CV Dr. Peter Gmeiner
Senior Machine Learning Engineer @GfK, Mathematician @AlgoBalanceGithub, LinkedIn, Xing, Google Scholar, Twitter: @PeterGmeiner4,
E-Mail: peter.gmeiner(at)algobalance.com
last update: 01/2023
Summary
A mathematician who is currently working in ML/AI, applying causal inference in practice (e.g. implementing a causal inference engine). I have years of experience in developing software as a full-stack software developer (Python, R, Java, C++, C#, SQL, Jupyter, PHP, HTML, Docker, Kubernetes, Spark, UML, ...). This technical knowledge is built on top of a foundational understanding of Machine Learning and AI techniques supplemented with years of research experience at university. My research interest is in causal inference, causal discovery, and in the connection between ML and causality.Positions
since 02/2019 | Senior Machine Learning Engineer at GfK SE, Nürnberg, Germany Tasks:
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11/2016-12/2018 | Software engineer at Orpheus GmbH, Nürnberg, Germany Tasks:
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since 04/2016 | Managing director, software, and algorithm developer at AlgoBalance UG (haftungsbeschränkt), Germany Tasks:
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04/2016 | Co-founder of AlgoBalance UG (haftungsbeschränkt), Germany | |
10/2015-09/2016 | EXIST scholarship holder, idea provider and know-how provider for the 'FoodOptimizer' project. | |
08/2015-09/2015 | Analysis algorithmic specialist at codemanufaktur GmbH, Erlangen, Germany Tasks:
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11/2010-03/2015 | Research assistant at the Department Mathematics of the University of Erlangen-Nürnberg, Germany Tasks:
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Education
03/2015 | PhD in Mathematics, University of Erlangen-Nürnberg, Thesis: 'Spectral Hypergraph Partitioning and Relative Entropy' | |
10/2010 | Diploma in Mathematics, University of Erlangen-Nürnberg, Thesis: 'Komplexitätsmaße und Emergenz' | |
07/2005 | intermediate diploma in computer science, University of Applied Sciences Nürnberg | |
07/2003 | subject-related advanced technical college entrance qualification (Fachabitur) |
Grants
10/2015-09/2016 | government grant (EXIST) for the software project 'FoodOptimizer' (now called Nutrimizer) |
Publications
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Talks
05/2024 | Causality and LLMs, we.innovate May 2024, GfK Nürnberg. | |
12/2022 | Machine Learning for Causal Analysis, GfK's Causal Inference Engine, Talk together with Michael Grottke at Data Science Summit 2022. | |
12/2022 | Statistical Transportability between Markets, Causal Inference Meeting. | |
12/2022 | Semi-Markovian Causal Models, Talk at GfK Nürnberg. | |
11/2022 | Markovian Causal Models, Talk at GfK Nürnberg. | |
06/2022 | On (un)observed confounders in causal models, Talk at GfK Nürnberg. | |
05/2022 | On (un)observed confounders in causal models, Causal Inference Meeting. | |
01/2022 | Causal Effect Estimation with Double Machine Learning, Causal Inference Meeting. | |
01/2022 | Causal Effect Estimation with Double Machine Learning, we.create 2022, GfK Nürnberg. | |
05/2021 | Causal Inference Engine, Talk at GfK Nürnberg. | |
01/2021 | Statistical Transportability between Markets, we.create 2021, GfK Nürnberg. | |
07/2020 | Causal discovery with Point of Sales data, 3rd International Conference on Advanced Research Methods and Analytics (CARMA 2020), 2020. | |
01/2020 | Causal discovery with POS data and business knowledge, we.create 2020, GfK Nürnberg. | |
03/2019 | Causality: Applications and Connections to Machine Learning, Talk at GfK Nürnberg. | |
03/2015 | Information-Theoretic Cheeger Inequalities, Special Seminar, MPI Leipzig. | |
04/2013 | Vertex and edge coloring models, 'Arbeitsgemeinschaft' with topic 'Limits of Structures', Oberwolfach. | |
09/2012 | Some Properties of Persistent Mutual Information, European Conference on Complex Systems 2012 in Brussels. | |
05/2012 | Spektren von Laplaceoperatoren auf Hypergraphen, Forschungsseminar Analysis, Stochastik und Mathematische Physik, TU Chemnitz. | |
04/2012 | The classical KAM Theory, 'Arbeitsgemeinschaft' with topic 'Quasiperiodic Schrödinger Operators', Oberwolfach. | |
03/2012 | Überraschende Geometrie und Fraktale, Tag der Mathematik, Erlangen. | |
10/2011 | Quantum ergodicity for quantum graphs, 'Arbeitsgemeinschaft' with topic 'Quantum Ergodicity', Oberwolfach. |
Skills
Mathematical skills | graph theory, information theory, statistical inference, causal inference, statistics and probability theory, exponential families, Bayesian networks, calculus, algorithm development and analysis, optimization | |
Methodological skills | (log)-linear models, regression models, random forest, SVM, neural networks (especially deep learning), LDA, reinforcement learning, clustering methods, causal models, causal inference and discovery methods, GAM, hidden Markov models, natural language processing (Word2Vec, Fasttext), (non)-linear optimization, particle swarm optimization | |
Programming languages | C, C++, C#, SQL, Java, Visual Basic, HTML, PHP, Python, Javascript, jQuery, Latex, Matlab, Mathematica, Maple, R | |
Application software | Office (MS Office, OpenOffice), Git, Dia, Apache | |
Development environments | Eclipse, Visual Studio, Aptana Studio, RStudio, Xamarin Studio, Intellij IDEA, PyCharm, Jupyter, Hive | |
Software design | UML, design patterns, object orientation, microservice architecture | |
Operating systems | MS Windows, Linux (Debian), MacOS, Android, iOS | |
Project management | Scrum, Agile Software Development | |
Language skills | German (native), English (fluent) | |
Other interests and hobbies | running (active), hiking, artificial intelligence, nutritional sciences, philosophy |