Pascal is a professor for IT Security and Machine Learning at the department Digital Business & Software Engineering at MCI - The Entrepreneurial School in Innsbruck.
2022 - presentProfessor - Management Center Innsbruck, Austria2020 - 2022Associate Professor - Management Center Innsbruck, Austria2018 - 2020Lecturer - Management Center Innsbruck, Austria2015 - 2018Post-Doc - University of Innsbruck, Austria2014 - 2015Post-Doc - Westfälische Wilhelms-University Münster, Deutschland2013Visiting Scholar - Pennsylvania State University, USA2011 - 2014Scientific Staff Member (Doctoral Candidate) - Westfälische Wilhelms-University Münster, Germany2010 - 2011Scientific Student Assistent - Ruhr-University Bochum, Deutschland
2011 - 2014Computer Science - Westfälische Wilhelms-University Münster, Germany (Ph. D. (Dr. rer. nat))2008 - 2011IT Security / Networks and Systems - Ruhr-University Bochum, Germany (Master of Science)2003 - 2008Mathematical Engineering - University of Duisburg-Essen, Germany (Bachelor of Science)
Blended Learning 1-2-3 - MCI - The Entrepreneurial SchoolSakai Advanced - MCI - The Entrepreneurial SchoolAdobe Connect Advanced - MCI - The Entrepreneurial SchoolSakai Basic - MCI - The Entrepreneurial SchoolAdobe Connect Basics - MCI - The Entrepreneurial School
Multimedia Security - Westfälische Wilhelms-University Münster, GermanyAdvanced Cryptology - Westfälische Wilhelms-University Münster, GermanyIntroduction to Computer Engineering - University of Innsbruck, AustriaComputer Networks and Internet Technology - University of Innsbruck, AustriaInformation Security II - University of Innsbruck, AustriaCommunication Technology and Computer Networks - University of Innsbruck, AustriaLogic & Computability - Management Center Innsbruck, AustriaMathematics & Statistics - Management Center Innsbruck, AustriaAlgorithms & Data Structures - Management Center Innsbruck, AustriaManagement Information Systems - Management Center Innsbruck, AustriaData Science - Management Center Innsbruck, AustriaSecurity for Smart Technologies - MCI - The Entrepreneurial School, AustriaSmart Systems & Machine Learning - MCI - The Entrepreneurial School, AustriaIT Security - MCI - The Entrepreneurial School, AustriaIntegrated Overall Project - MCI - The Entrepreneurial School, Austria
2012IEEE International Workshop on Information Forensics and SecurityBest Student Paper Award2008CAST - Competence Center for Applied Security Technology2nd place at CAST Förderpreis in IT security,
2021 - 2023SMiLE - Secure Machine Learning Applications with Homomorphically Encrypted Data - SMiLE - Secure Machine Learning Applications with Homomorphically Encrypted Data - FFG - The Austrian Research Promotion Agency2019 - 2023Game Over Eva(sion): Securing Deep Learning with Game Theory Keywords: Deep Learning, Security, Game Theory, Evasion Attacks - Game Over Eva(sion): Securing Deep Learning with Game Theory Keywords: Deep Learning, Security, Game Theory, Evasion Attacks - FWF - Austrian Science Fund2017 - 2019"Forensic Analysis of Scanned Text Documents" (FASTDoc). - "Forensic Analysis of Scanned Text Documents" (FASTDoc). - Forschungsförderungsmittel der Nachwuchsförderung 2017 (University Innsbruck)
2015 FFG Relocation Grant, for the relocation from Germany to Austria. - 2013 ONR Visiting Researcher Grant, funding the research visit at the Pennsylvania State University, US. -
2018Programm Committee Co-Chair - ACM Information Hiding & Multimedia Security 20182018Programm Committee Member - IEEEE International Conference on Acoustics, Speech, and Signal Processing2015 - 2020Program Committee Member - ACM Information Hiding & Multimedia Security2015 - 2018Programm Committee Member - International Workshop on Digital-forensics and Watermarking
Rauter Roland (2022): Trainieren eines CNN mithilfe von Invariance-Based Adversarial ExamplesStockinger Rene (2022): Universal Adversarial Perturbations als Angriff gegen GesichtserkennungMösl Michael (2022): On-Device Modell Optimierung von Machine-Learning Algorithmen auf mobilen GerätenHüttl Mathis (2022): Welche Anforderungen hat eine Software zur Bekämpfung von Fake News im Internet und wie kann diese umgesetzt werden?Köll Julian (2022): Cybersecurity in Computerspielen - Sicherheitsaspekte von Offline- und Online-GamesGriesser Daniel (2022): State-of-the-art Algorithmen zur Generierung von Adversarial Examples - ein VergleichGugler Anton (2022): Material demand forecasting : Ein Vergleich statistischer, Machine Learning und Deep Learning Methoden.Temizkan Abdulkadir (2022): Evaluierung von Social Engineering MethodenMirocha Tobias (2021): PKI-basierte E-Mail-Verschlüsselung und -SignaturEichhorn Philipp (2021): Few-Shot Learning am Beispiel automatisierter RechnungsklassifikationThurner Maximilian (2021): Entwicklung eines Konzepts zur Steigerung der Passwortsicherheit und dessen Anwendung in einer SicherheitsanalyseDivković Marijan (2021): Making Machine Learning Accessible for SMEs: Framework Requirements and Clustering PrototypeKlingenschmid Lukas (2021): Detektion von Laser-Range Finder Messpulsen unter Verwendung von Machine Learning AlgorithmenLerch Judith (2021): Machine Learning zur Vorhersage von Zeitaufwand im Kontext von INNIO JenbacherAumayr Daniel (2021): Automatische Erkennung von Bildmanipulationen durch mobile Applikationen mit einem CNN
Moog Patrick (2022): Fooling Neural Networks for Age-/Gender- and Emotion-Prediction with Adversarial PatchesSirbu Mihaela Roxana (2021): Humans vs. CNNs: susceptibility to invariance and sensitivity based adversarial examplesWeber David (2021): How much pruning is too much? The effects of neural network pruning on machine learning explainabilityHofer Nora (2020): On the Robustness of a BERT Model for ABSA against Input Level Adversarial ExamplesMerkle Florian (2020): The Impact of Network Pruning on the Adversarial Robustness of Deep Neural NetworksBleckmann Carl (2020): What‘s next for IoT Forensics? A Proposal for Integration of Multimedia Forensic Methods to IoT Forensic ConceptsMuhr Valentin (2019): Data Deletion in Deep Learning Networks