SCIoI. \nPhoto by freestocks on Unsplash \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-dr-arlena-jung-time-management-resilience/
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230309T100000
DTEND;TZID=Europe/Berlin:20230309T110000
DTSTAMP:20260404T093726
CREATED:20230207T103252Z
LAST-MODIFIED:20240813T102512Z
UID:14155-1678356000-1678359600@www.scienceofintelligence.de
SUMMARY:Judith L. Bronstein (University of Arizona)\, "Why Cooperate with Another Species? The Puzzles of Mutualism"
DESCRIPTION:Abstract:\nThe classic view of nature is one of a deathly struggle for existence. Yet\, throughout nature\, organisms cooperate with each other. Mutualisms – mutually beneficial interactions between species – are more than fascinating natural history stories: they are central to the diversity and the diversification of life on Earth. Charles Darwin\, well aware of mutualisms\, mused that if species could be shown to act exclusively for the good of others\, “it would annihilate my theory”. The very young field of mutualism research attempts in part to address Darwin’s challenge. I will first briefly discuss the relationship between within-species cooperation and mutualism. I will then introduce two underlying concepts that are helping to guide our growing understanding: mutualism not only confers benefits but also exacts costs on the participants; and the immediate interests of mutualists commonly conflict. Then\, I will review some of my group’s recent findings that help address two of the most vexing puzzles mutualism poses: if mutualisms are beneficial\, why isn’t the world covered with them; and if mutualisms are costly\, then why doesn’t everyone cheat their partners? Our understanding of mutualism has exploded in recent years\, but this new focus has come at the cost of exploring connections between and mutualism and other forms of interaction – a situation I am working to mend during my Wiko fellowship. I will conclude by highlighting the interfaces that excite me the most.\n\nThis talk will take place in person at SCIoI. \n  \nPhoto by Joseph Sharp on Unsplash \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-judith-l-bronstein-university-of-arizona-why-cooperate-with-another-species-the-puzzles-of-mutualism/
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20230228
DTEND;VALUE=DATE:20230305
DTSTAMP:20260404T093726
CREATED:20250219T130041Z
LAST-MODIFIED:20250219T130041Z
UID:23532-1677542400-1677974399@www.scienceofintelligence.de
SUMMARY:Winter School "Ethics of Neuroscience and AI" 2022
DESCRIPTION:The 11th Winter School “Ethics of Neuroscience and AI” is taking place on Feb 28 – March 4\, 2022. It is organized by the BCCN Berlin/ICCN\, the Berlin School of Mind and Brain\, and the Excellence Cluster “Science of Intelligence”. The event is tailored for MSc and PhD students\, but covers a range of topics of potential interest to other researchers\, reflecting on the ethical and societal consequences of modern neuroscience.\nTheoretical foundations\, as well as practical and ethical aspects are addressed. Participants will benefit from a combination of lectures with group work and discussions\, where they will put the learned content into practice. \nScientific organizers: John-Dylan Haynes and Thomas Schmidt. \nKeynote lecture: Kent Kiehl (University of New Mexico) will discuss the ethical issues involved with neuroprediction (Live stream available) \nYou are welcome to join the keynote which will be live-streamed on the Bernstein Network’s Vimeo channel. \nFees: The Winter School is free of cost but registration is necessary. \nVenue: Due to the ongoing pandemic\, the Winter School will be held online.
URL:https://www.scienceofintelligence.de/event/winter-school-ethics-of-neuroscience-and-ai-2022/
CATEGORIES:External Event
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END:VEVENT
BEGIN:VEVENT
DTSTART;VALUE=DATE:20230227
DTEND;VALUE=DATE:20230304
DTSTAMP:20260404T093726
CREATED:20250219T125804Z
LAST-MODIFIED:20250219T130224Z
UID:23528-1677456000-1677887999@www.scienceofintelligence.de
SUMMARY:Winter School "Ethics of Neuroscience and AI" 2023
DESCRIPTION:The 12th Winter School “Ethics of Neuroscience and AI” is taking place on Feb 27 – March 3\, 2023. It is organized by the BCCN Berlin/ICCN\, the Berlin School of Mind and Brain\, and the Excellence Cluster “Science of Intelligence”. The event is tailored for MSc and PhD students\, but covers a range of topics of potential interest to other researchers\, reflecting on the ethical and societal consequences of modern neuroscience.\nTheoretical foundations\, as well as practical and ethical aspects are addressed. Participants will benefit from a combination of lectures with group work and discussions\, where they will put the learned content into practice. \nScientific organizers: John-Dylan Haynes and Thomas Schmidt. \nKeynote lecture: Christine Heim (Charité-Universitätsmedizin Berlin) \nFees: The Winter School is free of cost but registration is necessary. \nVenue: The Winter School takes place at the Bernstein Center for Computational Neuroscience Berlin.
URL:https://www.scienceofintelligence.de/event/23528/
CATEGORIES:External Event
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230223T100000
DTEND;TZID=Europe/Berlin:20230223T110000
DTSTAMP:20260404T093726
CREATED:20221114T105022Z
LAST-MODIFIED:20240813T101537Z
UID:13332-1677146400-1677150000@www.scienceofintelligence.de
SUMMARY:Ryan Burnell\, "A Cognitive Approach to the Evaluation of AI Systems"
DESCRIPTION:Abstract: \nThe capabilities of AI systems are improving rapidly\, and these systems are being deployed in increasingly complex and high-stakes contexts\, from self-driving cars to the detection of medical conditions. As the importance of AI grows\, so too does the need for robust evaluation. If we want to determine the extent to which systems are safe\, effective\, and unbiased\, it is vital that we understand the cognitive capabilities of those systems. In this endeavour\, psychological science has a lot to offer—scientists from cognitive\, developmental\, and comparative psychology have spent many decades developing theories and paradigms to understand the cognitive capabilities of adults\, children\, and animals. Drawing on these theories and paradigms\, we are working to build a framework for evaluating the cognitive capabilities of AI systems that we hope can be used to better track and regulate AI progress. I will present an initial version of the framework and discuss the open questions and challenges of applying cognitive science to AI evaluation. \nThis talk will take place in person at SCIoI. \nPhoto by Michael Dziedzic on Unsplash. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-ryan-burnell-a-cognitive-approach-to-the-evaluation-of-ai-systems/
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230216T100000
DTEND;TZID=Europe/Berlin:20230216T110000
DTSTAMP:20260404T093726
CREATED:20230207T104351Z
LAST-MODIFIED:20240813T101551Z
UID:14161-1676541600-1676545200@www.scienceofintelligence.de
SUMMARY:Julten Abdelhalim (Science of Intelligence)\, "Tips and Guidelines for your grant application in Germany"
DESCRIPTION:Abstract: \nThis talk will be targeting junior postdocs and phd at their final stages. It will be a short and brief introduction to the major options for grants (those aiming at the stars or smaller ones). Julten will offer some quick tips on the application process. She will also share her own experience in applying to the DFG Sachbeihilfe and ERC Starting Grant. The talk is not a detailed workshop in which we get into details about the proposal writing but rather a summary and a call out for how you should ideally plan your grant application journey. Those interested in detailed consultation are invited to book appointments later.\n\n\nThis talk will take place in person at SCIoI. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-julten-abdelhalim-our-career-as-a-scientist-make-a-plan-for-successful-grant-applications/
CATEGORIES:Thursday Morning Talk
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BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230209T160000
DTEND;TZID=Europe/Berlin:20230209T173000
DTSTAMP:20260404T093726
CREATED:20230119T092829Z
LAST-MODIFIED:20240813T101605Z
UID:14065-1675958400-1675963800@www.scienceofintelligence.de
SUMMARY:Oliver Brock (Science of Intelligence)\, "About the Interplay of Embodiment and Learning in Intelligent Systems"
DESCRIPTION:Abstract:\nBiological intelligent systems manifest their intelligence in physical interactions with other agents and with their environment. Such interactions require embodiment. Intelligence\, both artificial and biological\, also requires some kind of learning. But what is the relationship between the two? How should the two interact? Do they even have to? What could be a common ground on which this relationship can be explored\, negotiated\, and ultimately designed? In this presentation\, I will attempt to provide my personal answers to these questions. I will argue that one of the reasons (deep) machine learning has not yet been able to replicate its smashing successes in the context of robotics lies in the widespread disregard for the important capabilities provided by the body. Instead of considering embodiment\, machine learning seems to be resorting to massive use of physical simulations. This seems to be unnecessarily complicated without being convincingly effective.
URL:https://www.scienceofintelligence.de/event/pi-lecture-with-oliver-brock-2/
LOCATION:MAR 2.057
CATEGORIES:Thursday Morning Talk
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BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230209T100000
DTEND;TZID=Europe/Berlin:20230209T110000
DTSTAMP:20260404T093726
CREATED:20230116T111824Z
LAST-MODIFIED:20250603T130020Z
UID:14047-1675936800-1675940400@www.scienceofintelligence.de
SUMMARY:Andreagiovanni Reina (Université Libre De Bruxelles)\, “The Power of Inhibition for Collective Decision Making in Minimalistic Robot Swarms”
DESCRIPTION:Abstract:\nI investigate how large groups of simple robots can reach a consensus with decentralized minimalistic algorithms. Simple robots can be useful in nanorobotics and in scenarios with low-cost requirements. I show that through decentralized voting algorithms\, swarms of minimalistic robots can make best-of-n decisions. In my research\, I show that using a biologically-inspired voting model based on inhibitory signals\, the swarm can collectively perform better and be more resilient against a minority of misbehaving robots than in models without inhibition. Our best-of-n decision algorithm can also be used for collective environmental monitoring. I will show that investigating these models can be very interesting and yield surprising results. As Anderson said in 1972\, More is different. In our analysis\, we found that limiting the communication range or the speed of the robots can improve collective performance in a range of relevant conditions. We explain the mechanisms of some of these phenomena with a combination of mathematical models and large-scale robot experiments.\n\nThis talk will take place in person at SCIoI. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-giovanni-rena/
CATEGORIES:Thursday Morning Talk
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BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230126T160000
DTEND;TZID=Europe/Berlin:20230126T173000
DTSTAMP:20260404T093726
CREATED:20230117T132407Z
LAST-MODIFIED:20250603T130033Z
UID:14062-1674748800-1674754200@www.scienceofintelligence.de
SUMMARY:Lars Lewejohann (Science of Intelligence)\, “What’s on a Mouse’s Mind? Behavioral Measures To Understand Experiences and Needs of an Animal”
DESCRIPTION:Lars Lewejohann\, Freie Universität Berlin\, German Federal Institute for Risk Assessment (BfR)\, German Centre for the Protection of Laboratory Animals (Bf3R) \nMice\, like all other living creatures\, have adapted to specific living conditions in the course of evolution. From a human point of view\, the behavior of animals is therefore not always easy to understand. This applies not only to the question of whether mice are actually capable of behaving intelligently\, but also to the question of what is necessary for optimizing animal welfare of laboratory animals. In our work\, we are interested in both questions and follow an animal-centered approach and are giving mice their say. Of course mice cannot fill out questionnaires\, but we have developed a series of behavioral tests that allow to query the animals. In this lecture I will outline our approach with regard to improving housing and living conditions as well as the implications of using mice as a model species for the science of intelligence.
URL:https://www.scienceofintelligence.de/event/pi-lecture-with-lars-lewejohann-whats-on-a-mouses-mind-behavioral-measures-to-understand-experiences-and-needs-of-an-animal/
LOCATION:MAR 2.057
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BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230126T100000
DTEND;TZID=Europe/Berlin:20230126T110000
DTSTAMP:20260404T093726
CREATED:20221128T133841Z
LAST-MODIFIED:20240813T101630Z
UID:13403-1674727200-1674730800@www.scienceofintelligence.de
SUMMARY:Scott Robins (Bonn University)\, "What Machines Shouldn't Do"
DESCRIPTION:Abstract: \nFrom writing essays to evaluating potential hires\, machines are doing a lot these days. In all spheres of life\, it seems that machines are being delegated more and more decisions. Some of these machines are being delegated decisions that could have significant impact on human lives.Examples of such machines which have caused such impact are widespread and include machines evaluating loan applications\, machines evaluating criminals for sentencing\, autonomous weapon systems\, driverless cars\, digital assistants\, etc. Considering that machines cannot be held morally accountable for their actions (Bryson\, 2010; Johnson\, 2006; van Wynsberghe & Robbins\, 2018)\, the question that governments\, NGOs\, academics\, and the general public should be asking themselves is: how do we keep meaningful human control (MHC) over these machines? \n\nThe literature thus far details what features the machine or the context must have in order for MHC to be realized. Should humans be in the loop or on the loop? Should we force machines to be explainable? Lastly\, should we endow machines with moral reasoning capabilities? (Ekelhof\, 2019; Floridi et al.\, 2018; Robbins\, 2019a\, 2019b; Santoni de Sio & van den Hoven\, 2018; Wendall Wallach & Allen\, 2010; Wendell Wallach\, 2007). Rather than look to the machine itself or what part humans have to play in the context\, I argue here that we should shine the spotlight on the decisions that machines are being delegated. Meaningful human control\, then\, will be about controlling what decisions get made by machines. \n\nI argue that keeping meaningful human control over machines (especially AI which relies on opaque methods) means restricting machines to decisions that do not require a justifying explanation and can\, in principle\, be proven efficacious. Because contemporary methodologies in AI are opaque\, many machines cannot offer explanations for their outputs. In many cases\, decisions require justifying explanations\, and we should therefore not use machines for such cases. It won’t be surprising that machines should be efficacious if they are to be used – especially in contexts that will have impacts on human beings. Increasingly\, however\, machines are being delegated decisions for which we are unable\, in principle\, to evaluate their efficacy. This should not happen. \n\nThese arguments lead to the conclusion that machines should be restricted to descriptive outputs. It must always be a human being deciding how to employ evaluative terms as these terms not only refer to specific states of affairs but also say something about how the world ought to be. Machines which are able to make decisions based on opaque considerations should not be telling humans how the world ought to be. This is a breakdown of human control in the most severe way. Not only would we be losing control over specific decisions in specific contexts\, but we would be losing control over what descriptive content grounds evaluative classifications. \n\nIn this talk\, I will first discuss what it means to say that a machine is ‘doing’ something. I then briefly discuss different proposals for MHC and why they fall short. I then argue that machines should not be delegated evaluative decisions as they require justifying explanations which machines cannot give and cannot be evaluated for efficacy. While this talk is framed negatively\, it is my hope that this focuses research and development to design and build machines to help us realize our visions for how the world ought to be\, rather than machines that tell us hour the world ought to be. Only humans can decide that.\n \nThis talk will take place in person at SCIoI. \nPhoto by David Levêque on Unsplash \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-scott-robins-bonn-university-what-machines-shouldnt-do/
CATEGORIES:Thursday Morning Talk
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BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230119T160000
DTEND;TZID=Europe/Berlin:20230119T173000
DTSTAMP:20260404T093726
CREATED:20230102T111439Z
LAST-MODIFIED:20240813T101638Z
UID:13961-1674144000-1674149400@www.scienceofintelligence.de
SUMMARY:Ingmar Posner (University of Oxford)\, "Learning to Perceive and to Act - Disentangling Tales from (Structured) Latent Space"
DESCRIPTION:Abstract:\nUnsupervised learning is experiencing a renaissance. Driven by an abundance of unlabelled data and the advent of deep generative models\, machines are now able to synthesise complex images\, videos and sounds. In robotics\, one of the most promising features of these models – the ability to learn structured latent spaces – is gradually gaining traction. The ability of a deep generative model to disentangle semantic information into individual latent-space dimensions seems naturally suited to state-space estimation. Combining this information with generative world-models\, models which are able to predict the likely sequence of future states given an initial observation\, is widely recognised to be a promising research direction with applications in perception\, planning and control. Yet\, to date\, designing generative models capable of decomposing and synthesising scenes based on higher-level concepts such as objects remains elusive in all but simple cases. In this talk I will motivate and describe our recent work using deep generative models for unsupervised object-centric scene inference and generation. Furthermore\, I will make the case that exploiting correlations encoded in latent space\, and learnt through experience\, lead to a powerful and intuitive way to disentangle and manipulate task-relevant factors of variation. I will show that this not only casts a novel light on affordance learning\, but also that the same framework is capable of generating plans executable on complex real-world robot platforms. \nPhoto courtesy by Ingmar Posner. \nThis talk will take place in person at SCIoI. \n 
URL:https://www.scienceofintelligence.de/event/distinguished-speaker-series-ingmar-posner-university-of-oxford-learning-to-perceive-and-to-act-disentangling-tales-from-structured-latent-space/
CATEGORIES:Distinguished Speaker Series
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BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230119T100000
DTEND;TZID=Europe/Berlin:20230119T113000
DTSTAMP:20260404T093726
CREATED:20230116T101152Z
LAST-MODIFIED:20250603T130050Z
UID:14043-1674122400-1674127800@www.scienceofintelligence.de
SUMMARY:David Garzón Ramos (Université Libre De Bruxelles)\, “Automatic Design of Robot Swarms: Context and Experiments”
DESCRIPTION:Abstract:\n \nSwarm robotics is a promising approach to the coordination of large groups of robots. Traditionally\, the design of collective behaviors for robot swarms has been an iterative manual process: a human designer manually refines the control software of the individual robots until the desired collective behavior emerges.\n\nIn this talk\, I discuss automatic design as an alternative approach to manual design. In automatic methods\, the design process is cast into an optimization problem: given a task to be performed by the swarm\, an optimization process designs a collective behavior to perform the task and produces appropriate control software for the robots. I focus on experiments that highlight the various aspects of the automatic design of robot swarms: classes of collective behaviors\, control architectures\, and the optimization process. In particular\, I present a case study on the design of shepherding behaviors for groups of robots. The results presented in this talk are outcomes of the project DEMIURGE; an ERC funded project devoted to the study of the automatic design of robot swarms (PI Mauro Birattari).\nThis talk will take place in person at SCIoI. \nPhoto by Omar Flores on Unsplash. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-david-garzon-ramos-universite-libre-de-bruxelles-automatic-design-of-robot-swarms-context-and-experiments/
CATEGORIES:Thursday Morning Talk
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BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230112T100000
DTEND;TZID=Europe/Berlin:20230112T110000
DTSTAMP:20260404T093726
CREATED:20221128T133344Z
LAST-MODIFIED:20250603T130102Z
UID:13400-1673517600-1673521200@www.scienceofintelligence.de
SUMMARY:Dustin Lehmann\, Fritz Francisco\, Jorg Raisch\, Pawel Romanczuk (Science of Intelligence)\, “Dynamical Adaptation and Learning: Knowledge Transfer and Cooperative Learning in Groups of Heterogeneous Agents”
DESCRIPTION:Abstract: \nIn groups of agents learning how to solve a common task\, interaction and knowledge transfer between agents is important and can vary depending on network topology. Heterogeneity is one of the key principles that influences the type and quality of interaction between learning agents. Different learning strategies and behaviors can be a driving factor for the learning success at the group and individual level\, whereas differences in dynamics (or capabilities\, behaviors\, internal states\, etc.) can impede the direct transferability of knowledge and may require dynamic adaption of the agents.\nIn this talk\, we show how to infer behavioral heterogeneity in learning groups of fish and how this affects future learning capabilities. Prior knowledge of social partners affects the outcome of learning processes and timing of information uptake. We further investigate behavioral heterogeneity from the perspective of synthetic dynamic systems and how to transfer knowledge between dissimilar agents to enable cooperative learning of how to solve a common task. First results show how to exploit heterogeneity for learning in synthetic agents and which information gradient is beneficial when dealing with novel tasks in a social context.\n \nThis talk will take place in person at SCIoI. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-dustin-lehmann-fritz-francisco-jorg-raisch-pawel-romanczuk-dynamical-adaptation-and-learning-knowledge-transfer-and-cooperative-learning-in-groups-of-heterogeneous-agents/
CATEGORIES:Thursday Morning Talk
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BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20230105T160000
DTEND;TZID=Europe/Berlin:20230105T160000
DTSTAMP:20260404T093726
CREATED:20221215T134407Z
LAST-MODIFIED:20250603T130112Z
UID:13676-1672934400-1672934400@www.scienceofintelligence.de
SUMMARY:Peter Neri (Laboratoire Des Systèmes Perceptifs\, CNRS\, Paris)\, “The Unreasonable Recalcitrance of Human Vision to Theoretical Domestication”
DESCRIPTION:Abstract: \nWe can view cortex from two fundamentally different perspectives: a powerful device for performing optimal inference\, or an assembly of biological components not built for achieving statistical optimality. The former approach is attractive thanks to its elegance and potentially wide applicability\, however the basic facts of human pattern vision do not support it. Instead\, they indicate that the idiosyncratic behaviour produced by visual cortex is largely dictated by its hardware components. The output of these components can be steered towards optimality by our cognitive apparatus\, but only to a marginal extent. We conclude that current theories of visually-guided behaviour are at best inadequate\, and we turn to neural networks in an attempt to establish whether the idiosyncratic character of human vision may be learnt from a larger repertoire of functional constraints\, such as the statistics of the natural environment. We challenge deep convolutional networks with the same stimuli/tasks used with human observers and apply equivalent characterization of the stimulus–response coupling. For shallow depth of behavioural characterization\, some variants of network-architecture/training-protocol produce human-like trends; however\, more articulate empirical descriptors expose glaring discrepancies. Our results urge caution in assessing whether neural networks do or do not capture human behavior: ultimately\, our ability to assess ‘’success’’ in this area can only be as good as afforded by the depth of behavioral characterization against which the network is evaluated. More generally\, our results provide a compelling demonstration of how far we still are from securing an adequate computational account of even the most basic operations carried out by human vision. \nPhoto by Mathew Schwartz on Unsplash \nThis talk will take place in person at SCIoI. \n 
URL:https://www.scienceofintelligence.de/event/distinguished-speaker-series-peter-neri-laboratoire-des-systemes-perceptifs-cnrs-paris-the-unreasonable-recalcitrance-of-human-vision-to-theoretical-domestication/
CATEGORIES:Distinguished Speaker Series
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20221215T160000
DTEND;TZID=Europe/Berlin:20221215T173000
DTSTAMP:20260404T093726
CREATED:20211222T113627Z
LAST-MODIFIED:20250603T130124Z
UID:11482-1671120000-1671125400@www.scienceofintelligence.de
SUMMARY:John Dylan Haynes (Science of Intelligence)\, “Intelligence in Humans Versus Machines”
DESCRIPTION:Many claims have been made that machine intelligence could make humans superfluous in the near future. Today this claim is largely seen as overstated\, but it is still important to assess the relative strengths of human versus machine cognition. \n\n  \nThis talk will take place in person at SCIoI.
URL:https://www.scienceofintelligence.de/event/pi-lecture-with-john-dylan-haynes/
CATEGORIES:PI Lecture
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20221215T100000
DTEND;TZID=Europe/Berlin:20221215T110000
DTSTAMP:20260404T093726
CREATED:20220914T121043Z
LAST-MODIFIED:20250603T130137Z
UID:13049-1671098400-1671102000@www.scienceofintelligence.de
SUMMARY:Robert Lange and Luis Gomez (Science of Intelligence)\, “Quantifying and Modelling Collective Behavior Across Ecological Contexts”
DESCRIPTION:Abstract: \nA central challenge in understanding the concept of swarm intelligence is the relation between the behavior of a swarm of agents and its ecological niche. In order to interpret such collective concept\, we have been using analytical and synthetic approaches to get more insights using mainly one particular biological system of Sulphur mollies as study system. We have combined analytical behavioral characterizations of schools of these fish with synthetic state-of-the-art machine learning methods to understand the  functionality of the behavior in real life. In this talk\, we will show our main findings related to the collective behavior. We will show i) that the highly synchronized diving behavior of the school is close to criticality\, ii) how this can be functionally related to effective communication about predator attacks\, and iii) how to study the heterogeneity in collectives by inferring the parameters of models using machine learning algorithms. \nThis talk will take place in person at SCIoI.
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-p12/
CATEGORIES:Thursday Morning Talk
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BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20221208T100000
DTEND;TZID=Europe/Berlin:20221208T110000
DTSTAMP:20260404T093726
CREATED:20221128T100636Z
LAST-MODIFIED:20250603T130147Z
UID:13385-1670493600-1670497200@www.scienceofintelligence.de
SUMMARY:Erik Rodner “Please Label Me: Challenges and Efficient Strategies for Data Annotation and Selection”
DESCRIPTION:Abstract: \nLack of data and annotations has been the showstopper for machine learning projects when I started my PhD and 15 years later it still is. In my talk\, I will give a brief overview of recent models we developed for weakly- and semi supervised as well as for active learning.\nIn addition\, we will analyze the relevance of these algorithms from an industrial perspective\, which often contradicts with the usual story line in traditional computer vision publications. \nThis talk will take place in person at SCIoI. \n  \nPhoto by vackground.com on Unsplash
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-with-erik-rodner-please-label-me-challenges-and-efficient-strategies-for-data-annotation-and-selection/
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20221201T160000
DTEND;TZID=Europe/Berlin:20221201T173000
DTSTAMP:20260404T093726
CREATED:20211222T113440Z
LAST-MODIFIED:20240813T101910Z
UID:11480-1669910400-1669915800@www.scienceofintelligence.de
SUMMARY:Klaus Obermayer (Science of Intelligence)\, "Computational Models of Electric Field Effects and Optimal Control of Neurons and Neural Populations"
DESCRIPTION:Abstract: \nThe brain is a complex dynamical system with processes operating on different spatial scales. At the macroscopic end one observes global dynamical phenomena\, which are called „brain states“ and which are often acompanied by oscillations in different frequency bands or by specific functional connectivity patterns between populations of neuron. A common hypothesis states\, that the global dynamics establishes a task-dependent operating point\, which is required by individual neurons and local networks to perform information processing tasks. Perturbation experiments are performed\, on the one hand\, to perform causal analyses into the consequences of this and related hypotheses and\, on the other hand\, to restore a brain’s operating point in case of dysfunction. \nIn my talk I will summarize some of our recent modelling work to better understand the interaction between the neural dynamics and external control inputs\, taking non-invasive electrical stimulation of neural tissue as an example. I will first present some results on the biophysics of (microscopic) neuron-field interactions and our modelling attempts to propagate these effects to the macroscopic level. In the second part of my presentation I will show\, how techniques from Optimal Control Theory can be used to probe controllability aspects of neural systems and to help design efficient ways of steering the neural dynamics. \n  \nThis talk will take place in person at SCIoI. \n 
URL:https://www.scienceofintelligence.de/event/pi-lecture-with-klaus-obermayer/
CATEGORIES:PI Lecture
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20221201T100000
DTEND;TZID=Europe/Berlin:20221201T110000
DTSTAMP:20260404T093726
CREATED:20220914T121438Z
LAST-MODIFIED:20240813T101934Z
UID:13054-1669888800-1669892400@www.scienceofintelligence.de
SUMMARY:David Bierbach (Science of Intelligence)\, "Anticipation in social interactions among live and artificial agents"
DESCRIPTION:Abstract: \nThe aim of SCIoI’s P10 is to investigate how anticipation and prediction shapes social interactions among live and artificial agents using for example the Robofish system. We will outline our research showing the sophisticated anticipation abilities of live fish\, as well as how we integrated prediction and anticipation into Robofish’s social interaction behaviors. We will furthermore show how experiments with robotic animals can help to promote animal welfare and what is necessary to build biomimetic robots that will be accepted by live animals as conspecifics (see also these articles: https://www.frontiersin.org/articles/10.3389/fbioe.2020.00441/full\,  https://www.annualreviews.org/doi/10.1146/annurev-control-061920-103228\, https://link.springer.com/chapter/10.1007/978-3-030-64313-3_26 ). Finally we will dive into our public outreach activities that include the Robofish exhibition in the Humboldt Labor at Stadtschloss Berlin with more than 100\,000 visitors since 2021. \nThis talk will take place in person at SCIoI. \n 
URL:https://www.scienceofintelligence.de/event/thursday-morning-talk-p10-jens-krause-verena-hafner-2/
CATEGORIES:Thursday Morning Talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Berlin:20221124T160000
DTEND;TZID=Europe/Berlin:20221124T173000
DTSTAMP:20260404T093726
CREATED:20220926T103901Z
LAST-MODIFIED:20240813T101918Z
UID:13096-1669305600-1669311000@www.scienceofintelligence.de
SUMMARY:Jan De Houwer (Ghent University)\, "Learning in Individual Organisms\, Genes\, Machines\, and Groups: A New Way of Defining and Relating Learning in Different Systems"
DESCRIPTION:Abstract:\nLearning is a central concept in many scientific disciplines. Communication about research on learning is\, however\, hampered by the fact that different researchers define learning in different ways. In this talk\, we introduce the extended functional definition of learning that can be used across scientific disciplines. We provide examples of how the definition can be applied to individual organisms\, genes\, machines\, and groups. The extended functional definition (a) reveals a heuristic framework for research that can be applied across scientific disciplines\, (b) allows researchers to engage in intersystem analyses that relate the behavior and learning of different systems\, and (c) clarifies how learning differs from other phenomena such as (changes in) behavior\, damaging systems\, and programming systems. \nPhoto by DeepMind on Unsplash \nThis talk will take place in person at SCIoI. \n 
URL:https://www.scienceofintelligence.de/event/distinguished-speaker-series-with-jan-de-houwer-learning-in-individual-organisms-genes-machines-and-groups-a-new-way-of-defining-and-relating-learning-in-different-systems/
LOCATION:MAR 2.057
CATEGORIES:Distinguished Speaker Series
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END:VEVENT
END:VCALENDAR