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| ===== Working With Us ===== | ===== Working With Us ===== | ||
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| + | * 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&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 <a href="https://www.tirol.gv.at/fileadmin/themen/bildung/medienzentrum/downloads/07_Magazin_Co/2025_01.pdf">Lieber | + | |
| - | gleich berechtigt als später: Hallo KI, hilfst du uns bei der | + | |
| - | Gleichstellung?!</a>, 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" 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 | + | |
| - | "understand" 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]] | ||