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--- start [2019/06/14 06:25]
IIS Webadmin
+++ start [2026/08/23 06:40] (current)
Justus Piater [Working With Us]
@@ Line 7: / Line 7: @@
 We seek to answer the question: //How can we enable robots to acquire the knowledge and understanding they require to interact sensibly with unstructured environments? //
-Our research addresses complete perception-action loops, from computer vision to grasping and manipulation, using reactive algorithms and/or cognitive models.  Much of our work uses machine learning to enable robots to synthesize and improve complex and robust sensorimotor behavior with experience. Related areas of interest include human-robot interaction, image and video analysis, and visual neuroscience.
+Our research addresses complete perception-action loops, from computer vision to grasping and manipulation, using reactive algorithms and/or cognitive models.  Much of our work uses machine learning to enable robots to synthesize and improve complex and robust sensorimotor behavior with experience.
 ===== Working With Us =====
-  * We are hiring [[jobs|two Ph.D. students]].
   * Check our thesis topics for [[theses/start|Bachelor and Master students]].
+  * [[:jobs:#notice_for_non-eueea_prospective_master_students|Notice]] for non-[[https://en.wikipedia.org/wiki/EU|EU]]/[[https://en.wikipedia.org/wiki/European_Economic_Area|EEA]] prospective Master students
+  * We do not currently have any open PhD positions.
-{{::iis-2017.jpg?570|Group Picture}}\\
+<html>
-Group picture taken at our retreat in Obergurgl
+<div style="clear:both"><br></div>
+</html>
+{{ ::iis_retreat_2024.jpg?direct&900 |}}\\
+<html>
+<div style="text-align: center;">
+  <p>Group picture taken at our 2024 retreat at Meissner Haus.</p>
+</div>
+</html>
 ===== News =====
-<HTML><table><tr valign="top"><td>2019-06-13</td><td>Simon Haller gives an invited talk <i>Coding Literacy –
+<HTML><table><tr valign="top"><td>2026-09-27</td><td>Justus Piater co-organizes the <a href="https://worldmodelworkshop.github.io/">RoBoWoMo:
-    Konzepte und Anwendungen in der Schule und im Alltag</i>, <a href="https://www.uibk.ac.at/events/2019/06/13/kuenstliche-intelligenz-und-robotik-als-theologisch-ethische-...">Künstliche
+    Bridging the Gap between Neural and Symbolic World Models for
-    Intelligenz und Robotik als theologisch-ethische
+    Robot Planning, Reasoning, and Action</a>.</td></tr><tr valign="top"><td>2026-05-20</td><td>Simon Haller-Seeber appears in the media: <a href="https://www.digital.tirol/page.cfm?vpath=news&amp;rnpageid=42902">
-    Herausforderung</a>, Universität Innsbruck.</td></tr><tr valign="top"><td>2019-06-13</td><td>Justus Piater gives an invited talk <i>Künstliche Intelligenz in einer menschlichen
+        Digitale Bildung aktiv erleben: Der RoboCupJunior Austrian Open 2026 in Tirol</a>. (Interview im Rahmen des RoboCup Junior Austrian Open)</td></tr><tr valign="top"><td>2026-05-07</td><td>Justus Piater is a panelist at a public discussion on <a href="https://www.uibk.ac.at/de/medien-kommunikation/kommunikation/intern/">Invited
-    Gesellschaft</i>, <a href="https://www.uibk.ac.at/events/2019/06/13/kuenstliche-intelligenz-und-robotik-als-theologisch-ethische-...">Künstliche
+    expert interview on “Human-robotics relations: What does the
-    Intelligenz und Robotik als theologisch-ethische
+    future hold?”</a>, Innsbruck. (Public event organized by the Department of Media, Society and Communication, Universität Innsbruck)</td></tr><tr valign="top"><td>2026-04-15</td><td>Justus Piater gives an invited talk <i>Some Latest Results in Robot Learning of Structure by
-    Herausforderung</a>, Universität Innsbruck.</td></tr><tr valign="top"><td>2019-05-24</td><td>Philipp Zech and Erwan Renaudo co-organize the <a href="https://r1d1.github.io/iwcmar/">2nd International
+    Interaction</i> at <a href="https://airov.at/2026/workshop/TactileRobotics.html">Austrian
-    Workshop on Computational Models of Affordance in Robotics
+    Robotics Workshop</a>, Leoben. (Annual workshop of the GMAR; at AIRoV 2026)</td></tr><tr valign="top"><td>2026-04-08</td><td>Simon Haller-Seeber and Justus Piater co-organize the <a href="https://robocupjunior.at/">RCJ2026 - Robocup Junior Austrian Open: 08.-10.4.2026</a>.</td></tr><tr valign="top"><td>2026-04-08</td><td>Justus Piater gives an invited talk <i>Generative KI: Funktionsweise, Möglichkeiten und
-    </a>.</td></tr><tr valign="top"><td>2019-05-02</td><td>Justus Piater gives an invited talk <i>Digitalization: Promises and Challenges</i>, <a href="https://www.andrassyuni.eu/nachrichten/innovation-trifft-geschichte-oder-wie-kommunizieren-wir-digital-und-analog.html">Möglichkeiten
+    Grenzen</i> at SchulleiterInnen-Tagung „IT-Sicherheit und KI-Einsatz in
-    und Herausforderungen der Digitalisierung</a>, Universität Innsbruck.</td></tr><tr valign="top"><td>2019-04-26</td><td>Justus Piater appears in the media: TV interview on educational and societal aspects of robot
+    der Schule“, Pädagogische Hochschule Tirol. (Veranstaltung für Schulleitungen der Bildungsdirektion für Tirol) <span class="actions"><a href="javascript:void(0)" onclick="showHide('newsitem6', 'Abstract')">[Abstract]</a></span><blockquote id="newsitem6Abstract" style="display:none">Generative KI-Systeme wie ChatGPT und Midjourney haben
-    technology by ORF 2 Tirol Heute (in German).</td></tr><tr valign="top"><td>2019-03-28</td><td>Simon Haller teaches a tutorial <i>Coding und Robotik - Makerspaces mit Einplatinencomputern.</i>, <a href="https://www.efuture-day.tsn.at/content/programmablauf-2019">eFuture-Day</a>, Grillhof Vill.</td></tr><tr valign="top"><td>2019-03-26</td><td>Justus Piater co-organizes the <a href="https://www.standort-tirol.at/page.cfm?vpath=veranstaltungen&amp;genericpageid=25174">GMAR Robotics Talk: Robotik in Fertigung, Montage und
+    die Welt im Sturm erobert. Wie können wir sie produktiv nutzen?
-    Forschung</a>.</td></tr><tr valign="top"><td>2019-02-20</td><td>Justus Piater gives an invited talk <i>Künstliche Intelligenz in der Robotik</i>, <a href="https://www.eventbrite.de/e/smart-city-finale-2019-tickets-56007354505">Smart City Finale 2019</a>, HTL Dornbirn.</td></tr><tr valign="top"><td>2019-01-10</td><td>Justus Piater gives an invited talk <i>High-Level, Skill-Based Robot Programming Using Autonomous
+    Wie können wir mit den Herausforderungen umgehen, die durch sie
-    Playing and Autonomous Testing</i>, <a href="https://www.standort-tirol.at/page.cfm?vpath=veranstaltungen&amp;genericpageid=23118">Taste Digitalization – CAMPUS:digi:TOUR (4)</a>, ICT, Universität Innsbruck.</td></tr><tr valign="top"><td>2018-10-05</td><td>Justus Piater gives an invited talk <i>Perception of Abstract Concepts</i>, <a href="http://iros2018-uvsp.org/">Unconventional Sensing and
+    entstehen? Ich werde diese Fragen von der technischen Seite her
-    Processing for Robotic Visual Perception</a>, Madrid, Spain.</td></tr></table></HTML>
+    angehen und einen Eindruck davon vermitteln, wie diese Systeme
+    funktionieren. Daraus ergeben sich ein realistisches Verständnis
+    für ihre Möglichkeiten und Grenzen sowie einige grundlegende
+    Empfehlungen für den Umgang mit ihnen im Schulbetrieb.</blockquote></td></tr><tr valign="top"><td>2026-03-31</td><td>Samuele Tosatto gives an invited keynote <i>Accelerating Reinforcement Learning with Off-Policy Data: Promises, Pitfalls, and Future Directions</i> at <a href="https://rl4aa.github.io/RL4AA26/">Reinforcement Learning For Autonomous Accelerators 2026</a>, Liverpool. <span class="actions"><a href="javascript:void(0)" onclick="showHide('newsitem7', 'Abstract')">[Abstract]</a></span><blockquote id="newsitem7Abstract" style="display:none">Reinforcement learning is a promising technique for solving complex control problems in real-world physical systems, such as robotics, plasma stabilization, and particle accelerators. However, RL is often data-hungry, and its classic on-policy formulation is often inefficient, as it disallows data reuse, and unsafe, as it requires the agent to interact with the environment from scratch.
+Off-policy reinforcement learning offers a more appealing paradigm by enabling the reuse of historical data and the utilization of safe, external behavior sources (such as human operator logs). However, this flexibility comes at a cost: off-policy learning introduces significant theoretical instabilities. In this talk, we will analyze some fundamental difficulties in off-policy reinforcement learning, both in value and policy learning, explore the algorithmic landscape that tames them, and see the future direction in which the field is moving. </blockquote></td></tr><tr valign="top"><td>2025-11-19</td><td>Justus Piater gives an invited talk <i>Structural Understanding – The Grand Challenge of Robot
+    Learning</i> at <a href="https://elliit.se/news-and-events/focus-period-lund-2025/symposium/">ELLIIT Focus Period Symposium: Robot Learning</a>, Lund University. (The ELLIIT Focus Period Symposium is the highlight of the five-week focus period, during which young international scholars, ELLIIT researchers and other well-established international academics gather in Lund to work together on joint research challenges.) <span class="actions"><a href="javascript:void(0)" onclick="showHide('newsitem8', 'Abstract')">[Abstract]</a></span><blockquote id="newsitem8Abstract" style="display:none">AI has made great progress in recent years, and the
+    sophistication of robots has been rising with costs falling. Yet,
+    the capabilities of AI-enabled robots are not keeping pace. I
+    argue that this is due to a lack of structural understanding by
+    current AI systems. I will discuss several lines of research in my
+    lab that seek to enable robots to generalize better and learn
+    faster thanks to explicit notions of structure.</blockquote></td></tr><tr valign="top"><td>2025-09-18</td><td>Samuele Tosatto gives an invited keynote <i>Where are all the intelligent robots? A quest for efficiency in reinforcement learning</i> at <a href="https://sarl-plus.github.io/RL-Bootcamp2025/">Reinforcement Learning Bootcamp 2025</a>, Salzburg. <span class="actions"><a href="javascript:void(0)" onclick="showHide('newsitem9', 'Abstract')">[Abstract]</a></span><blockquote id="newsitem9Abstract" style="display:none">As artificial intelligence reshapes our digital world at a breathtaking pace,
+    a curious question arises: Where are all the real-world, intelligent robots?
+    While we have mastered the generation of text, images, and video by leveraging vast web-scale datasets,
+    robotics still faces a fundamental data bottleneck. Reinforcement learning (RL) offers a compelling solution,
+    enabling agents to learn autonomously by collecting their own experience.
+    However, the path to autonomy is often blocked by the staggering inefficiency of current RL algorithms,
+    which can require millions of trials to master simple tasks. This talk embarks on a quest to tackle this
+    efficiency problem head-on. I will argue that a crucial step toward unlocking the potential of
+    robot learning lies in a two-pronged approach: first, by developing statistically efficient
+    algorithms that can reuse data by leveraging sound off-policy techniques, and second,
+    by designing better action representations for physical, real-world agents.
+    By making our algorithms more efficient and refining their core hypotheses,
+    we can accelerate the journey toward real embodied artificial intelligence.</blockquote></td></tr><tr valign="top"><td>2025-07-15</td><td>Justus Piater gives an invited keynote <i>Making robots learn to perceive and act with
+    understanding</i> at <a href="https://www.uibk.ac.at/en/congress/multibody2025/">The
+th ECCOMAS Thematic Conference on Multibody Dynamics</a>, Innsbruck. <span class="actions"><a href="javascript:void(0)" onclick="showHide('newsitem10', 'Abstract')">[Abstract]</a></span><blockquote id="newsitem10Abstract" style="display:none">The flexibility and robustness of current robots is
+    limited by their lack of understanding of their environment. For
+    this reason, most robots operate in controlled environments.
+    Machine learning can circumvent modeling problems but introduces
+    new problems of generalizing from examples. How can robots acquire
+    understanding (of structure, function, causality, etc.) that
+    allows them to generalize from sparse experience? Motivated by
+    shortcomings of current machine-learning methods, I will argue
+    that &quot;understanding&quot; is a meaningful notion in AI that reaches
+    beyond prediction and control. I will discuss examples of our
+    recent work on learning visual relational concepts, extrapolation
+    of learned movements beyond the training distribution, learning of
+    symbolic concepts and rules, and structure-driven skill learning
+    from sensorimotor experience. Our long-term objective is to
+    improve abstraction, generalization, robustness, and ultimately
+    explainability of robot perception and action.</blockquote></td></tr></table></HTML>
 [[news|Older News]]
@@ Line 47: / Line 94: @@
 Austria
-**How to find us:** See the [[http://informatik.uibk.ac.at/how-to-reach-us/|directions]].
+**How to find us:** See the [[https://www.uibk.ac.at/informatik/kontakt/anfahrt.html.en|directions]].
 **Legal Notice:** See the [[:impressum|Impress and Privacy Notice]].

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