Sascha Hauck
PhD student at SOS from 2022 until 2023
Contact
Sascha Hauck joined the Lab as a PhD student in January 2022 and is part of the FlowForLife project funded by Hesse's research promotion programme LOEWE. The general Goal of said project is to develop organ-like three-dimensional cell aggregates represent versatile cellular models for drug development and toxicology assessment. There, he is interested in applying deep learning methods in combination with complex triangulated cell models to analyse the structure and growth of brain and liver tissue.
Prior to that, he received his M.Sc. degree in Theoretical Physics with focus on Quantum Computation and Quantum Inormation Processing from Technische Universität Darmstadt in 2021. His Masters Thesis was focusing on a novel method for optimal transport of atoms confined by a laser trap with non-trivial geometry.
His research topics includes supervised learning with deep neural networks, image analysis, growing neural networks, building realistic cell-models, simulation of heterogene cell aggregates in complex geometries and self-organising systems like the tile assembly model.
Completed Student Projects
Chewei Hsu (Master Thesis - coop. w. Aptiv) |
Hardware-aware Partially-Connected Differential Architecture Search in embedded Systems |
03/2023 |
Meng Yao (Master Thesis) |
Subpopulation Formation within the Active Brownian Particle Model | 01/2023 |
Roman Frels (Master Thesis) |
Combining Degenerative and Regenerative Methods forConvolutional Neural Networks |
12/2022 |
Jonas Kahl (Project Seminar) |
GradMax Approach: Generalization for 3D Convolutional Neural Networks | 08/2022 |
Simon Schmidt (Bachelor Thesis) |
Optimal Timing for Neuronal Growth within Artificial Neural Networks | 08/2022 |
Publications

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