Associate Professor for Data Science
I will join the LMU Munich from summer on as an Associate Professor for Data Science.
2023
One paper accepted at PAKDD 2023
Cascaded Latent Diffusion Models for High-Resolution Chest X-ray Synthesis
One paper accepted at AIStats 2023, on paper accepted at ICLR 2023
Two papers on uncertainty quantification have been accepted!
2022
Combining Structured Regression and Deep Learning with Semi-Structured Distributional Regression
Our paper on Semi-Structured Distributional Regression has been accepted for publication in The American Statistician.
Probabilistic Time Series Forecasts with Autoregressive Transformation Models
Our paper on Autoregressive Transformation Models has been accepted for publication in Statistics and Computing.
Interim Professor TU Dortmund
I will be Interim Professor for Computational Statistics at the TU Dortmund this winter.
Accelerated Component-wise Gradient Boosting
Our paper on the acceleration of model-based boosting has been accepted for publication in the Journal of Computational and Graphical Statistics.
FaStR
Our paper Factorized Structured Regression for Large-Scale Varying Coefficient Models has been accepted at the ECML-PKDD 2022.
deepregression
Our Software Paper deepregression was accepted at the Journal of Statistical Software.
Interim Professor RWTH
I will be Interim Professor for Computational Statistics at the RWTH Aachen this summer.
Paper accepted at European Spine Journal
Paper on the comparison between ML and regression for neck pain prognostics accepted.
AStA Advances in Statistical Analysis
I am now Associate Editor for AStA Advances in Statistical Analysis
Advances in Statistical Learning with Neural Networks at CMStatistics
I will organize a session for Advances in Statistical Learning with Neural Networks
Guest Editor for AStA
I will be a Guest Editor for AStA Advances in Statistical Analysis
Paper accepted at Scientific Reports
Combining graph neural networks and spatio-temporal disease models to predict Covid-19 cases in Germany
Paper accepted at PAKDD
Deep Piecewise Exponential Additive Mixed Models
2021
Paper accepted at PLOS ONE
The mechanical energetics of walking across the adult lifespan
JSS Editorial Team
I was appointed Section Editor for the Journal of Statistical Software
Three Papers accepted at NeurIPS Workshops
Work on Climate Change, ML for Clinicians and Generative Models accepted.
Paper accepted at the Journal of Biomechanics
Comparing shallow, deep, and transfer learning in predicting joint moments in running
Paper accepted at WACV 2021
Joint Classification and Trajectory Regression of Online Handwriting using a Multi-Task Learning Approach
Paper accepted at the ICMLA
Paper Deep Semi-Supervised Time Series Classification accepted at ICMLA
Interim Professorship Data Science
I will serve another term as interim professor for Data Science (W2) in the upcoming winter semester.
Paper accepted at Computational Statistics and Data Analysis
Selective Inference for Additive and Linear Mixed Models
Paper accepted at the Journal of Electromyography and Kinesiology
Modern Machine Learning Approaches Applied in Spinal Pain Research
Our Work on Covid-19 is featured by Facebook’s Data for Good
Combining Graph Neural Networks and Spatio-temporal Disease Models to Predict COVID-19 Cases in Germany
Paper accepted at the ECML-PKDD Workshop on Automating Data Science (ADS2021)
AutoCompboost: Automatic Interpretable Boosting
Paper accepted at the Journal of Forecasting
Paper on Bayesian Time-Varying Autoregssive Models accepted at the Journal of Forecasting
Paper accepted at the ECML-PKDD
Paper Deep Conditional Transformation Models accepted at ECML
Interim Professorship Data Science
I was appointed interim professor for Data Science (W2) for next semester
Paper accepted at Scientific Reports (Nature)
Paper on Intra-Class Correlation as Pain Threshold Measurement
Our Covid-19 Paper and Facebook’s Data for Good Program
Our Covid-19 Paper was featured in an interview with Facebook
Paper accepted at AAAI Spring Symposium 2021
Paper on Semi-Structured Piecewise Exponential Models accepted at AAAI Spring Symposium 2021.
2020
Paper accepted at Scientific Reports (Nature)
Paper on Machine Learning Approach for Predictive Modelling of Post-surgical Recovery.
Framework for Survival Analysis in ML
Paper on Machine Learning for Survival Analysis accepted at the ECML 2020.
Another applied FDboost Paper accepted
Paper on classification of Patellofemoral Pain Syndrome accepted at Gait and Posture
Lecturer Position at the SLDS Chair
Today I finally got confirmed my new position.
Updates on Workshops
Due to Covid-19 we unfortunately had to cancel …
Interpretable Machine Learning Models for classifying Back Pain
Paper on interpretable machine learning models for classifying back pain accepted
Research Stay at Xiamen University
Thanks to several people making a short research stay at Xiamen University possible!
Unifying Statistical Models and Deep Neural Networks
I will present our new unifying method at the Institutskolloquium on 26th of February.
2019
We will host the useR! 2020 European Hub in Munich
From 7th to 10th of July in 2020 we will host the European useR! satellite conference in Munich.
Applied FDboost Paper accepted
Paper on neck pain classification accepted at Gait and Posture
Advances in Deep Regression EcoSta 2020
We will host a session on advances in deep regression.
Homepage Update
New homepage launched.
My Acadmic Career
I will join the working group computational statistics in Jan ‘20
Open Positions at our Working Group
Open researcher positions for deep distributional regressions
Update of our cAIC4 package
cAIC4 now supports lmeand gamm objects
Paper accepted at Computation and Statistics
Paper Inference for $L_2$-Boosting accepted
AppliedR Meetup @ CYOSS
Our next Applied R Meetup will be at CYOSS
Talk at DAGStat Conference 2019
I will give a talk on Inference for L2-Boosting
Paper accepted at Journal of Statistical Software
Paper Conditional Model Selection in Mixed-Effects Models with cAIC4 accepted