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Academic Work & Historical Archive

Preserved peer-reviewed publications, graduate research seminars from Friedrich-Alexander-Universität Erlangen-Nürnberg, and earlier systems engineering prototypes.

PEER-REVIEWED PUBLICATION

Published Scientific Research

Flagship peer-reviewed journal article combining deep learning and mathematical optimization.

PEER-REVIEWED JOURNAL ARTICLEIOP Publishing · Dec 2025
DOI: 10.1088/2632-2153/ae25b6

High-quality tomographic image reconstruction integrating neural networks and mathematical optimization

Machine Learning: Science and Technology (IOP Publishing)

A compact ReLU network is trained to approximate local edge intensity from image patches, then translated into a mixed-integer formulation and integrated with an optimization-based reconstruction pipeline. The resulting method improves edge sharpness and material homogeneity while preserving explicit control over reconstruction fidelity.

CRediT Roles:
Lead: Software, Investigation, Formal Analysis, Data Curation
Equal: Conceptualization, Methodology, Validation, Visualization, Writing
Mathematical OptimizationDeep LearningComputed Tomography
GRADUATE RESEARCH

FAU Academic Seminars

Graduate research seminars delivered at Friedrich-Alexander-Universität Erlangen-Nürnberg.

FAU SeminarDecember 2023

MILP-Based Optimization for Deep Neural Networks

Selected Topics in Mathematical Optimization · Prof. Dr. Frauke Liers

Investigated mathematical formulation of DNNs using Mixed-Integer Linear Programming, focusing on piecewise linear ReLU activations, bound tightening algorithms, and certified adversarial verification.

PyTorchGurobi Solver
Read Seminar & Slides
HISTORICAL REPOSITORIES

Earlier Engineering Projects

Earlier systems engineering projects, medical IoT backends, and optimization prototypes.