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start [2020/12/10 06:25]
IIS Webadmin
start [2025/10/23 06:25] (current)
IIS Webadmin
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 ===== Working With Us ===== ===== Working With Us =====
   * 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 
 +  * We currently do not have any open PhD positions. 
 + 
 +<​html><​!--We currently have [[jobs|one open PhD position]].--></​html>​
  
 <​html><​!-- <​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>​2020-11-19</​td><​td>​Justus Piater ​gives an invited ​talk <i>Machine Learning ​in Robotics</i> at <a href="​https://​baiome.org/">bAIome PI Talk, Center for +<​HTML><​table><​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('​newsitem0', '​Abstract'​)">​[Abstract]</​a></​span><​blockquote id="newsitem0Abstract" style="​display:​none">​As artificial intelligence reshapes our digital world at a breathtaking pace,  
-    Biomedical AI, University Medical Center Hamburg-Eppendorf</​a>, ​online. <span class="​actions"><​a href="​javascript:​void(0)"​ onclick="​showHide('​newsitem1', '​Abstract'​)">​[Abstract]</​a></​span><​blockquote id="newsitem1Abstract" style="​display:​none">​Machine Learning increasingly equips ​robots ​with +    a curious question arises: Where are all the real-world, intelligent ​robots 
-    ​learning capabilities ​and flexibility This will enable them to +    ​While we have mastered the generation of text, images, ​and video by leveraging vast web-scale datasets, 
-    ​act purposefully in unstructured environments and to react to +    robotics still faces a fundamental data bottleneckReinforcement learning (RL) offers a compelling solution, ​ 
-    ​unforeseen events. ​ People can teach them intuitively ​to perform +    ​enabling agents ​to learn autonomously by collecting their own experience. ​ 
-    ​tasks instead ​of having ​to program them in painstaking ways+    ​However, the path to autonomy is often blocked by the staggering inefficiency of current RL algorithms, 
-    ​Robots can learn from experience and can improve their behavior +    ​which can require millions ​of trials ​to master simple tasksThis talk embarks on a quest to tackle this  
-    over time In this talk I will give an overview ​of methods, +    ​efficiency problem head-on. I will argue that a crucial step toward unlocking the potential ​of  
-    ​opportunities,​ and challenges of machine ​learning in +    ​robot learning ​lies in a two-pronged approach: first, by developing statistically efficient ​ 
-    ​robotics.</​blockquote></​td></​tr><​tr valign="​top"><​td>​2020-11-20</​td><​td>​Simon Haller-Seeber ​and Patrick Lamprecht present a 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</​a>​online.</​td></​tr><​tr valign="​top"><​td>​2020-09-30</​td><​td>​Erwan Renaudo contributes a talk <​i>​ROSSINI:​ RobOt kidS deSIgn thiNkIng</​i>​ at <a href="​https://​www.springer.com/​gp/​book/​9783030674106">​Robotics in  +    ​algorithms that can reuse data by leveraging sound off-policy techniques, ​and second 
-    ​Education 2020</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 +    by designing better action representations for physical, real-world agents.  
-    ​ISIS Réunion Apprentissage et Robotique</​a>, ​online. <span class="​actions"><​a href="​javascript:​void(0)"​ onclick="​showHide('​newsitem4', '​Abstract'​)">​[Abstract]</​a></​span><​blockquote id="newsitem4Abstract" style="​display:​none">​Conditional Neural Movement Primitives (CNMP) constitute +    ​By making our algorithms more efficient and refining their core hypotheses,  
-    ​a novel framework for robot programming ​by demonstration based on +    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 
-    Conditional Neural Processes (CNP) Like Bayesian methods such as +    understanding</i> at <a href="https://www.uibk.ac.at/​en/​congress/​multibody2025/​">The 
-    ​Gaussian Processes (GP)CNP learn how target distributions depend +    ​12th ECCOMAS Thematic Conference on Multibody Dynamics</​a>, ​Innsbruck. <span class="​actions"><​a href="​javascript:​void(0)"​ onclick="​showHide('​newsitem1', '​Abstract'​)">​[Abstract]</​a></​span><​blockquote id="newsitem1Abstract" style="​display:​none">​The flexibility and robustness of current robots is 
-    ​on data, and can be conditioned on specific data points to infer +    ​limited ​by their lack of understanding of their environmentFor 
-    new target distributions at test time ​Unlike GP that are +    ​this reasonmost robots operate in controlled environments. 
-    ​expensive to train and scale poorly to high dimensionsCNP are +    ​Machine learning ​can circumvent modeling problems but introduces 
-    neural networks and are trained by gradient descent CNMP +    new problems of generalizing from examplesHow can robots acquire 
-    ​leverage CNP to represent motion trajectories that can be +    ​understanding (of structurefunction, causality, etc.) that 
-    ​conditionedat test time, on task paramters such as goal +    ​allows them to generalize from sparse experience? Motivated by 
-    ​locations, via points, ​and/or force readings ​Moreover,​ CNMP are +    ​shortcomings of current machine-learning methodsI will argue 
-    ​conditioned ​on sensor readings during executionresulting in +    ​that &​quot;​understanding&​quot;​ is a meaningful notion in AI that reaches 
-    ​robustreactive behavior. ​ This talk will present an overview ​of +    beyond prediction ​and controlI will discuss examples of our 
-    ​how CNMP work and how they can be used in various robot +    ​recent work on learning visual relational conceptsextrapolation 
-    ​applications.</​blockquote></​td></​tr><​tr valign="​top"><​td>​2020-06-03</​td><​td>​Justus Piater ​appears ​in the mediaWie 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 +    ​of learned movements beyond the training distributionlearning ​of 
-    „Primers for Predocs – Strategien für eine erfolgreiche +    ​symbolic concepts ​and rules, and structure-driven skill learning 
-    Promotion“<​/a>, Universität Heidelberg. <span class="​actions"><a href="​javascript:void(0)"​ onclick="​showHide('​newsitem7'​'​Abstract'​)">​[Abstract]</a></​span><​blockquote id="​newsitem7Abstract"​ style="​display:​none">​Massive availability of data and computing power are +    ​from sensorimotor experience. Our long-term objective is to 
-    promoting data-driven methods in all areas of science and +    improve abstraction,​ generalization,​ robustness, and ultimately 
-    technology. ​ I will describe how the University of Innsbruck +    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:​ 
-    supports this via its new Digital Science Center, and will give a +    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 2025Streif­züge an den Naht­stel­len von MedienBil­dung 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 SoftwareRobotics, and AIExploring 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</i> at Campustag BG/BRG SillgasseUniversität ​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 
-    flavor of machine learning for data analysis.</​blockquote>​</​td></​tr><​tr valign="​top"><​td>​2020-01-20</​td><​td>​Joanna Chimiak-OpokaCarina 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, +    Seminar: AI in Law and Practice: Regional Perspectives on European 
-    Herausforderungen</i> at 47. Tagung des Innsbrucker Kreises von MoraltheologInnen +    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 
-    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 +    ​gleich berechtigt als später: Hallo KI, hilfst du uns bei der 
-    Understand My Robot?</i> at <a href="http://www.trustrobots.eu/">TrustRobots Lecture series +    Gleichstellung?​!</​a>,​ Tiroler Bildungsinstitut Grillhof Vill. <span class="​actions"><​a href="​javascript:​void(0)"​ onclick="​showHide('​newsitem7',​ '​Abstract'​)">​[Abstract]</​a></​span><​blockquote id="​newsitem7Abstract"​ style="​display:​none">​Künstliche Intelligenz&​quot;​ bezeichnet derzeit Systeme, die 
-    ​Trust in Robots</​a>, ​TU Vienna.</​td></​tr></​table></​HTML>​+    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 tutorial <i>Programmieren eines autonomen Roboters anhand einer selbstentwickelten KI</​i>​ at STAIR-Lab INNALP Workshop für das Gymnasium Ursulinenen InnsbruckUniversität 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></​table></​HTML>​
  
 [[news|Older News]] [[news|Older News]]
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 Austria 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]]. **Legal Notice:** See the [[:​impressum|Impress and Privacy Notice]].
start.1607577922.txt.gz · Last modified: 2020/12/10 06:25 by IIS Webadmin