Scholar
Andreas Auer
Google Scholar ID: Rg_Ooc8AAAAJ
PhD Student, Ellis Unit Linz - Institute for Machine Learning, Johannes Kepler University, Linz
Citations & Impact
Citations
638
H-index
5
i10-index
3
Publications
9
Co-authors
20
list available
Publications
Resume (English only)
Academic Achievements
- - Pre-trained Forecasting Models: Strong Zero-Shot Feature Extractors for Time Series Classification (Recent Advances in Time Series Foundation Models @ NeurIPS 2025)
- - TiRex: Zero-Shot Forecasting Across Long and Short Horizons with Enhanced In-Context Learning (NeurIPS 2025 Main Conference)
- - Zero-Shot Time Series Forecasting with Covariates via In-Context Learning (Under Review)
- - TiRex: Zero-Shot Forecasting Across Long and Short Horizons ([Spotlight] Workshop on Foundation Models for Structured Data @ ICML 2025)
- - xLSTM: Extended Long Short-Term Memory ([Spotlight] NeurIPS 2024 Main Conference)
- - A data-centric perspective on the information needed for hydrological uncertainty predictions (Hydrol. Earth Syst. Sci. Discuss. (HESS))
- - xLSTM: Extended Long Short-Term Memory (First Workshop on Long-Context Foundation Models @ ICML 2024)
- - Conformal Prediction for Time Series with Modern Hopfield Networks (NeurIPS 2023 Main Conference)
- - VT-KGNN: A Valid Time Knowledge Graph Neural Network (Master Thesis, Technical University Vienna)
Research Experience
- - Pre Doc Researcher at Johannes Kepler University (May 2022 – Present)
- - Applied Scientist Intern at Amazon Web Services (AWS) (Sep 2025 – Dec 2025), research on Foundational Time Series Models
- - PhD Researcher at NXAI GmbH (Apr 2025 – Aug 2025), research on Foundational Time Series Models
- - Applied Scientist Intern at Amazon Web Services (AWS) (Jul 2024 – Nov 2024), research on Foundational Time Series Models
- - Knowledge and Software Engineer / ML Consultant at Onlim GmbH (Aug 2020 – Aug 2023), worked part-time as a Backend Developer during master’s studies, then provided machine learning consulting
- - Research Intern at University of Oxford (Feb 2020 – Feb 2020), short-term research internship
Education
- PhD: Machine Learning, Institute for Machine Learning at Johannes Kepler University, Linz, supervised by Sepp Hochreiter; Master's and Bachelor's: Computer Science, Technical University of Vienna.
Background
- PhD student in the field of Machine Learning, focusing on Deep Learning in the context of Time Series or more broadly — sequential data. Currently specifically interested in Foundational Time Series Models. Has experience as a professional Software Developer.
