Richard Baumgartner Email & Phone Number

Rahway, New Jersey, US

Rahway, New Jersey, US

• Statistical support and data analysis of preclinical and translational imaging studies in discovery and early drug development. Designed, analyzed and reported preclinical and early clinical studies with functional.
• Contribution to machine learning efforts at Merck: feature identification / screening in learn and confirm paradigm for biomarker identification cancer staging, heart failure classification from real world claims data.
• Developed clustering and visualization for high-dimensional imaging data in proof-of-concept imaging studies
• Performed repeatability and reproducibility analysis and longitudinal data analysis in imaging based on linear mixed effects model.
• Carried out simulations to estimate variability of test-retest outcome measures for quantitative imaging endpoints
• Developed processing pipelines for preclinical and clinical studies with functional Magnetic Resonance Imaging (fMRI)

Rahway, New Jersey, US

• Quantified low dimensional endpoints from stimulus driven and resting state functional MR imaging and spectroscopic data in temporal and frequency domain using model as well as data driven methods such as clustering.
• Developed clustering and visualization for high-dimensional imaging data in proof-of-concept imaging studies
• Performed repeatability and reproducibility analysis and longitudinal data analysis in imaging based on linear mixed effects model
• Investigated variability of test-retest outcome measures for quantitative imaging endpoints
• Developed processing pipelines for functional Magnetic Resonance Imaging (fMRI)
• Mentored new hires, biometricians, summer interns and contractors working on image processing and statistical analysis of imaging data

Rahway, New Jersey, US

• Carried out research in machine learning (classification and regression) for biomarker discovery from high-dimensional biomedical data in metabolomics and chemometrics (MR spectroscopy), genomics (gene microarrays) and.
• Developed dimensionality reduction, visualization, feature selection/extraction and data complexity assessment techniques for prediction of different species of pathogenic fungi from high-dimensional spectroscopic data
• Co-developed methods for classification error estimation and selection bias in under-sampled classification problems, mostly for spectroscopic data
• Developed multiple classifiers systems for classification of spectroscopic and gene expression data from neurodegenerative diseases and oncology
• Co-developed improved methods for prediction of osteoporosis from administrative data
• Supervised students and served as a lecturer for several undergraduate and graduate courses

• Developed methods for exploratory analysis of functional MRI data
• Implemented modifications to fuzzy k-means clustering. Developed minimum spanning tree ranking for visualization and exploration of fMRI time-series. Carried out comparisons between Principal Component Analysis (PCA).
• Co-developed signal processing methods for fMRI based on wavelets

Winnipeg, MB, CA

Taught intro math courses and supervised studentsCourses taught: Linear Algebra I, Linear Algebra II, Introduction to Calculus

Winnipeg, MB, CA

Taught courses and supervised master studentsCourses taught: Topics in applied linear algebra and optimization

Winnipeg, MB, CA

• Developed methods for exploratory data analysis (EDA) for fMRI based on PCA / factor analysis and cluster analysis. Pioneered application of EDA in fMRI

Würzburg, Bavaria, DE

• Carried out research in image segmentation of MR images
• Developed a software package for semi-automated segmentation of cardiac MRI

Munich, DE

Munich, DE

Phd, Electrical, Biomedical Engineering

Ing, Electrical Engineering

Mathematics, Physics