Miriam Elia M.Sc.

Research Assistant
Software Methodologies for Distributed Systems
Phone: +49 821 598 2472
Email:
Room: 3004 (N)
Address: Universitätsstraße 6a, 86159 Augsburg

Short Resume

  • Since December 2021: PhD candidate, Chair of Software Methodologies for Distributed Systems, University of Augsburg
  • 2021: Master’s degree in Business & Information Systems Engineering, University of Augsburg
  • 2019: Bachelor’s degree in Business & Information Systems Engineering, University of Augsburg
  • 2016: Bachelor of Education in English & French, University of Augsburg

Research Area

  • Trustworthy AI
  • Machine Learning in Healthcare
  • Certifiable AI in Medicine
  • Creation of a Generic and Customizable Methodology based on Quality Gates towards Certifiable AI in Medicine

Projects

Mentored Theses

  • "Zusammenführung multimodaler Datenquellen in einer Anwendung zur Analyse des Ösophagus für die Diagnoseunterstützung von Achalasie" - Master Thesis

Publications

2023 | 2021

2023

Miriam Elia and Bernhard Bauer. 2023. A methodology based on quality gates for certifiable AI in medicine: towards a reliable application of metrics in machine learning. DOI: 10.5220/0012121300003538
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Fabian Stieler, Miriam Elia, Benjamin Weigell, Bernhard Bauer, Peter Kienle, Anton Roth, Gregor Müllegger, Marius Nann and Sarah Dopfer. 2023. LIFEDATA - a framework for traceable active learning projects. DOI: 10.1109/REW57809.2023.00088
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Miriam Elia, Tobias Peter, Fabian Stieler, Bernhard Bauer, Sandra Nagl, Alanna Ebigbo and Vivien Grünherz. in press. Precision medicine for achalasia diagnosis: a multi-modal and interdisciplinary approach for training data generation [Abstract].
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Luuk H. Boulogne, Julian Lorenz, Daniel Kienzle, Robin Schön, Katja Ludwig, Rainer Lienhart, Simon Jegou, Guang Li, Cong Chen, Qi Wang, Derik Shi, Mayug Maniparambil, Dominik Müller, Silvan Mertes, Niklas Schröter, Fabio Hellmann, Miriam Elia, Ine Dirks, Matias Nicolas Bossa, Abel Diaz Berenguer, Tanmoy Mukherjee, Jef Vandemeulebroucke, Hichem Sahli, Nikos Deligiannis, Panagiotis Gonidakis, Ngoc Dung Huynh, Imran Razzak, Reda Bouadjenek, Mario Verdicchio, Pasquale Borrelli, Marco Aiello, James A. Meakin, Alexander Lemm, Christoph Russ, Razvan Ionasec, Nikos Paragios, Bram van Ginneken and Marie-Pierre Revel Dubios. in press. The STOIC2021 COVID-19 AI challenge: applying reusable training methodologies to private data.
BibTeX | RIS | URL

Dominik Mueller, Silvan Mertes, Niklas Schroeter, Fabio Hellmann, Miriam Elia, Bernhard Bauer, Wolfgang Reif, Elisabeth André and Frank Kramer. 2023. Towards automated COVID-19 presence and severity classification. DOI: 10.3233/shti230309
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2021

Miriam Elia, Carola Gajek, Alexander Schiendorfer and Wolfgang Reif. 2021. An interactive web application for decision tree learning.
PDF | BibTeX | RIS | URL | URL

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