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start [2026/06/25 06:25] IIS Webadmin |
start [2026/11/02 14:12] (current) Simon Haller-Seeber [Working With Us] |
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| 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? // | 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 ===== | ===== 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 do not currently have any open PhD positions. If you'd like to work with us starting in summer 2027, apply via the [[https://ellis.eu/news/ellis-phd-program-call-for-applications-2026|ELLIS PhD Program]] by 2026-10-31. | ||
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| </html> | </html> | ||
| - | {{ ::iis_retreat_2024.jpg?direct&900 |}}\\ | + | {{ ::iis-group-2026.jpg?direct&1000 |}}\\ |
| <html> | <html> | ||
| <div style="text-align: center;"> | <div style="text-align: center;"> | ||
| - | <p>Group picture taken at our 2024 retreat at Meissner Haus.</p> | + | <p>Group picture taken at our 2026 retreat at Maria Waldrast.</p> |
| </div> | </div> | ||
| </html> | </html> | ||
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| ===== News ===== | ===== News ===== | ||
| - | <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"> | + | <HTML><table><tr valign="top"><td>2026-09-27</td><td>Justus Piater co-organizes the <a href="https://worldmodelworkshop.github.io/">RoBoWoMo: |
| + | Bridging the Gap between Neural and Symbolic World Models for | ||
| + | Robot Planning, Reasoning, and Action</a>.</td></tr><tr valign="top"><td>2026-08-23 – 2026-08-28</td><td>David J. Crandall, Dirk Nowotka, Justus Piater, and Katrin Schöning-Stierand co-organize the <a href="https://www.dagstuhl.de/en/seminars/seminar-calendar/seminar-details/26351">Dagstuhl | ||
| + | Seminar 26351 on Digital Transformation of Research and Digital | ||
| + | Centers in the Science Landscape</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&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 | 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 | expert interview on “Human-robotics relations: What does the | ||
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| 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 | 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 | 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 | + | der Schule“, Pädagogische Hochschule Tirol. (Veranstaltung für Schulleitungen der Bildungsdirektion für Tirol) <span class="actions"><a href="javascript:void(0)" onclick="showHide('newsitem7', 'Abstract')">[Abstract]</a></span><blockquote id="newsitem7Abstract" style="display:none">Generative KI-Systeme wie ChatGPT und Midjourney haben |
| die Welt im Sturm erobert. Wie können wir sie produktiv nutzen? | die Welt im Sturm erobert. Wie können wir sie produktiv nutzen? | ||
| Wie können wir mit den Herausforderungen umgehen, die durch sie | Wie können wir mit den Herausforderungen umgehen, die durch sie | ||
| Line 45: | Line 47: | ||
| funktionieren. Daraus ergeben sich ein realistisches Verständnis | funktionieren. Daraus ergeben sich ein realistisches Verständnis | ||
| für ihre Möglichkeiten und Grenzen sowie einige grundlegende | 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. | + | 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('newsitem8', 'Abstract')">[Abstract]</a></span><blockquote id="newsitem8Abstract" 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 | 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 | + | 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('newsitem9', 'Abstract')">[Abstract]</a></span><blockquote id="newsitem9Abstract" style="display:none">AI has made great progress in recent years, and the |
| sophistication of robots has been rising with costs falling. Yet, | sophistication of robots has been rising with costs falling. Yet, | ||
| the capabilities of AI-enabled robots are not keeping pace. I | the capabilities of AI-enabled robots are not keeping pace. I | ||
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| current AI systems. I will discuss several lines of research in my | current AI systems. I will discuss several lines of research in my | ||
| lab that seek to enable robots to generalize better and learn | 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, | + | 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('newsitem10', 'Abstract')">[Abstract]</a></span><blockquote id="newsitem10Abstract" 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? | 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, | While we have mastered the generation of text, images, and video by leveraging vast web-scale datasets, | ||
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| by designing better action representations for physical, real-world agents. | by designing better action representations for physical, real-world agents. | ||
| By making our algorithms more efficient and refining their core hypotheses, | 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 | + | we can accelerate the journey toward real embodied artificial intelligence.</blockquote></td></tr></table></HTML> |
| - | 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('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 | + | |
| - | 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 "understanding" 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><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></table></HTML> | + | |
| [[news|Older News]] | [[news|Older News]] | ||
start.1782361513.txt.gz · Last modified: 2026/06/25 06:25 by IIS Webadmin