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start [2020/11/23 08:50]
IIS Webadmin
start [2026/06/11 06:17] (current)
Justus Piater [Working With Us]
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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]].
-  * [[https://ellis.eu/|ELLIS]] PhD Program: ​[[https://ellis.eu/de/news/​ellis-phd-program-call-for-applications|Call for Applications]]+  * [[:​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 
  
-<​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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- +{{ ::iis_retreat_2024.jpg?direct&​900 ​|}}\\ 
-{{::dsc_0052.jpg?640|Group Picture}}\\ +<​html>​ 
-Group picture taken at our retreat ​in Obergurgl +<div style="​text-align:​ center;">​ 
 +  <p>Group picture taken at our 2024 retreat ​at Meissner Haus.</​p>​ 
 +</​div>​ 
 +</​html>​
  
 ===== News ===== ===== News =====
  
-<​HTML><​table><​tr valign="​top"><​td>​2020-11-20</​td><​td>​Simon Haller-Seeber and Patrick Lamprecht present ​show <​i>​Explainable AI: A sneak peek into the Black-Box</​i> ​at <a href="​https://​youtube.com/watch?​v=4NVfPwdLnCg&​amp;​t=17m43s">Science Slam +<​HTML><​table><​tr valign="​top"><​td>​2026-05-07</​td><​td>​Justus Piater is panelist ​at a public discussion on <a href="​https://​www.uibk.ac.at/​de/​medien-kommunikation/​kommunikation/​intern/">Invited 
-    </​a>, ​online.</​td></​tr><​tr valign="​top"><​td>​2020-06-22</​td><​td>​Justus Piater gives an invited talk <i>Conditional Neural Movement Primitives</i> at <a href="http://www.gdr-isis.fr/index.php?​page=reunion&​amp;idreunion=424">GdR +    ​expert interview on “Human-robotics relations: What does the 
-    ​ISIS Réunion Apprentissage et Robotique</a>, online. <span class="​actions"><​a href="​javascript:​void(0)"​ onclick="​showHide('​newsitem1', '​Abstract'​)">​[Abstract]</​a></​span><​blockquote id="newsitem1Abstract" style="​display:​none">​Conditional Neural Movement Primitives (CNMP) constitute +    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 
-    ​a novel framework for robot programming by demonstration based on +    Interaction</i> at <a href="https://airov.at/​2026/​workshop/​TactileRobotics.html">​Austrian 
-    Conditional Neural Processes (CNP) Like Bayesian methods such as +    Robotics Workshop<​/a>, Leoben(Annual workshop of the GMARat AIRoV 2026)</​td></​tr><​tr valign="top"><​td>​2026-04-08</​td><​td>​Justus Piater gives an invited talk <​i>​Generative KI: Funktionsweise,​ Möglichkeiten und 
-    ​Gaussian Processes (GP)CNP learn how target distributions depend +    ​Grenzen</iat SchulleiterInnen-Tagung „IT-Sicherheit und KI-Einsatz in 
-    ​on data, and can be conditioned on specific data points to infer +    der Schule“Pädagogische Hochschule Tirol(Veranstaltung für Schulleitungen der Bildungsdirektion für Tirol) ​<span class="​actions"><​a href="​javascript:​void(0)"​ onclick="​showHide('​newsitem2', '​Abstract'​)">​[Abstract]</​a></​span><​blockquote id="newsitem2Abstract" style="​display:​none">​Generative KI-Systeme wie ChatGPT und Midjourney haben 
-    ​new target distributions at test time.  Unlike GP that are +    ​die Welt im Sturm erobertWie können wir sie produktiv nutzen? 
-    expensive to train and scale poorly to high dimensionsCNP are +    ​Wie können wir mit den Herausforderungen umgehendie durch sie 
-    ​neural networks and are trained by gradient descent CNMP +    ​entstehen? Ich werde diese Fragen von der technischen Seite her 
-    ​leverage CNP to represent motion trajectories that can be +    ​angehen und einen Eindruck davon vermittelnwie diese Systeme 
-    ​conditioned,​ at test time, on task paramters such as goal +    ​funktionierenDaraus ergeben sich ein realistisches Verständnis 
-    locations, via points, and/or force readings. ​ Moreover, CNMP are +    ​für ihre Möglichkeiten und Grenzen sowie einige grundlegende 
-    conditioned on sensor readings during execution, resulting in +    ​Empfehlungen für den Umgang mit ihnen im Schulbetrieb.</​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 
-    robust, reactive behavior. ​ This talk will present an overview of +    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('​newsitem3', '​Abstract'​)">​[Abstract]</​a></​span><​blockquote id="newsitem3Abstract" style="​display:​none">​AI has made great progress in recent years, ​and the 
-    how CNMP work and how they can be used in various robot +    ​sophistication of robots has been rising with costs falling. Yet, 
-    applications.</​blockquote></​td></​tr><​tr valign="​top"><​td>​2020-06-03</​td><​td>​Justus Piater appears in the media: Wie der Roboter denken lernt.</​td></​tr><​tr valign="​top"><​td>​2020-01-29</​td><​td>​Justus Piater gives an invited talk <i>Digital Science</i> at <a href="​https://​www.graduateacademy.uni-heidelberg.de/karriere/veranstaltungsreihen.html">Vortragsreihe +    the capabilities of AI-enabled robots are not keeping pace. I 
-    „Primers for Predocs – Strategien für eine erfolgreiche +    argue that this is due to a lack of structural understanding by 
-    Promotion“</​a>, ​Universität Heidelberg. <span class="​actions"><​a href="​javascript:​void(0)"​ onclick="​showHide('​newsitem4', '​Abstract'​)">​[Abstract]</​a></​span><​blockquote id="newsitem4Abstract" style="​display:​none">​Massive availability of data and computing power are +    ​current AI systems. I will discuss several lines of research in my 
-    ​promoting data-driven methods in all areas of science and +    ​lab that seek to enable robots to generalize better ​and learn 
-    ​technology I will describe how the University ​of Innsbruck +    ​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('​newsitem4',​ '​Abstract'​)">​[Abstract]</​a></​span><blockquote id="newsitem4Abstract"​ style="​display:​none">As artificial intelligence reshapes our digital world at a breathtaking pace,  
-    ​supports this via its new Digital Science Center, ​and will give a +    a curious question arises: Where are all the real-world, intelligent robots?  
-    ​flavor ​of machine learning for data analysis.</​blockquote></​td></​tr><​tr valign="​top"><​td>​2020-01-20</​td><​td>​Joanna Chimiak-Opoka,​ Carina König, and Justus Piater appear ​in the media: ​<a href="​https://​www.uibk.ac.at/newsroom/ergaenzung-digital-science-erfolgreich-gestartet.html.de">Ergänzung Digital Science erfolgreich gestartet – UIBK Newsroom</a>.</​td></​tr><​tr valign="​top"><​td>​2020-01-03</​td><​td>​Justus Piater gives an invited talk <​i>​Künstliche Intelligenz:​ GrundlagenErfolge, +    While we have mastered the generation of text, images, and video by leveraging vast web-scale datasets, 
-    Herausforderungen</​i>​ at 47. Tagung des Innsbrucker Kreises von MoraltheologInnen +    robotics still faces a fundamental data bottleneck. Reinforcement learning (RL) offers a compelling solution,  
-    und SozialethikerInnen,​ Innsbruck.</​td></​tr><​tr valign="top"><​td>​2019-12-19</​td><​td>​Justus Piater appears in the media: ​<a href="https://​tvthek.orf.at/​profile/​Tirol-heute/​70023/​Tirol-heute/​14035670/​Alexa-Siri-Co-Spione-im-eigenen-Haus/​14610743">TV interview by ORF 2 Tirol Heute RedHaus ​(in German)</a>.</td></​tr><​tr valign="top"><​td>​2019-12-12</​td><​td>​Justus Piater gives an invited lecture <​i>​Too Smart to Be Trusted – Do I Even Want to +    enabling agents ​to learn autonomously by collecting their own experience.  
-    ​Understand My Robot?</​i>​ at <href="​http://​www.trustrobots.eu/">​TrustRobots Lecture series +    However, the path to autonomy is often blocked by the staggering inefficiency of current RL algorithms, 
-    ​Trust in Robots</a>TU Vienna.</​td></​tr><​tr valign="​top"><​td>​2019-12-05</​td><​td>​IIS guest <span style="​font-weight:​bold">​Heiko Neumann</​span>,​ University of Ulm,  ​gives an invited ​colloquium ​<i>Biologically inspired visual-auditory processing – from +    ​which can require millions of trials to master simple tasks. This talk embarks on quest to tackle this  
-    ​brain-like computation to neuromorphic algorithms</i> at <a href="​https://​www.uibk.ac.at/​informatik/forschung/lunchtime-seminar/index.html.en">IFI Lunchtime Seminar</a>. <span class="​actions"><​a href="​javascript:​void(0)"​ onclick="​showHide('​newsitem9', '​Abstract'​)">​[Abstract]</​a></​span><​blockquote id="newsitem9Abstract" style="​display:​none">​A fundamental task of sensory processing ​is to detect +    efficiency problem head-onI will argue that a crucial step toward unlocking the potential of  
-    ​and integrate feature items to group them into perceptual units +    ​robot learning lies in a two-pronged approach: firstby developing statistically efficient  
-    segregating them from other objects and the background+    algorithms that can reuse data by leveraging sound off-policy techniques, and second,  
-    framework is discussed which explains how perceptual grouping at +    by designing better action representations for physical, real-world agents 
-    early as well as higher-level cognitive stages may be implemented +    By making our algorithms more efficient and refining their core hypotheses,  
-    in cortexDifferent grouping mechanisms are implemented which are +    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 
-    ​attuned to basic features and feature combinations and mainly +    ​understanding</i> at <a href="​https://​www.uibk.ac.at/​en/congress/multibody2025/">The 
-    ​evaluated along the forward sweep of stimulus processingHowever, +    12th ECCOMAS Thematic Conference on Multibody Dynamics</a>, Innsbruck. <span class="​actions"><​a href="​javascript:​void(0)"​ onclick="​showHide('​newsitem5', '​Abstract'​)">​[Abstract]</​a></​span><​blockquote id="newsitem5Abstract" style="​display:​none">​The flexibility and robustness ​of current robots ​is 
-    ​due to limitations ​of local feature detection mechanisms and +    ​limited by their lack of understanding of their environmentFor 
-    inherent ambiguitiestop-down feedback is required to deliver +    ​this reason, most robots operate ​in controlled environments
-    ​contextual information helping ​to disambiguate initial +    ​Machine learning can circumvent modeling problems but introduces 
-    ​measurements. Feedback ​of contextual information ​is demonstrated +    ​new problems ​of generalizing from examplesHow can robots acquire 
-    ​to improve object recognition performance,​ stabilize learning ​of +    ​understanding (of structurefunction, causality, etc.) that 
-    ​object categoriesand integrate multi-sensory representations. +    ​allows them to generalize from sparse experience? Motivated by 
- +    ​shortcomings ​of current machine-learning methods, I will argue 
-    ​The canonical principles ​of neural computation define a set of +    that &​quot;​understanding&​quot; ​is a meaningful notion in AI that reaches 
-    ​core operations to implement above-mentioned mechanisms of +    ​beyond prediction and control. I will discuss examples ​of our 
-    ​perceptual and cognitive inferenceThese operations can be +    ​recent work on learning visual relational conceptsextrapolation 
-    ​mappedin a simplified formonto neuromorphic platforms to +    of learned movements beyond the training distribution,​ learning ​of 
-    ​emulate brain-like computation. It is demonstrated that an +    ​symbolic concepts and rules, and structure-driven skill learning 
-    architecture composed ​of canonical circuit mechanisms can be +    ​from sensorimotor experienceOur long-term objective is to 
-    mapped onto neuromorphic chip technology facilitating low-energy +    ​improve abstractiongeneralizationrobustness, and ultimately 
-    non-von Neumann computation.</​blockquote></​td></​tr><​tr valign="​top"><​td>​2019-11-26</​td><​td>​IIS guest <span style="font-weight:bold">Tamim Asfour</span>, Karlsruhe Institute of Technology,  ​gives an invited ​keynote ​<i>Engineering Humanoids with Motion Intelligence</i> at <a href="​https://​www.uibk.ac.at/​informatik/studium/inday-students/index.html.en">inday students</a>. <span class="actions"><​a href="javascript:void(0)" ​onclick="​showHide('​newsitem10',​ '​Abstract'​)">​[Abstract]</​a></​span><blockquote id="newsitem10Abstract"​ style="​display:​none">Humanoid robotics plays a central role in robotics +    ​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:​ 
-    research as well as in understanding intelligence. Engineering +    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 Roboterwas macht eine KI? Entwickle deine eigene KI und programmiere unsere Minibots</iat Campustag BG/BRG Sillgasse, Universität Innsbruck.</​td></​tr></​table></​HTML>​
-    humanoid robots that are able to learn from humans and +
-    sensorimotor experience, to predict the consequences of actions +
-    and exploit the interaction with the world to extend their +
-    cognitive horizon remains a research grand challenge. Currently,​ +
-    we are experiencing AI systems with superhuman performance in +
-    games, image and speech processing. However, the generation of +
-    robot behaviors with human-like motion intelligence and +
-    performance has yet to be achieved. In this talk, I will present +
-    recent progress towards engineering 24/7 humanoid robots that link +
-    perception ​and action to generate intelligent behavior. I will +
-    show the ARMAR humanoid robots performing complex grasping and +
-    manipulation tasks in kitchen and industrial environments, +
-    learning actions from human observation and experience as well as +
-    reasoning about object-action relations.</blockquote></​td></​tr></​table></​HTML>​+
  
 [[news|Older News]] [[news|Older News]]
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 Austria Austria
  
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start.1606117818.txt.gz · Last modified: 2020/11/23 08:50 by IIS Webadmin