Sarem Seitz
DISL-Lab (KI-Labor Dependable Intelligent Systems)
Office: WE5/05.052
Office hours: by appointment
Phone:
Email: sarem.seitz(at)uni-bamberg.de
| since 09/2020 | Research assistant at DISL-Lab (CogSys Team) |
02/2019 - 04/2019 | Intern Data Scientist Advanced Analytics at McKinsey&Company Dusseldorf |
| since 12/2016 | Freelancing Data Scientist & Machine Learning Engineer |
| 10/2016 - 11/2016 | Intern Data Scientist Financial Accounting Advisory Services at EY Frankfurt a.M. |
| 10/2015 - 03/2016 | Intern Audit at PwC Nuremberg |
Main Research Interests
- Methods for Interpretable Machine Learning
- Reinforcement Learning
- Learning and forecasting with time-series data
- Statistical and Bayesian Learning
- Data Analysis
- Neuro-Symbolic Integration
- Differentiable Programming
Preprints
Seitz, S. (2021) - Mixtures of Gaussian Processes for regression under multiple prior distributions (arXiv)
Talks and Presentations
"Deep Learning - Das next big thing oder die nächste große Blase?" - Talk at Total Digital 2019, Coburg
"Wie lernen Maschinen? - Ein- und Ausblicke in aktuelle Erkenntnisse aus der KI-Forschung" - Talk at Total Digital 2020, Coburg
"Dependable AI under heavy tailed distributions" - Short presentation at KI2020 Workshop for dependable AI, Bamberg
Other
Personal blog: https://sarem-seitz.com
When is Bayesian Machine Learning actually useful?