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 ===== Working With Us ===== ===== Working With Us =====
 +  * We are hiring [[jobs|two doctoral students]] in machine learning for computer vision or robotics.
   * Check our thesis topics for [[theses/​start|Bachelor and Master students]].   * Check our thesis topics for [[theses/​start|Bachelor and Master students]].
-  ​* [[https://​ellis.eu/​|ELLIS]] PhD Program: [[https://​ellis.eu/​news/​ellis-phd-program-call-for-applications-deadline-november-15-2021|Call for Applications]]+ <​html><​!-- 
 + * [[https://​ellis.eu/​|ELLIS]] PhD Program: [[https://​ellis.eu/​news/​ellis-phd-program-call-for-applications-deadline-november-15-2021|Call for Applications]] 
 +--></​html>​
  
 <​html><​!-- <​html><​!--
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 ===== News ===== ===== News =====
  
-<​HTML><​table><​tr valign="​top"><​td>​2021-11-24</​td><​td>​Justus Piater is a panelist at a public discussion on <a href="​https://​www.linkedin.com/​posts/​elsa-innsbruck_letzte-woche-fand-zum-elsa-day-am-24112021-activity-6871397038093869057-16-7">​Privacy+<​HTML><​table><tr valign="​top"><​td>​2022-06-02</​td><​td>​Erwan Renaudo contributes a talk <​i>​Deep Learning for Fast Segmentation of E-waste Devices’  
 +    Inner Parts in a Recycling Scenario</​i>​ at <a href="​https://​icprai2022.sciencesconf.org/">​ICPRAI 2022</​a>,​ Paris/​online. <span class="​actions"><​a href="​javascript:​void(0)"​ onclick="​showHide('​newsitem0',​ '​Abstract'​)">​[Abstract]</​a></​span><​blockquote id="​newsitem0Abstract"​ style="​display:​none">​Recycling obsolete electronic devices (E-waste) is a 
 +    dangerous task for human workers. Automated E-waste recycling  
 +    is an area of great interest but challenging for current robotic  
 +    applications. We focus on the problem of segmenting inner parts  
 +    of E-waste devices into manipulable elements. First, we extend  
 +    a dataset of hard-drive disk (HDD) components with labelled  
 +    occluded and non-occluded points of view of the parts, in order  
 +    to increase the diversity and the quality of the learning data  
 +    with different angles. We then perform an extensive evaluation  
 +    with three different state-of-the-art models, namely CenterMask,​ 
 +    BlendMask and SOLOv2 (including variants) and two types of  
 +    metrics: the average precision as well as the frame rate. Our  
 +    results show that instance segmentation using state-of-the-art  
 +    deep learning methods can precisely detect complex shapes along  
 +    with their boundaries, as well as being suited for fast tracking of 
 +    parts in a robotic recycling system. (Rojas et  al. 2022) 
 +    </​blockquote></​td></​tr><​tr valign="​top"><​td>​2022-05-17</​td><​td>​Erwan Renaudo gives an invited talk <i>A Brief tour of autonomous robots'​ &​quot;​Cognition&​quot;</​i>​ at <a href="​https://​www.philosophie.uni-konstanz.de/​ag-mueller/​aktuelles/​meldungsdetails-ag-mueller/​2022/​5/​17/​event/​46426-Creating-Agency-and-Cogn/​tx_cal_phpicalendar/">​Creating Agency and Cognition in Automated Systems: What can we learn from the Octopus? International Hybrid Workshop</​a>,​ Innsbruck. <span class="​actions"><​a href="​javascript:​void(0)"​ onclick="​showHide('​newsitem1',​ '​Abstract'​)">​[Abstract]</​a></​span><​blockquote id="​newsitem1Abstract"​ style="​display:​none">​In the design of &​quot;​Cognitive Robots&​quot;​ software architectures,​  
 +    researchers had to face many organizational problems due to  
 +    the particular nature of robots. Not only should they manage  
 +    to achieve complex tasks with long-terms goals, but they must  
 +    also be reactive to their surroundings to preserve their environment. 
 +    We will go over several layered control paradigms developed over 
 +    the history of robotics and see how these can relate to the  
 +    knowledge about the Octopus'​ brain organization,​ and discuss  
 +    how the Octopus itself can inspire cognitive robotic research. 
 +    </​blockquote></​td></​tr><​tr valign="​top"><​td>​2022-05-11</​td><​td>​Justus Piater gives an invited talk <​i>​Robots That Learn Like Humans?</​i>​ at <a href="​https://​pintofscience.at/​events/​innsbruck">​Pint of 
 +    Science</​a>,​ Innsbruck. <span class="​actions"><​a href="​javascript:​void(0)"​ onclick="​showHide('​newsitem2',​ '​Abstract'​)">​[Abstract]</​a></​span><​blockquote id="​newsitem2Abstract"​ style="​display:​none">​Wouldn'​t it be great to have a helper robot that we can 
 +    task with our annoying chores? How would we teach the robot to 
 +    perform these tasks? Can we build such robots by equipping them 
 +    with artificial intelligence?​ We will discuss how human and 
 +    machine learning differ and how this impacts what skills, 
 +    including for communication,​ our helper robot will be able to 
 +    learn.</​blockquote></​td></​tr><​tr valign="​top"><​td>​2022-02-19</​td><​td>​Justus Piater gives an invited talk <​i>​Learning as a Creative Process in Humans and 
 +    Machines</​i>​ at <a href="​https://​www.philosophie.uni-konstanz.de/​ag-mueller/​online-workshop-on-agency-life-and-creativity/">​Workshop 
 +    on “Agency, Life, and Creativity”</​a>,​ online. <span class="​actions"><​a href="​javascript:​void(0)"​ onclick="​showHide('​newsitem3',​ '​Abstract'​)">​[Abstract]</​a></​span><​blockquote id="​newsitem3Abstract"​ style="​display:​none">​Humans constantly engage in creative activity such as 
 +    finding explanations,​ improving technology, or solving novel 
 +    problems in everyday life. Even imitating other humans, e.g. while 
 +    learning a new skill, is creative in that the imitator has to 
 +    infer the conceptual structure underlying the observed 
 +    manifestation and to regenerate the latter from the former. In 
 +    contrast, current AI-enabled agents are unable to generate and 
 +    draw upon such conceptual structures. Their learning is mostly 
 +    driven by statistics, and any ability to produce novelty is 
 +    largely limited to trial and error. I will try to characterize 
 +    this fundamental difference between learning in human and 
 +    artificial agents, and will discuss possible technological 
 +    approaches that might help close this gap.</​blockquote></​td></​tr><tr valign="​top"><​td>​2021-11-24</​td><​td>​Justus Piater is a panelist at a public discussion on <a href="​https://​www.linkedin.com/​posts/​elsa-innsbruck_letzte-woche-fand-zum-elsa-day-am-24112021-activity-6871397038093869057-16-7">​Privacy
     in the Digital Age</​a>,​ online. (Organized by ELSA Innsbruck)</​td></​tr><​tr valign="​top"><​td>​2021-10-22</​td><​td>​Justus Piater gives an invited talk <​i>​Robotik und KI in der Medizin – nur     in the Digital Age</​a>,​ online. (Organized by ELSA Innsbruck)</​td></​tr><​tr valign="​top"><​td>​2021-10-22</​td><​td>​Justus Piater gives an invited talk <​i>​Robotik und KI in der Medizin – nur
     Bedarfserweckung?</​i>​ at <a href="​https://​medical-update-hall.com/​veranstaltungen/">​Medical     Bedarfserweckung?</​i>​ at <a href="​https://​medical-update-hall.com/​veranstaltungen/">​Medical
-    Update Hall 2021 – Fit für das neue Jahrzehnt</​a>,​ UMIT, Hall in Tirol.</​td></​tr><​tr valign="​top"><​td>​2021-08-26</​td><​td>​Justus Piater contributes a talk <​i>​Digital Science at the University of Innsbruck</​i>​ at Aurora Research Conference Digital Society &amp; Global Citizenship,​ Vrije Universiteit Amsterdam. <span class="​actions"><​a href="​javascript:​void(0)"​ onclick="​showHide('​newsitem2', '​Abstract'​)">​[Abstract]</​a></​span><​blockquote id="newsitem2Abstract" style="​display:​none">​Growing data processing capacities and progress in+    Update Hall 2021 – Fit für das neue Jahrzehnt</​a>,​ UMIT, Hall in Tirol.</​td></​tr><​tr valign="​top"><​td>​2021-08-26</​td><​td>​Justus Piater contributes a talk <​i>​Digital Science at the University of Innsbruck</​i>​ at Aurora Research Conference Digital Society &amp; Global Citizenship,​ Vrije Universiteit Amsterdam. <span class="​actions"><​a href="​javascript:​void(0)"​ onclick="​showHide('​newsitem6', '​Abstract'​)">​[Abstract]</​a></​span><​blockquote id="newsitem6Abstract" style="​display:​none">​Growing data processing capacities and progress in
     analytical methods and artificial intelligence are motivating     analytical methods and artificial intelligence are motivating
     entire branches of science to raise new questions and to develop     entire branches of science to raise new questions and to develop
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     and Open Lab on Field Robotics - Interdisciplinary aspects of     and Open Lab on Field Robotics - Interdisciplinary aspects of
     robotics and its applications in outdoor scenarios</​a>,​ NOI Techpark, Bolzano, Italy.</​td></​tr><​tr valign="​top"><​td>​2021-05-26</​td><​td>​Justus Piater contributes a talk <​i>​Intelligente und interaktive Systeme</​i>​ at <a href="​http://​www.gmar.at/​aktuell/">​GMAR Robotics Science     robotics and its applications in outdoor scenarios</​a>,​ NOI Techpark, Bolzano, Italy.</​td></​tr><​tr valign="​top"><​td>​2021-05-26</​td><​td>​Justus Piater contributes a talk <​i>​Intelligente und interaktive Systeme</​i>​ at <a href="​http://​www.gmar.at/​aktuell/">​GMAR Robotics Science
-    Talks</​a>,​ online.</​td></​tr><​tr valign="​top"><​td>​2021-03-24</​td><​td>​Justus Piater gives an invited lecture <​i>​Machine Learning, Perception, And Abstract Concepts</​i>​ at Invited lecture at Ontario Tech U, Canada, online. <span class="​actions"><​a href="​javascript:​void(0)"​ onclick="​showHide('​newsitem6',​ '​Abstract'​)">​[Abstract]</​a></​span><​blockquote id="​newsitem6Abstract"​ style="​display:​none">​With every spectacular achievement of a machine learning +    Talks</​a>,​ online.</​td></​tr></​table></​HTML>​
-    system, the long-elusive AI breakthrough is popularly proclaimed +
-    to be just around the corner. ​ Most recent successes have been due +
-    in large part to massive data and computation,​ in particular using +
-    deep artificial neural networks. ​ But can artificial cognition +
-    really be achieved just by further scaling up existing +
-    machine-learning techniques? ​ I discuss examples of simple, +
-    perceptual problems that are easily solved by humans but very +
-    difficult for today'​s machine learning methods. ​ These problems +
-    reflect how humans conceptualize their world. ​ Their mastery is +
-    thus likely to be an essential prerequisite for autonomous robots +
-    to attain higher levels of cognitive abilities. ​ To get there, a +
-    few core issues can be identified that should drive research in +
-    cognitive robotics.</​blockquote></​td></​tr><​tr valign="​top"><​td>​2021-01-28</​td><​td>​Matteo Saveriano gives an invited talk <​i>​Making robots to learn from human observation?</​i>​ at <a href="​https://​www.bmeia.gv.at/​en/​austrian-embassy-ottawa/​news/​events/​detail/​article/​showcasing-young-austrian-scholars-and-scientists-an-original-seven-part-virtual-lectures-ser/">​Showcasing Young Austrian Scholars and Scientists, Austrian cultural forum, Ottawa</​a>,​ online.</​td></​tr><​tr valign="​top"><​td>​2021-01-14</​td><​td>​Matteo Saveriano gives an invited talk <​i>​Hierarchical action decomposition and motion learning for the execution of manipulation tasks</​i>​ at <a href="​http://​www.gmar.at/​aktuell/">​Hello Tyrol calling! Robotics Talk online, GMAR, Innsbruck</​a>,​ online.</​td></​tr><​tr valign="​top"><​td>​2020-11-19</​td><​td>​Justus Piater gives an invited talk <​i>​Machine Learning in Robotics</​i>​ at <a href="​https://​baiome.org/">​bAIome PI Talk, Center for +
-    Biomedical AI, University Medical Center Hamburg-Eppendorf</​a>,​ online. <span class="​actions"><​a href="​javascript:​void(0)"​ onclick="​showHide('​newsitem10',​ '​Abstract'​)">​[Abstract]</​a></​span><​blockquote id="​newsitem10Abstract"​ style="​display:​none">​Machine Learning increasingly equips robots with +
-    learning capabilities and flexibility. ​ This will enable them to +
-    act purposefully in unstructured environments and to react to +
-    unforeseen events. ​ People can teach them intuitively to perform +
-    tasks instead of having to program them in painstaking ways. +
-    Robots can learn from experience and can improve their behavior +
-    over time.  In this talk I will give an overview of methods, +
-    opportunities,​ and challenges of machine learning in +
-    robotics.</​blockquote>​</​td></​tr></​table></​HTML>​+
  
 [[news|Older News]] [[news|Older News]]
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