Dr. Matthias Lenga

Current areas of work: automation in data quality control workflows, multi-modal models for PII/PHI detection, content-based medical image/video retrieval, automated medical image modality/sequence labelling, automated medical image/video deduplication, metrics for medical image similarly assessment

Leading a data science group specialized in machine learning and medical imaging. Broad portfolio of projects in the areas of Radiology and Oncology. Our contributions include fundamental research, generative modelling in the field of contrast media and methods for companion diagnostic systems.

Scientist at the Philips Research Department for Digital Imaging. Working on machine learning methods for medical image processing in various modalities (CT, 3D ultrasound, X-ray) covering applications in musculoskeletal imaging, echocardiography, fetal screening and chest X-ray analysis.

Research at the interface of probability theory, optimization and financial mathematics. My work focused on understanding the relation between certain Markovian stochastic control problems and convex optimization problems on a topological pairings. In addition, I worked on approximation and non-linear filtering theory related to polynomial processes. Supervision of courses and student projects related to the MS Mathematical Finance and MS Quantitative Finance degree programs.