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Prof. Dr. Patrick Glauner

KI-Gesamtpaket:

Methodik und Technologie
Kommerzialisierung
Rechtliche, wirtschaftliche und politische Fragestellungen

Fakultät Angewandte Informatik

Professorinnen und Professoren

Professor

Praktikumsbeauftragter der Bachelorstudiengänge Artificial Intelligence und Künstliche Intelligenz

K 005

0991/3615-453

Sprechzeiten

Freitags von 13 bis 14 Uhr während der Vorlesungszeit und nach Vereinbarung. Bitte zuvor per E-Mail Kontakt aufnehmen.

Publikationen

Sortierung:

Beitrag in Sammelwerk/Tagungsband

Patrick Glauner
A. Boechat
L. Dolberg
R. State
F. Bettinger
Y. Rangoni
D. Duarte

Large-scale detection of non-technical losses in imbalanced data sets.

DOI: 10.1109/ISGT.2016.7781159

(2016)

Zeitschriftenartikel

Patrick Glauner
J. Meira
P. Valtchev
R. State
F. Bettinger

The Challenge of Non-Technical Loss Detection Using Artificial Intelligence: A Survey.

In: International Journal of Computational Intelligence Systems (vol. 10) , pg. 760-775

(2017)

DOI: 10.2991/ijcis.2017.10.1.51

Abstract anzeigen

Detection of non-technical losses (NTL) which include electricity theft, faulty meters or billing errors has attracted increasing attention from researchers in electrical engineering and computer science. NTLs cause significant harm to the economy, as in some countries they may range up to 40% of the total electricity distributed. The predominant research direction is employing artificial intelligence to predict whether a customer causes NTL. This paper first provides an overview of how NTLs are defined and their impact on economies, which include loss of revenue and profit of electricity providers and decrease of the stability and reliability of electrical power grids. It then surveys the state-of-the-art research efforts in a up-to-date and comprehensive review of algorithms, features and data sets used. It finally identifies the key scientific and engineering challenges in NTL detection and suggests how they could be addressed in the future.

Beitrag in Sammelwerk/Tagungsband

Patrick Glauner
N. Dahringer
O. Puhachov
J. Meira
P. Valtchev
R. State
D. Duarte

Identifying Irregular Power Usage by Turning Predictions into Holographic Spatial Visualizations.

DOI: 10.1109/ICDMW.2017.40

(2017)

Beitrag in Sammelwerk/Tagungsband

Patrick Glauner
P. Valtchev
R. State

Impact of Biases in Big Data.

pg. 645-654

(2018)

Beitrag in Sammelwerk/Tagungsband

M. Thurner
Patrick Glauner

Digitalization in Mechanical Engineering.

In:
Patrick Glauner
P. Plugmann

Springer pg. 107-117

(2020)

Beitrag in Sammelwerk/Tagungsband

S. Mund
Patrick Glauner

Autonomous Driving on the Thin Trail of Great Opportunities and Dangerous Trust.

In:
Patrick Glauner
P. Plugmann

Springer pg. 153-165

(2020)

Beitrag in Sammelwerk/Tagungsband

Patrick Glauner

Unlocking the Power of Artificial Intelligence for Your Business.

In:
Patrick Glauner
P. Plugmann

Springer pg. 45-59

(2020)

Beitrag in Sammelwerk/Tagungsband

L. Trestioreanu
Patrick Glauner
J. Meira
M. Gindt
R. State

Using Augmented Reality and Machine Learning in Radiology.

In:
Patrick Glauner
P. Plugmann

Springer pg. 89-106

(2020)

Beitrag in Sammelwerk/Tagungsband

Patrick Glauner

Staying Ahead in the MOOC-Era by Teaching Innovative AI Courses.

pg. 5-9

(2021)

Beitrag in Sammelwerk/Tagungsband

Patrick Glauner

Artificial Intelligence in Healthcare: Foundations, Opportunities and Challenges.

In:
Patrick Glauner
P. Plugmann
G. Lerzynski

[S.l.]: Springer Nature Switzerland AG pg. 1-15

(2021)

Beitrag in Sammelwerk/Tagungsband

Patrick Glauner

Everyone Needs to Acquire Some Understanding of What AI Is.

In:
A. Loth

John Wiley & Sons Canada, Limited pg. 267-281

(2021)

Beitrag in Sammelwerk/Tagungsband

U. Hutschek
T. Abele
P. Plugmann
Patrick Glauner

Efficiently Delivering Healthcare by Repurposing Solution Principles from Industrial Condition Monitoring: A Meta-Analysis.

In:
Patrick Glauner
P. Plugmann
G. Lerzynski

[S.l.]: Springer Nature Switzerland AG pg. 171-176

(2021)

Monographie

Patrick Glauner
P. Ramin

Digitalisierungskompetenzen. Rolle der Hochschulen.

München: Carl Hanser Verlag GmbH & Co. KG

(2021)

Beitrag in Sammelwerk/Tagungsband

Horst Kunhardt

Home 4.0: With Sensor Data from Everyday Life to Health and Care Prognosis.

In:
Patrick Glauner
P. Plugmann
G. Lerzynski

[S.l.]: Springer Nature Switzerland AG

(2021)

Zeitschriftenartikel

F. Ünal
A. Almalaq
S. Ekici
Patrick Glauner

Big Data-Driven Detection of False Data Injection Attacks in Smart Meters.

In: IEEE Access (vol. 9) , pg. 144313-144326

(2021)

DOI: 10.1109/ACCESS.2021.3122009

Abstract anzeigen

Today’s energy resources are closer to consumers thanks to sustainable energy and advanced metering infrastructure (AMI), such as smart meters. Smart meters are controlled and manipulated through various interfaces in smart grids, such as cyber, physical and social interfaces. Recently, a large number of non-technical losses (NTLs) have been reported in smart grids worldwide. These are partially caused by false data injections (FDIs). Therefore, ensuring a secure communication medium and protected AMIs is critical to ensuring reliable power supply to consumers. In this paper, we propose a novel Big Data-driven solution that employs machine learning, deep learning and parallel computing techniques. We additionally obtained robust statistical features to detect the FDIs based cyber threats at the distribution level. The performance of the proposed model for NTL detection is investigated using private smart grid datasets in the Turkish distribution network for AMI-level cyber threats, and the results are compared to state-of-the-art machine learning algorithms used for NTL classification problems. Our approach shows promising results, as the accuracy, specificity, and precision metrics of most classifiers are above 90% and false positive rates vary between 0.005 to 0.027.

Beitrag in Sammelwerk/Tagungsband

Patrick Glauner

Innovation Management for Artificial Intelligence.

In:
Patrick Glauner
V. Nestle
P. Plugmann

[S.l.]: Springer International Publishing pg. 1-13

(2021)

Beitrag in Sammelwerk/Tagungsband

Agnes Nocon

Evaluating the ethical aspects of online counselling.

In:
Patrick Glauner
P. Plugmann
G. Lerzynski

[S.l.]: Springer Nature Switzerland AG

(2021)

Beitrag in Sammelwerk/Tagungsband

Horst Kunhardt

Modern Home Care: A Glimpse into the Future of Patient-Centered Healthcare Systems.

In:
F. Thieringer
P. Plugmann
S. Ehsani
Patrick Glauner

Cham, Switzerland: Springer International Publishing pg. 251-261

(2022)

Beitrag in Sammelwerk/Tagungsband

Patrick Glauner

An Assessment of the AI Regulation Proposed by the European Commission.

In:
F. Thieringer
P. Plugmann
S. Ehsani
Patrick Glauner

Cham, Switzerland: Springer International Publishing

(2022)

Beitrag in Sammelwerk/Tagungsband

Anna-Maria Kasparbauer
Veronika Reisner
C. Schenk
A. Glas
Helana Lutfi
Oscar Blanco
Thomas Spittler

Sensor Devices, the Source of Innovative Therapy and Prevention.

In:
F. Thieringer
P. Plugmann
S. Ehsani
Patrick Glauner

Cham, Switzerland: Springer International Publishing pg. 207-226

(2022)

Beitrag in Sammelwerk/Tagungsband

S. Ehsani
Patrick Glauner
P. Plugmann
F. Thieringer

Introduction: Trends, Puzzles and Hopes for the Future of Healthcare.

In:
F. Thieringer
P. Plugmann
S. Ehsani
Patrick Glauner

Cham, Switzerland: Springer International Publishing

(2022)

Beitrag in Sammelwerk/Tagungsband

Thomas Spittler
Helana Lutfi

Innovations for Sustainable Healthcare.

In:
F. Thieringer
P. Plugmann
S. Ehsani
Patrick Glauner

Cham, Switzerland: Springer International Publishing pg. 343-357

(2022)

Beitrag in Sammelwerk/Tagungsband

Patrick Glauner

Künstliche Intelligenz im Gesundheitswesen: Grundlagen, Möglichkeiten und Herausforderungen.

In:
R. Grinblat
D. Etterer
P. Plugmann

Wiesbaden: Springer Fachmedien Wiesbaden GmbH pg. 143-160

(2022)

Beitrag in Sammelwerk/Tagungsband

T. Jelinek
A. Bhave
N. Buchoud
M. Buehler
Patrick Glauner
O. Inderwildi
M. Kraft
C. Mok
K. Nuebel
M. Pathak
S. Some
A. Voss

Advancing AI for Climate Action: Global Collaboration on Intelligent Decarbonisation.

In:
Observer Research Foundation
Observer Research Foundation

(2023)

Beitrag in Sammelwerk/Tagungsband

Patrick Glauner

Lessons from Germany.

In:
S. Hansen
K. Daniels

Cheltenham, UK; Northampton, MA: Edward Elgar Publishing pg. 295-303

(2023)

Zeitschriftenartikel

T. Jelinek
A. Bhave
N. Buchoud
M. Bühler
Patrick Glauner
O. Inderwildi
M. Kraft
C. Mok
K. Nübel
A. Voss

International Collaboration: Mainstreaming Artificial Intelligence and Cyberphysical Systems for Carbon Neutrality.

In: IEEE Transactions on Industrial Cyber-Physical Systems (vol. 2) , pg. 26-34

(2024)

DOI: 10.1109/TICPS.2024.3351624

Abstract anzeigen

Cyberphysical systems together with Artificial Intelligence play vital roles in reducing, eliminating, and removing greenhouse gas emissions across sectors. Electrification with renewables introduces complexity in systems in the deployment, integration, and efficient orchestration of electrified economic systems. AI-driven cyberphysical systems are uniquely suited to tackle this complexity, potentially accelerating the transition towards a low-carbon economy. The objective of this policy brief is to advocate for the mainstreaming of AI-driven cyberphysical systems for climate change risk mitigation and adaptation. To effectively and more rapidly realize the Intelligent Decarbonation potential, the concept of AI-driven cyberphysical systems must be elevated to a global level of collaboration and coordination, fostering research and development, capacity building, as well as knowledge and technology transfer. Drawing on a multidisciplinary, international study about intelligent decarbonization use cases, this brief also highlights factors impeding the transition to carbon neutrality and risks associated with technology determinism. The importance of governance is emphasized to avoid unwanted path dependency and avert a technology-solutionist approach dominating climate policy that delivers limited results. Given only 12% of the Sustainable Development Goals have been realized, a condensed version of this policy brief was submitted to the India T20, a G20 engagement group, urging global collaboration to prioritize AI-driven CPSs.

Beitrag in Sammelwerk/Tagungsband

Patrick Glauner

§ 1 Technische Grundlagen von generativen KI-Modellen.

In:
M. Ebers
B. Quarch

Baden-Baden: Nomos Verlagsgesellschaft mbH & Co. KG pg. 21-42

(2024)

Bericht/Report

J. Zhou
Patrick Glauner
D. Kaminskiy

IFF Global Artificial Intelligence Competitiveness Index Report - Part 1: Analyzing AI Competitiveness From the Enterprise Perspective. International Finance Forum.

(2024)

Zeitschriftenartikel

Patrick Glauner

Technical foundations of generative AI models.

In: Legal Tech - Zeitschrift für die digitale Anwendung , pg. 24-34

(2024)

Abstract anzeigen

In recent years, generative AI has gained prominence for its ability to create realistic and creative content, from text and images to music and beyond. This paper serves as a comprehensive guide to the technical foundations underpinning the fascinating field of generative AI models. Understanding the core principles and techniques behind these models is essential for both practitioners, lawyers, judges, policy makers, and enthusiasts seeking to harness their potential.

Beitrag in Sammelwerk/Tagungsband

Richard Latzel
Patrick Glauner

Artificial Intelligence in Sport Scientific Creation and Writing Process.

In:
F. Gassmann
M. Fröhlich
E. Bartaguiz
C. Dirndorf

Cham: Imprint Springer, Springer Nature Switzerland pg. 15-29

(2024)

Beitrag in Sammelwerk/Tagungsband

Patrick Glauner

KI: Auswirkungen auf Altersvorsorge und Vermögensbildung.

In:
H.-G. Horlemann
A. Briese

Berlin: Erich Schmidt Verlag pg. 1-5

(2024)

Kernkompetenzen

KI und Maschinelles Lernen
Big Data, Bildverstehen und Sprachverarbeitung
Kommerzialisierung von KI und Innovationsmanagement
Rechtliche, wirtschaftliche und politische Fragestellungen
Quantencomputing
Branchenkenntnisse: Automobil, Bau, Beratung, Bildung, Energie, Finanzen, Gesundheitswesen, Halbleiter, IT, Landwirtschaft, Logistik, Management, Maschinenbau, Materialwissenschaften, Nachrichtendienste, Polizei, Stromversorgung, Verkehr, Verteidigung, Versicherungen und weitere

Mehr Informationen: www.glauner.info

Forschungs- und Lehrgebiete

Kurse:

Algorithmen und Datenstrukturen
Big Data
Bildverstehen
KI-Innovationsmanagement
KI-Projekt
Quantencomputing

Mehr Informationen: www.glauner.info/teaching

Vita

Besondere Erfolge:

Beratung der Parlamente von Deutschland, Frankreich und Luxemburg als Sachverständiger
Führung durch das CDO Magazine und Global AI Hub in der Liste der weltweit führenden Professoren im Datenbereich
Panelist im AI House Davos während des Jahrestreffen 2024 des World Economic Forum
Sprecher beim Jahrestreffen 2024 des International Finance Forum
Veranstaltung des CERN Spring Campus 2024 an der TH Deggendorf

Positionen:

Seit 2020: Professor für Künstliche Intelligenz, TH Deggendorf
2022 - 2023: Ramon O'Callaghan Professor of Technology Management and Innovation, Woxsen University
2019 - 2020: Head of Data Academy, Alexander Thamm GmbH
2018 - 2019: Innovationsmanager für Künstliche Intelligenz, Krones AG
2018: Gastforscher, Université du Québec à Montréal (UQAM)
2015 - 2018: Doktorand, Universität Luxemburg
2012 - 2014: Fellow, Europäische Organisation für Kernforschung (CERN)

Abschlüsse:

2019: Promotion in Informatik, Universität Luxemburg
2018: MBA, Quantic School of Business and Technology
2015: MSc in Machine Learning, Imperial College London
2012: BSc in Informatik, Hochschule Karlsruhe

Stipendium:

Studienstiftung des deutschen Volkes