Bettina Finzel

Research Assistant (Doctoral Candidate)

 

Office: WE5/04.028
Office hours: Thu, 10:00 - 12:00, by apppointment otherwise

Phone: +49 951 863 2878
Email: bettina.finzel(at)uni-bamberg.de

orcid.org/0000-0002-9415-6254

 

Bettina Finzel holds a bachelor and a master degree in Applied Computer Science from the University of Bamberg. In 2018 she joined the Cognitive Systems Group as a research assistant and doctoral candidate in the project TraMeExCo, which is funded by the Federal Ministry for Education and Research. Since 2019 she is member of the Bamberg Graduate School of Affective and Cognitive Sciences (BaGrACS).

since 10/2018Research Assistant in the project Transparent Medical Expert Companion (TraMeExCo) founded by BMBF at Cognitive Systems Group, Faculty of Information Systems and Applied Computer Sciences, Otto-Friedrich-Universität Bamberg, Germany
10/2016 - 10/2019Applied Computer Science Study at the Faculty of Information Systems and Applied Computer Sciences, Otto-Friedrich-Universität Bamberg, Germany (Master of Science, with distinction)
04/2018 - 09/2018Internship concerning the Implementation of Predictive Analytics at MHP Management- und IT-Beratung GmbH
10/2012 - 03/2017Applied Computer Science Study at the Faculty of Information Systems and Applied Computer Sciences, Otto-Friedrich-Universität Bamberg, Germany (Bachelor of Science)

 

Main Research Interests

  • Interpretable and Interactive Machine Learning for human-AI partnerhip in medical diagnosis
  • Explainable Artificial Intelligence for Deep Learning-based classification

Methods

  • Relational Learning, especially Inductive Logic Programming
  • Constraint Programming
  • Visual post-hoc explanations

Further Research Interests

  • Mentoring in Computer Science
  • Diversity and Fairness

Advised Theses

Antonia Höfer: Enhancing an Interactive Machine Learning Companion by Corrective Feedback with User-defined Global Constraints (BA AI)

Namrata Jain: Managing Chemical Production Processes with Deep (Transfer) Learning (MA ISSS, in collaboration with Wacker AG)

Michael Fuchs: Towards Fast Interactive Machine Learning with Aleph (BA AI)

Rene Kollmann: Explaining Facial Expressions with Temporal Prototypes (MA AI)

Isabel Saffer: Generierung und Evaluation von kontrastiven Erklärungen für die Paarweise Klassifikation von Partiell Geordneten Tumorklassen in der Histopathologie (Generating and Evaluating Contrastive Explanations for Pairwise Classification of Partially Ordered Tumorclasses in Histopathology) -- (BA AI, finished in August 2020)

Nina Krob: Ausdrucksstärke und Effizienz in der Generierung von Erklärungen: Vergleich von Association Rule Mining und Induktiver Logischer Programmierung für Interpretierbare Klassifikation von Schmerz (Expressiveness and Efficiency in Explanation Generation: Comparing Association Rule Mining and Inductive Logic Programming for Interpretable Pain Classification) (BA AI, finished in July 2020)

Simon Kuhn: Identifying Near Misses for Relational Concepts with Graph Matching – Explaining Classifier Decisions of Facial Expressions (BA AI, finished in June 2019)

2020

  • Bruckert S., Finzel B., Schmid U. (2020). The next generation of medical decision support: a roadmap towards transparent expert companions. Frontiers in Artificial Intelligence, section Medicine and Public Health (zur Veröffentlichung angenommen).
  • Finzel B. (2020), Korrigierbares maschinelles Lernen mithilfe wechselseitiger Erklärungen am Beispiel der Medizin. Frauen machen Informatik - Magazin der Fachgruppe Frauen und Informatik der GI (zur Veröffentlichung angenommen).
  • Deuschel J., Finzel B., Rieger I. (2020), Uncovering the Bias in Facial Expressions. FORSCHEnde FRAUEN Kolloquium, Bamberg University Press (zur Veröffentlichung angenommen).
  • Rieger I., Kollmann R., Finzel B., Seuß D., Schmid U. (2020), Verifying Deep Learning-based Decisions for Facial Expression Recognition. 28th European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning (ESANN, 22-24.4.2020, Bruges, Belgium) (zur Veröffentlichung angenommen).
  • Schmid U., Finzel B. (2020), Mutual Explanations for Cooperative Decision Making in Medicine. Künstliche Intelligenz, 34, 227–233.

2019

  • Rieger I., Finzel B., Seuß D., Wittenberg T., Schmid U. (2019) Make Pain Estimation Transparent: A Roadmap to Fuse Bayesian Deep Learning and Inductive Logic Programming (Poster). 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC, 23.-27. Juli 2019, Berlin).
  • Finzel B., Schmid U. (2019) Erklärbare KI für medizinische Anwendungen (Talk). 49. Kongress der Deutschen Gesellschaft für Endoskopie und Bildgebende Verfahren e.V. (28.-30. März 2019, Stuttgart), Track der Deutschen Gesellschaft für Biomedizinische Technik "Krankenhaus der Zukunft".
  • Finzel B., Rabold J., Schmid U. (2019) Explaining Relational Concepts: When Visualisation and Visual Interpretation of a Deep Neural Network's Decision are not enough (Abstract). Europäische Konferenz zur Datenanalyse (ECDA, 18.-20. März 2019, Bayreuth), Special Session on Interpretable Machine Learning.
  • Finzel, B., Sperker H.-C. (2019) Machine Learning goes E-Mobility: Mit Datenanalyse die Elektromobilität vorantreiben - Konzepte und Methoden zur Implementierung von Predictive-Analytics-Komponenten. JAXenter Online Magazin, 2019. -- [Link]

2018

  • Finzel B., Deininger H., Schmid U. (2018) From beliefs to intention: mentoring as an approach to motivate female high school students to enrol in computer science studies. In Proceedings of the 4th Conference on Gender & IT (GenderIT '18). ACM, New York, NY, USA, 251-260.

2017

  • Elmamooz, G., Finzel, B. & Nicklas, D., (2017). Towards Understanding Mobility in Museums. In: Mitschang, B., Nicklas, D., Leymann, F., Schöning, H., Herschel, M., Teubner, J., Härder, T., Kopp, O. & Wieland, M. (Hrsg.), Datenbanksysteme für Business, Technologie und Web (BTW 2017) - Workshopband. Bonn: Gesellschaft für Informatik e.V.. (S. 127-136).

All Publications

Master's Thesis

  • Finzel B., (2019). Explanation-guided Constraint Generation for an Inverse Entailment Algorithm. Master's Thesis, University of Bamberg, 2019 (unpublished).

Bachelor's Thesis

  • Finzel B., (2017). A graph-based context model for PoI-based interactive guidance in museums. Bachelor's Thesis, University of Bamberg, 2017 (unpublished).

Awards

  • Finalist of the competition "KI-Newcomer*innen Wettbewerb 2019" of the German Informatics Society, -- [News]
  • Finalist of the Future X Healthcare Scientific Excellence Award 2019, Roche, Munich -- [News]
  • Female Tech Talents Stipendium (2018) awarded by Campusjäger
  • Award of the Ministry for Environment and Health (2012) for a Sustainability and Nutrition Education Project for Elementary Schools

Talks

  • Gedanken zu Künstlicher Intelligenz und der künftigen Gesellschaft, Diskussionspanel Gesellschaft 4.0, Jahreskonferenz des Deutsch-Tschechischen Gesprächsforums zum Thema "Die Zukunft der deutsch-tschechischen Beziehungen aus der Sicht junger Deutscher und Tschechen", Olomouc, 20.11.2018 -- [Program]
  • Künstliche Intelligenz und Medizin: Von operierenden Robotern und Computerdiagnosen, Tag der Begabtenförderung 2019, Kloster Banz, 8.7.2019 -- [Report]
  • Learning Expressive First Order Rules - Introduction to Inductive Logic Programming, talk held in KIZI seminar, University of Economics Prague, 22.10.2019 -- [Event]
  • Skalpell bitte! KI in der Medizin: Chancen und Herausforderungen, KI und Wir* Convention, Magdeburg, 23.11.2019 -- [Program], [Abstract], [News]
  • Constraints as Verbal Corrective Feedback -- An Inductive Logic Programming Approach to Generate and Adapt Explanations in Image Classification, 1st GK Doctoral Symposium on Cognitive Science, 23.-24.01.2020 -- [Abstract]
  • Constraints as Verbal Corrective Feedback -- An Inductive Logic Programming Approach to Generate and Adapt Explanations in Image Classification, Virtuelle Konferenz der GI Fachgruppe Frauen und Informatik, 25.04.2020 -- [Program]
  • Uncovering the Bias in Facial Expressions, FORSCHEnde FRAUEN Kolloquium der Universität Bamberg, 23.-30.06.2020 -- [Program], [News]
  • Künstliche Intelligenz - Konkurrenz oder Partnerschaft, Frauennetzwerk Fürth, 07.04.2020 (postponed) -- [Event]

Workshops and Lectures

  • Workshops
    • Das Mentoring Program make IT, 16. Arbeitstagung der Konferenz der Einrichtungen für Frauen- und Geschlechterstudien im deutschsprachigen Raum (KEG), Arbeitsgruppe „Mentoringprojekte in der Informatik“, University of Music and Performing Arts, Vienna, 26.9.2018 -- [Program]
    • Shiny R - Analysen interaktiv gestalten und visualisieren, course at the TAO-SFZ-Workshop „KI selber programmieren“, University of Bamberg 29.-31.10.2018 -- [Report]
    • Maschinelles Lernen und Data Science – Hands-On mit KNIME, Woche der Forschung, University of Bamberg, 26.2.2019 -- [Program]
  • Lectures
    • Classifying Medical Data with Neural Nets and Inductive Logic Programming, lecture including practical tasks in R and Prolog, University of Economics Prague, 22.10.2019 -- [Event]

Participation in Schools

  • Interdisciplinary College 2019 Günne/Möhnesee Germany “Out of your senses: from data to insight”, intense one-week spring school, 12.-18.3.2019
  • ECML PKDD Summer School 2019 Würzburg Germany “Machine Learning and Data Mining for Geo-Spatial Data/Volunteered Geographic Information, Quality of Experience and Human-Computer Interaction (EPSS19)”, intense one-week spring school, 11.-16.10.2019
    • included paper preparation in group work for submission at an international conference

Reviews

  • MICCAI Conference
  • ECML/PKDD Conference (Subreviewer)
  • KI Conference (Subreviewer)
  • ACM SIGMIS Conference (Subreviewer)
  • ACM GEWINN Conference
  • ACM SIGMIS Database Journal

Memberships and Voluntary Services

  • Member of the Bamberg Graduate School of Affective and Cognitive Sciences (BaGrACS)
  • Member of the German Informatics Society
  • Alumni Advisor for the make IT Computer Science Mentoring at the University of Bamberg (voluntary)
  • Elected member of the Czech-German Discussion Forum, participation in the task force for social and economic affairs, especially digital transformation topics (voluntary)