Thursday Morning Talk

A cornerstone of SCIoI are the three example behaviors that provide the motivation, as well as the demonstration platforms to showcase the amazing research happening within the cluster. In order to get the ball rolling towards interesting example behaviors, we have recently started regular "integration hackathon" meetings. They bring together people from different projects, who

Abstract:Theories of learning from multimodal sources (e.g., combinations of text and pictures, aka multimedia) posit that in order to effectively learn from multimedia, students need to select information from text and pictures, organize the information in memory, and most importantly, integrate the information into one mental model. In the first part of my presentation, I

Abstract: Collective dynamics play a crucial role in everyday decision-making. Whether social influence promotes the spread of accurate information, and ultimately results in collective intelligence, or leads to false information cascades and maladaptive social contagion depends on the cognitive mechanisms underlying social interactions. In our talk, we will argue that cognitive modeling, in tandem with

Abstract: I will present our current research involving the Robofish. I will put a special focus on our latest research paper that found live fish to be able to anticipate predictably behaving Robofish both in regard to final movement locations as well as movement dynamics. This talk will take place in person at SCIoI  

From 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

More details to follow. Photo by DeepMind on Unsplash This talk will take place in person at SCIoI.  

Abstract: As many of us know by now, Deep Learning has enabled tackling very challenging problems and applications that were previously almost impossible to solve with machine learning. However, for most of the tasks we want to solve with Deep Learning, we need large, if not huge, amounts of data and computing power. This is

Abstract: The BUA-funded experimental knowledge transfer project CollActive Materials, a collaboration between the Clusters of Excellence Science of Intelligence and Matters of Activity, encourages speculation on what the future has in store. Which intelligent materials will pave our tomorrows? How can substances and materials change our world in an intelligent way? What will the world

Abstract: The contents of this presentation will be twofold. In the first part the Centre for Robotics of the Queensland University of Technology (QUT) and its research directions and facilities will be introduced. The research on semantics for the benefit of UAVs, specifically quadcopters, will be highlighted. The second part will contain the personal experiences

Abstract: The 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

Abstract: Lack 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. In addition, we will

Abstract: A 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