PhD's Theses
Ongoing PhDs
- Lena BAUER: Mining High-Dimensional Data with Applications in Medicine (supervised by Claudia Plant und Philipp Grohs)
- Xandro BAYER: Machine Learning meets Financial Econometrics (supervised by Nikolaus Hautsch)
- Aleksandar DOKNIC: Explainable models: Visual parameter space analysis in neural networks (supervised by Torsten Möller and Claudia Plant)
- Guojun LAI: Efficient Data Analysis and Processing on Morden Hardware (supervised by Claudia Plant)
- Timothée SCHMUDE: Interpretability and Explainability as Drivers to Democracy (supervised by Sebastian Tschiatschek and Torsten Möller)
Former PhDs
- Leon GERARD: Solving the electronic Schrödinger equation using Deep Neural Networks (2024, supervised by Philipp Grohs)
- Alexander KINAST: Combining metaheuristics and process mining to improve
manufacturing processes (2023, supervised by Karl Dörner and Stefanie Rinderle-Ma) - Sebastian RATZENBÖCK: Finding needles in the Galactic haystack - Towards interpretable machine learning methods to identify stellar structures in the Milky Way (2022, supervised by João Alves and Torsten Möller)
- Michael SCHERBELA: Solving the Schrödinger Equation using Deep Neural Networks (supervised by Philipp Grohs)
- Michael SEDLMAYER: Convergence rate analysis of optimisation and minimax algorithms for machine learning (2023, supervised by Radu Bot)
Former Post-Docs:
- Pavol HARÁR
- Rafael REISENHOFER
Master's Theses
Business Analytics
- Sergio ARELLANO TINAJERO: Quantitative descriptive analysis of the social behavior and movements of wild sows in european nature (2024, supervised by Claudia Plant)
- Eduardo BAGGIO: Data mining for efficient request bundle generation in auction-based transportation collaborations (2023, supervised by Jan Ehmke)
- Petra BALIOVÁ: Impact of Weather Conditions of Public Transport Ridership: A Study of Bratislava Slovakia (2024, supervised by Jan Ehmke)
- Anja BOHATSCHEK: Concepts for spatial clustering of passenger rail booking data on a case study of the Austrian railway network (2023, supervised by Immanuel Bomze, co-supervised by Bertram Wassermann)
- Kseniia BOKOVAIA: Analyzing banking data by designing a Machine Learning tool for selecting the best model (2024, supervised by Yllka Velaj)
- Pavel CIMILI: Deep learning for automated damage detection of trailers at intermodal terminals (2023, supervised by Karl Dörner)
- Florian FAHRNGRUBER: Prediction of transfer passenger streams at an airport using machine learning (2022, supervised by Jan Ehmke)
- Stefan FILIPOVIĆ: SaaS business development through design thinking. A user-centered approach (2024, supervised by Arndt Niebisch)
- Clara HALMDIENST: Clustering nodes according to their access to information in networks (2024, supervised by Yllka Velaj)
- Soojeong JANG: Named entity recognition in government domain with reports from the city of Vienna court of audit (2023, supervised by Benjamin Roth)
- Carmen Maria KALUZINSKI: A time series churn analysis integrating the generation of product recommendations for customers (2023, supervised by Jan Ehmke)
- Marina KOZHEVNIKOVA: Applying predictive analytics to order book data of financial spot markets (2022, supervised by Roland Braune)
- Mykola LAZARENKO: Clustering brain regions by similar interaction patterns based on multivariate neural signals for identifying the response to antidepressants (2023, supervised by Claudia Plant, co-supervised by Katerina Schindlerova)
- Anastasiia MINAEVA: Development of metrics to measure and evaluate cities in terms of their implementation of the 15 minute city concept (2023, supervised by Roland Braune)
- Gabriela-Nicoleta PETROV: Robust crew scheduling problem using the Tabu Search metaheuristic (2023, supervised by Jan Ehmke)
- Sofiia Ihorivna PIVEN: Text analytics for customer relationship management in tourism (2023, supervised by Werner Winiwarter)
- Rebekka PRADER: Novel matheuristic for two echelon inventory routing problems in lower-middle income countries (2023, supervised by Karl Dörner)
- Ridhi Veerabhadrappa SHETRU: An iterated local search for the multi depot multi vehicle inventory routing problem (2024, supervised by Karl Dörner)
- Ava SUMESGUTNER: A comparison of forecasting methods for container freight indices in the context of recent supply chain shocks (2024, supervised by Karl Dörner)
- Tomáš Tax: Machine Learning for Direction Prediction in Equity Returns (2024, supervised by Christian Westheide)
- Theresa Sophie WOLF: A dynamic dial-a-ride problem with predicted return transports (2023, supervised by Karl Dörner)
- Johannes ZISCHG: Copositivity testing: a novel decomposition procedure for arbitrary matrices and an investigation of gradient-based search algorithms for finding violating vectors (2023, supervised by Immanuel Bomze)
Data Science
- Lorenzo BELTRAME: Artificial Intelligence for Airborne Phenotyping (2024, supervised by Sebastian Tschiatschek)
- Jonas BRUGGER: A two-step approach for analysing time-to-event data under non-proportional hazards (2023, supervised by Franz König)
- Louis CAUMEL MORALES: Clustering of Wind Related Time Series in a Wind Turbine Farm (2024, supervised by Claudia Plant, co-supervised by Katerina Schindlerova)
- Simon Noel-Marie FOURMAN: Estimation of sets with Barron boundaries under margin conditions (2023, supervised by Philipp Petersen)
- Konstantin HAAS: Generalized concentration protocols for gas sensing applications (2023, supervised by Moritz Grosse-Wentrup)
- Hannes JANKER: Conceiving, designing and implementing an energy dashboard on the example of the industrial company Constantia Teich (2024, supervised by Torsten Möller)
- Melanija KRALJEVSKA: Classification of treatment response in depression patients using motif discovery (2024, supervised by Claudia Plant)
- Pavla KROTKÁ: Model-based adjustments for non-concurrent comparisons in platform trials (2023, supervised by Martin Posch)
- Patrick POLLEK: Interpreting Neural Networks Under Latent Confounding (2024, supervised by Sebastian Tschiatschek)
- Michael RAFFELSBERGER: Variational autoencoders with structured missingness (2023, supervised by Sebastian Tschiatschek)
- Marlene STEINER: Analysis of gene expression data for precision medicine in ulcerative colitis (2023, supervised by Thomas Rattei)
- Sarah THILL: Unsupervised root cause analysis of anomalies in multivariate time series signals (2022, supervised by Sebastian Tschiatschek)
- Vojtech VORÁCEK: Learning with Reduced Molecular Graphs (2023, supervised by Nils Kriege)
- Susanna Maria WEINBERGER: Imitation learning from multiple perspectives (2024, supervised by Sebastian Tschiatschek)
- Elisabeth Katharina WIMMER: An analysis of dashboard usability and design for rowing coaches (2024, supervised by Torsten Möller)
- Lena ZELLINGER: Gradient matching for learning with noisy data (2022, supervised by Benjamin Roth)
Digital Humanities
- Christos BINTSIS: Applying Data Analytics and Natural Language Processing Methods in Acta Sanctorum (2024, supervised by Thomas Wallnig)
- Dasha EVSINA: Modelling power dynamics in piratical networks (2022, supervised by Tara Andrews)
- Annabelle Eunhasu LEE: "Omeka" for online exhibitions. A multidisciplinary analysis & evaluation (2024, supervised by Rebecca Kahn)
- Nora LINSER: Exploring the potential of digital and computational tools for analysis, research and visualization of art collections: a case study of MoMA's datasets (2023, supervised by Rebecca Kahn)
- Lisa Maria NUßBAUMER: Sensitive information leakage in neural taggers (2023, supervised by Benjamin Roth)
- David SIEGL: Measuring Plot in the Age of Distant Reading. A study in the search for the narrative arc within the stories of Sherlock Holmes (2024, supervised by Tara Andrews)
- Emilie SITTER: Predicting keywords in a corpus of field post letters (2024, supervised by Benjamin Roth)