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start [2025/08/29 17:00]
Justus Piater
start [2026/06/25 06:25] (current)
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 ===== Working With Us ===== ===== Working With Us =====
 +
 +  * We are hiring [[:jobs:|1 Postdoc and 3 PhD Students in Robot Learning]].
   * Check our thesis topics for [[theses/​start|Bachelor and Master 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   * [[:​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 currently do not have any open PhD positions. 
  
-<​html><​!--We currently have [[jobs|one open PhD position]].--></​html>​ 
  
-<​html><​!-- 
-//Bachelor students://​{{ ::​mobile-manipulator-crop.jpg?​nolink&​100|}} **Want to create artificial intelligence for autonomous robots?** Want to join our [[@/​uibk/​piater/​courses/​RC_Poster2.pdf |interdisciplinary LFUI team]] to compete in the 2020 [[https://​www.robocup.org/​leagues/​16|RoboCup@Work]] competition?​ Take the [[https://​lfuonline.uibk.ac.at/​public/​lfuonline_lv.details?​sem_id_in=19W&​lvnr_id_in=703135|Introduction to Robotics]] course in the winter semester 2019-20! 
---></​html>​ 
  
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 ===== News ===== ===== News =====
  
-<​HTML><​table><​tr valign="​top"><​td>​2025-07-15</​td><​td>​Justus Piater gives an invited keynote <​i>​Making robots learn to perceive and act with+<​HTML><​table><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">​ 
 +        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 
 +    expert interview on “Human-robotics relations: What does the 
 +    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 
 +    Interaction</​i>​ at <a href="​https://​airov.at/​2026/​workshop/​TactileRobotics.html">​Austrian 
 +    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 
 +    Grenzen</​i>​ at SchulleiterInnen-Tagung „IT-Sicherheit und KI-Einsatz in 
 +    der Schule“, Pädagogische Hochschule Tirol. (Veranstaltung für Schulleitungen der Bildungsdirektion für Tirol) <span class="​actions"><​a href="​javascript:​void(0)"​ onclick="​showHide('​newsitem5',​ '​Abstract'​)">​[Abstract]</​a></​span><​blockquote id="​newsitem5Abstract"​ style="​display:​none">​Generative KI-Systeme wie ChatGPT und Midjourney haben 
 +    die Welt im Sturm erobert. Wie können wir sie produktiv nutzen? 
 +    Wie können wir mit den Herausforderungen umgehen, die durch sie 
 +    entstehen? Ich werde diese Fragen von der technischen Seite her 
 +    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('​newsitem6',​ '​Abstract'​)">​[Abstract]</​a></​span><​blockquote id="​newsitem6Abstract"​ 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('​newsitem7',​ '​Abstract'​)">​[Abstract]</​a></​span><​blockquote id="​newsitem7Abstract"​ 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('​newsitem8',​ '​Abstract'​)">​[Abstract]</​a></​span><​blockquote id="​newsitem8Abstract"​ 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     understanding</​i>​ at <a href="​https://​www.uibk.ac.at/​en/​congress/​multibody2025/">​The
-    12th ECCOMAS Thematic Conference on Multibody Dynamics</​a>,​ Innsbruck. <span class="​actions"><​a href="​javascript:​void(0)"​ onclick="​showHide('​newsitem0', '​Abstract'​)">​[Abstract]</​a></​span><​blockquote id="newsitem0Abstract" style="​display:​none">​The flexibility and robustness of current robots is+    12th ECCOMAS Thematic Conference on Multibody Dynamics</​a>,​ Innsbruck. <span class="​actions"><​a href="​javascript:​void(0)"​ onclick="​showHide('​newsitem9', '​Abstract'​)">​[Abstract]</​a></​span><​blockquote id="newsitem9Abstract" style="​display:​none">​The flexibility and robustness of current robots is
     limited by their lack of understanding of their environment. For     limited by their lack of understanding of their environment. For
     this reason, most robots operate in controlled environments.     this reason, most robots operate in controlled environments.
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     improve abstraction,​ generalization,​ robustness, and ultimately     improve abstraction,​ generalization,​ robustness, and ultimately
     explainability of robot perception and action.</​blockquote></​td></​tr><​tr valign="​top"><​td>​2025-07-11</​td><​td>​Justus Piater and Alejandro Agostini give an invited talk <​i>​Learning Symbols and Abstractions in Robot Planning</​i>​ at <a href="​https://​www.unibz.it/​en/​events/​abstraction-language-science-engineering">​Abstraction:​     explainability of robot perception and action.</​blockquote></​td></​tr><​tr valign="​top"><​td>​2025-07-11</​td><​td>​Justus Piater and Alejandro Agostini give an invited talk <​i>​Learning Symbols and Abstractions in Robot Planning</​i>​ at <a href="​https://​www.unibz.it/​en/​events/​abstraction-language-science-engineering">​Abstraction:​
-    Language - Science - Engineering</​a>,​ Bolzano. (International Workshop)</​td></​tr><​tr valign="​top"><​td>​2025-04-25</​td><​td>​Simon Haller-Seeber gives an invited talk <​i>​AI-powered tools for real-time transcription and translation in action: A self-hosted open-source framework for digital spaces.</​i>​ at <a href="​https://​www.uibk.ac.at/​de/​medien/​veranstaltungen/​tagungen/​medien-wissen-bildung-2025/">​Medien - Wissen - Bildung 2025: Streif­züge an den Naht­stel­len von Medien, Bil­dung und Phi­lo­so­phie</​a>,​ Universität Innsbruck.</​td></​tr><​tr valign="​top"><​td>​2025-04-10</​td><​td>​Simon Haller-Seeber gives an invited keynote <​i>​Hands-on Approaches to Software, Robotics, and AI: Exploring Experiments and Science in Action</​i>​ at <a href="​https://​iis.uibk.ac.at/​public/​simon/​ECER-2025/">​European Conference on Educational Robotics (ECER 2025)</​a>,​ HTL Anichstrasse.</​td></​tr><​tr valign="​top"><​td>​2025-04-10</​td><​td>​Simon Haller-Seeber and Christopher Kelter teach a tutorial <​i>​Was sind Roboter, was macht eine KI? Entwickle deine eigene KI und programmiere unsere Minibots</​i>​ at Campustag BG/BRG Sillgasse, Universität Innsbruck.</​td></​tr><​tr valign="​top"><​td>​2025-04-03</​td><​td>​Justus Piater gives an invited keynote <​i>​What is AI really?</​i>​ at <a href="​https://​www.uibk.ac.at/​events/​2025/​04/​03/​ai-in-law-and-practice-regional-perspectives-on-european-rules">​Cross-Border +    Language - Science - Engineering</​a>,​ Bolzano. (International Workshop)</​td></​tr></​table></​HTML>​
-    Seminar: AI in Law and Practice: Regional Perspectives on European +
-    Rules</​a>,​ Universität Innsbruck.</​td></​tr><​tr valign="​top"><​td>​2025-03-06</​td><​td>​Justus Piater teaches a tutorial <​i>​Funktionsweise,​ Möglichkeiten und Grenzen von KI</​i>​ at Lieber gleich berechtigt als später: Hallo KI, hilfst du +
-    uns bei der Gleichstellung?​!,​ Tiroler Bildungsinstitut Grillhof Vill. <span class="​actions"><​a href="​javascript:​void(0)"​ onclick="​showHide('​newsitem6',​ '​Abstract'​)">​[Abstract]</​a></​span><​blockquote id="​newsitem6Abstract"​ style="​display:​none">​Künstliche Intelligenz&​quot;​ bezeichnet derzeit Systeme, die +
-    auf maschinellem Lernen (ML) basieren. Dieser Workshop führt in +
-    die Grundlagen des ML ein, mit besonderem Augenmerk auf neuronale +
-    Netze, der derzeit populärsten ML-Technologie. Darauf aufbauend +
-    vermittelt er ein Grundverständnis für prinzipielle Möglichkeiten +
-    und Grenzen von ML und warum es mit derzeitigen Mitteln extrem +
-    schwierig ist, Diskriminierung in KI-Systemen zu +
-    verhindern.</​blockquote></​td></​tr><​tr valign="​top"><​td>​2025-02-26</​td><​td>​Simon Haller-Seeber and Christopher Kelter teach a tutorial <​i>​Programmieren eines autonomen Roboters anhand einer selbstentwickelten KI</​i>​ at STAIR-Lab INNALP Workshop für das Gymnasium Ursulinenen Innsbruck, Universität Innsbruck.</​td></​tr><​tr valign="​top"><​td>​2025-02-26</​td><​td>​Marko Zarić teaches a tutorial <​i>​Einführung in das Programmieren mit Microcontrollern</​i>​ at STAIR-Lab INNALP Workshop für das Gymnasium Ursulinenen Innsbruck, Universität Innsbruck.</​td></​tr><​tr valign="​top"><​td>​2025-01-31</​td><​td>​Justus Piater gives an invited lecture <​i>​High-Level AI For Autonomous Robots</​i>​ at <a href="​https://​elias-ai.eu/​event/​ellis-vismac/">​ELIAS-ELLIS-VISMAC +
-    Winter School 2025</​a>,​ Brunico, Italy. <span class="​actions"><​a href="​javascript:​void(0)"​ onclick="​showHide('​newsitem9',​ '​Abstract'​)">​[Abstract]</​a></​span><​blockquote id="​newsitem9Abstract"​ style="​display:​none">​What barriers will have to be overcome to raise the +
-    flexibility and robustness of autonomous robots to the next level? +
-    I argue that current AI methods are unlikely to get there, no +
-    matter how far we scale them up. Robots need to be able to +
-    &​quot;​understand&​quot;​ their environment in ways that reach beyond +
-    prediction and control. I will discuss examples of work (ours and +
-    others'​) 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.</​blockquote>​</​td></​tr></​table></​HTML>​+
  
 [[news|Older News]] [[news|Older News]]
start.1756479641.txt.gz · Last modified: 2025/08/29 17:00 by Justus Piater