Eingeladene Vorträge

Hier finden Sie von Know-Center MitarbeiterInnen gehaltene Vorträge

2019

Tools and Methods for Data-Driven Business Model Innovation

Analyse von Big Data-basierten Geschäftsmodellen

München

München, Analyse von Big Data-basierten Geschäftsmodellen, TU München, Institut für Unternehmensführung, Institut für Logistik und Produktion

2019

Blended Learning for Professionals

Data-Driven Futures: Learning 4.0

Graz

Graz, Data-Driven Futures: Learning 4.0, Know-Center

2019

Future of Competitive Inteligence i

Automated Intelligence – Anticipating Relationships and Trends to Obtain Competitive and Market Advantage

Luxembourg
Successful Use cases for Competitive Intelligence Approaches to Automation of Information Processing to Gain Competitive Insights Future directions and the importance of AI and Deep Learning

Luxembourg, Automated Intelligence – Anticipating Relationships and Trends to Obtain Competitive and Market Advantage, ICI

2019

Automated Intelligence – Anticipating Relationships and Trends to Obtain Competitive and Market Advantage i

Automated Intelligence – Anticipating Relationships and Trends to Obtain Competitive and Market Advantage

Luxembourg
Agile, global enterprises need accurate and readily available information about customers, markets and competitors to formulate strategic decisions. We apply our expertise in collecting and processing information from open and closed sources to support key strategic functions such as technology observation, business intelligence and patent analysis. We provide design and implementation of innovative search solutions and intelligent dashboards that visually capture and present relevant information and support the data-driven decision-making process. Automated Intelligence is now more than ever an important side of the future of data analytics, therefore we apply multiple techniques for the automation of data processing and analysis through the usage of the latest machine learning and artificial intelligence algorithms. We present several successful use cases of our strategic intelligence partnerships and future directions.

Luxembourg, Automated Intelligence – Anticipating Relationships and Trends to Obtain Competitive and Market Advantage, ICI

2019

Eye tracking support for visual analytics systems: foundations, current applications, and research challenges i

the 11th ACM Symposium on Eye Tracking Research & Applications

Denver
Visual analytics (VA) research provides helpful solutions for interactive visual data analysis when exploring large and complex datasets. Due to recent advances in eye tracking technology, promising opportunities arise to extend these traditional VA approaches. Therefore, we discuss foundations for eye tracking support in VA systems. We first review and discuss the structure and range of typical VA systems. Based on a widely used VA model, we present five comprehensive examples that cover a wide range of usage scenarios. Then, we demonstrate that the VA model can be used to systematically explore how concrete VA systems could be extended with eye tracking, to create supportive and adaptive analytics systems. This allows us to identify general research and application opportunities, and classify them into research themes. In a call for action, we map the road for future research to broaden the use of eye tracking and advance visual analytics.

Denver, the 11th ACM Symposium on Eye Tracking Research & Applications, ACM

2019

Evaluation of Visual Decision Support Systems used in Semiconductor Industry

9th European advanced process control and manufacturing (apc|m) Conference

Villach

Villach, 9th European advanced process control and manufacturing (apc|m) Conference, Silicon Saxony

2019

Wie intelligent ist KI wirklich? i

Quergedacht

Graz
"Quergedacht" ist eine Veranstaltungsreihe, bei der MitarbeiterInnen der Energie Graz innovative Themen und aktuelle Fragestellungen nähergebracht werden. Bei dem Vortrag wurde das Thema Künstliche Intelligenz präsentiert, wobei versucht wurde aufzuzeigen wo wir heute mit der – datengetriebenen – KI stehen (d.h. was KI heute kann und was nicht) und wohin die Reise aus Forschungssicht geht.

Graz, Quergedacht, Energie Graz

2019

Workshop/Seminar des Stipendienprogramms i

Pfingstdialog 2019

Leibnitz
Kombination aus Vortrag und Workshop - Ideengenerierung von daten-getriebenen Use Case zur Verbesserung des öffentlichen Verkehrs

Leibnitz, Pfingstdialog 2019, Land Steiermark

2019

Workshop/Seminar des Stipendienprogramms i

Pfingstdialog 2019

Leibnitz
Kombination aus Vortrag und Workshop - Ideengenerierung von daten-getriebenen Use Case zur Verbesserung des öffentlichen Verkehrs

Leibnitz, Pfingstdialog 2019, Land Steiermark

2019

Workshop/Seminar des Stipendienprogramms i

Pfingstdialog 2019

Leibnitz
Kombination aus Vortrag und Workshop - Ideengenerierung von daten-getriebenen Use Case zur Verbesserung des öffentlichen Verkehrs

Leibnitz, Pfingstdialog 2019, Land Steiermark

2019

Wie intelligent ist KI heute schon? i

Impuls>>Live - Smart Services und Künstliche Intelligenz - Neue Entwicklungen und Trends

Graz
Der Vortrag beleuchtet den Status Quo von AI bzw. versucht das Thema auf den Boden der Tatsachen zu bringen. Folgende Punkte behandelt der Vortrag: (i) Geschichte der AI, (ii) Fähigkeiten der KI heute und (iii) zukünftige Entwicklungen der KI aus Forschungssicht.

Graz, Impuls>>Live - Smart Services und Künstliche Intelligenz - Neue Entwicklungen und Trends, SFG

2019

AI in Tourism i

Applied Artificial Intelligence Conference 2019

Wien
Panel discussion with representants from industry, public services and research about the application of AI in tourism (I stepped in for Wolfgang Kienreich)

Wien, Applied Artificial Intelligence Conference 2019 , WKO

2019

Reflection Guidance - State-of-the-art and challenges in Intelligent Tutoring Systems i

EATEL Summerschool

Bari
Adaptive reflection guidance can be understood as a specific kind of intelligent tutoring systems – as a kind of intelligent mentoring systems, as envisaged by Dimitrova (2006). These systems don’t encode to a very fine-granular degree domain knowledge, and learning strategies, but support the learner in developing the capability to learn in a self-directed manner; and in to learn about a particular learning domain. In this lecture and demo, I will show a concrete modular in-app reflection guidance framework, and its instantiation in different research prototypes (Fessl et al., 2017). I will also discuss how such a system relates to the very wide fields of intelligent tutoring systems and adaptive and context-aware systems in general; inheriting open challenges from each of these fields. In particular, it connects to promising fields of future TEL research in finding the sweet spot between human and artificial intelligence.

Bari, EATEL Summerschool, EATEL

2019

EMMA - der Mensch im Mittelpunkt der Pflege

Life Sciences im digitalen Wandel

Graz

Graz, Life Sciences im digitalen Wandel, HTS, BioNanoNet, Know-Center

2019

How (Not) To Train Your Neural Network Using the Information Bottleneck Principle i

Fifth London Symposium on Information Theory (LSIT) 2019

London
(This is joint work with Rana Ali Amjad from Technical University of Munich.) The information bottleneck theory of neural networks has received a lot of attention in both machine learning and information theory. At the heart of this theory is the assumption that a good classifier creates representations that are minimal sufficient statistics, i.e., they share only as much mutual information with the input features that is necessary to correctly identify the class label. Indeed, it has been claimed that information-theoretic compression is a possible cause of generalization performance and a consequence of learning the weights using stochastic gradient descent. On the one hand, the claims set forth by this theory have been heavily disputed based on conflicting empirical evidence: There exist classes of invertible neural networks with state-of-the-art generalization performance; the compression phase also appears in full batch learning; information-theoretic compression is an artifact of using a saturating activation function. On the other hand, several authors report that training neural networks using a cost function derived from the information bottleneck principle leads to representations that have desirable properties and yields improved operational capabilities, such as generalization performance and adversarial robustness.In this work we provide yet another perspective on the information bottleneck theory of neural networks. With a focus on training deterministic (i.e., non-Bayesian) neural networks, we show that the information bottleneck framework suffers from two important shortcomings: First, for continuously distributed input features, the information-theoretic compression term is infinite for almost every choice of network weights, making this term problematic during optimization. The second and more important issue is that the information bottleneck functional is invariant under bijective transforms of the representation. Optimizing a neural network w.r.t. this functional thus yields representations that are informative about the class label, but that may still fail to satisfy desirable properties, such as allowing to use simple decision functions or being robust against small perturbations of the input feature. We show that there exist remedies for these shortcomings: Including a decision rule or softmax layer, making the network stochastic by adding noise, or replacing the terms in the information bottleneck functional by more well-behaved quantities. We conclude by showing that the successes reported about training neural networks using the information bottleneck framework can be attributed to exactly these remedies.

London, Fifth London Symposium on Information Theory (LSIT) 2019

2019

Field Studies as evaluation method for socio-technical interventions in Technology-Enhanced Learning (TEL) i

EATEL Summerschool

Bari
Field studies as evaluation method for socio-technical interventions in Technology-Enhanced Learning. Much research in TEL is design work – i.e., the research team designs an intervention that is intended to support learning. This intervention needs to be evaluated to show the extent to which this goal has been reached; and to gain additional insights that are sought for. Field studies are one main type of evaluations. They are challenging to set up; and in case of a bad study design cannot be easily repeated due to the effort and cost of running a field study. The goal of this lecture and workshop is To provide a blueprint for field studies as evaluation method for socio-technical interventions in technology enhanced learning To present a hierarchical principle of evaluating learning interventions– based on Kirkpatrick & Kirkpatrick: Usage/observable activities – Learning – Impact on task/work performance – Impact on organization (in workplace learning/applicable to settings in which individual learning impacts a wider social entity) To have students plan a field study for their own PhD in rough lines individually To discuss their plans with peers and the lecturer, as well as other senior researchers who may be present – i.e., students will get feedback on their own plan The blueprint for field studies is to evaluate in a hierarchy of research questions/evaluation level: First, one assesses the observable (learning) activities that are carried out – in particular how and whether participants adhered to the prescribed intervention; this helps understand the success of the intervention and it is possible to identify problems. Second, one assesses concrete learning outcomes – insights that are generated. Thirdly, one assesses a change in behaviour, and fourthly a change in performance. In parallel, a mix of qualitative and quantitative methods should be used – this allows on the one hand statistical comparison (pre/post; between groups). On the other hand, one can get in depth explanatory insights.

Bari, EATEL Summerschool, EATEL

2019

Artificial Intelligence - und die Wichtigkeit bei österreichischen Unternehmen/Institutionen i

Digital Austria / Artifical Intelligence

Hof bei Salzburg
Panel discussion with representants from industry, public services and research about the impact of AI for Austrian economy

Hof bei Salzburg, Digital Austria / Artifical Intelligence, LSZ Consulting

2019

Status Quo of AI - Is a chatbot intelligent? i

From zero to chatbot in one hour

Wien
What's the conection between a chatbot and AI? The keynote gives an overview about the current state of AI as well as discusses research directions and future challenges of AI.

Wien, From zero to chatbot in one hour, 2050 Thinkers Club Vienna

2019

Big Data Strategies i

Studiengang Regenerative Energiesysteme & technisches Energiemanagement

Wieselburg
Die Digitalisierung ist einer der großen Megatrends der Gesellschaft und neben der Energiewende das bestimmende Thema in der Energiewirtschaft. Die Lehrveranstaltung, die im Rahmen des Moduls "Digitalisierung" des berufsbegleitenden Masterlehrganges "Regenerative Energiesysteme & technisches Energiemanagement" stattfindet, gibt einen Einblick in die grundlegenden Konzepte von Big Data – angefangen von entsprechenden Begriffserklärungen, über Verfahren der Datenanalyse, Aspekte der Datenökonomie bis hin zu datengetriebenen Geschäftsmodellen und rechtlichen Fragen im Umgang mit Big Data.

Wieselburg, Studiengang Regenerative Energiesysteme & technisches Energiemanagement, Fachhochschule Wiener Neustadt

2019

Was kann der Computer vom Menschen lernen und was nicht i

Modern Workplace: Effizienz und Attraktivität des modernen Arbeitsplatze

4020 Linz
Die Möglichkeiten und Unmöglichkeiten der KI Unterstützung

4020 Linz, Modern Workplace: Effizienz und Attraktivität des modernen Arbeitsplatze, Insight Technology Solutions GmbH

2019

Was kann der Computer vom Menschen lernen und was nicht i

Modern Workplace: Effizienz und Attraktivität des modernen Arbeitsplatze

9020 Klagenfurt
Die Möglichkeiten und Unmöglichkeiten der KI Unterstützung

9020 Klagenfurt, Modern Workplace: Effizienz und Attraktivität des modernen Arbeitsplatze, Insight Technology Solutions GmbH

2019

Was kann der Computer vom Menschen lernen und was nicht i

Modern Workplace: Effizienz und Attraktivität des modernen Arbeitsplatze

1020 Wien
Die Möglichkeiten und Unmöglichkeiten der KI Unterstützung

1020 Wien, Modern Workplace: Effizienz und Attraktivität des modernen Arbeitsplatze, Insight Technology Solutions GmbH

2019

Possibilities and Challenges of Digitalisation in the Semiconductor and Other Domains

APC|M Europe Conference

Villach

Villach, APC|M Europe Conference, Silicon Saxony

2019

Data Driven Product Development - A Tool Based Approach to Build Great Data Products i

Let's Cluster

Graz
Products fueled by data and machine learning can be a powerful way to solve users‘ needs. The opportunity extends far beyond the tech giants: companies of a range of sizes and across sectors are investing in their own data-powered products and business models. But the data component adds an extra layer of complexity. To tackle the challenge, companies should emphasize cross functional collaboration, evaluate and prioritize data product opportunities with an eye to the long-term, and start simple.

Graz, Let's Cluster, Silicon Alps

2019

Digital Future Life i

Let's Cluster

Graz
Short presentation of Know-Center's portfolio on the basis of a use case from the everyday life of a person in the future

Graz, Let's Cluster, Silicon Alps Cluster

2019

Obtaining Knowledge From Text-based Sources i

Strategic Intelligence Workshop 1

Graz
Give you an overview on Competitive Intelligence. Introduce a framework for Innovation from Uberbrands. Present Know-Center competencies and case studies. Discuss your challenges and collaboration possibilities.

Graz, Strategic Intelligence Workshop 1, Know-center and Uberbrands

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