Denys Korzh

- Research and development of Computer Vision algorithms in C++, OpenCV; - Prototyping in Python of pose estimation algorithms; - Working with fiducial markers including ArUco Markers.

- Developing in C++ new image processing features and improving existing ones of different Brainlab products including SmartBrush and SmartBrush Angio; - Using Perforce as the main version control system; - Using Agile techniques for organisation of the working processes.

- Implementation of new features for Photogrammetry and 3D-Reconstruction software in C++; - Implementing Bundle adjustment algorithms based on flat markers; - Extensive use of OpenCV, Eigen and PCL libraries.

- Implementation of Topology Optimization Constraints for NX Nastran in C++; - Improvement of the performance in Model Order Reduction Code in Python; - Implementation of the new material model for OpenFOAM in C++.

- Implementation and GPU (CUDA) acceleration of the Finite Volume CFD solver; - Implementation of the new boundary conditions for the smoothed-particle hydrodynamics code developed on CUDA; - CUDA code optimization; - Creating of new features using C++; - Benchmarking and validation.

- Benchmarking of the highly parallelizable MPI based code to find the optimal grid distribution between different processor units in the software for simulation of cavitational flows and prediction of the cavitation-induced erosion.

- Integration of the MATLAB simulated Heat Transfer data through the lookup table into LabVIEW based controller of the metan valve for Rocket Combustion Chambers.

- Software Development in C++ and MPI for Peano (Framework for PDE Solvers on Spacetree Grids); - Developing of the compression scheme for particle simulation in Peano.

The program covers a wide range of subjects and research areas, including numerical analysis, computer science, scientific computing and diverse applications like computational physics, computational fluid dynamics, visualization, machine learning, and many more.

Solid-state physics studies how the large-scale properties of solid materials result from their atomic-scale properties. Thus, solid-state physics forms the theoretical basis of materials science. It also has direct applications, for example in the technology of transistors and semiconductors.