At Apheris we enable enterprises to collaborate and analyse data securely — without compromising privacy. Our privacy-preserving data ecosystem are built upon cutting-edge technologies and cryptographic techniques created by a team of world-class researchers at the intersection of data privacy, cryptography and computational sciences.

Various projects with focus on Digitalization and Internet of Things in Chemical and Industrial Goods companies:• Lead incubation of IoT predictive maintenance product covering full IoT range from sensors to cloud connectivity & machine learning analytics models combined with user interface and underlying business model• Lead commercialization of IoT product including market push and technical professionalization of product• Lead modules on digital customer experience and new digitally enabled business models• Developed digitalization strategy along digital journey• Developed new startup venture concepts in innovation sprint with BCG Digital Ventures• Developed a Go-To-Market strategy for a new digital business unit• Developed a growth strategy for a sensor components & solutions provider• Developed data processing and data analysis module (Python) for warranty spend reduction programme with BCG GAMMA

• Developed data processing and analysis software for terabyte scale imaging data (from neutron & X-Ray sources), leveraging the Python data science & machine learning tech stack (NumPy, SciPy, scikit-learn, Numba) as well as Matlab• Contributed to open source numerical simulation package OpenPNM (github.com/pmeal/openpnm, https://ieeexplore.ieee.org/document/7478437), a package for performing pore network modeling of porous media • Conducted numerical simulation studies and compared simulation results with experimental output from processed and analysed imaging data• Leveraged these insights to optimize porous media components for water electrolysis with regard to efficiency and cost for usage in a Power-To-Gas process to store fluctuating renewable electricity from wind and solar• Planned and acquired research projects with industry partners (e.g. with SIEMENS) and coordinated project setup (work packages, time, resource and budget planning) with project partners• Lead project teams for work packages and supervised several student master theses

• Developed data analysis tool for time series data of feed-in of renewable energies into the power grid - analyzing correlations between actual feed-ins at the EEX with feed-in predictions• Developed trading strategies for electricity trading from time-series data analysis

Work conducted at Fraunhofer Institute for Physical Measurement Techniques (IPM):• Developed optically tunable terahertz metamaterial filters and lenses leveraging numerical simulations of electromagnetic wave propagation based on finite element method (FEM) and finite difference time domain (FDTD) methods• Fabricated microstructures using cleanroom-based processes of micro technology• Characterized the fabricated devices using Terahertz-Time Domain Spectroscopy (TDS)

• Developed, validated and implemented a software tool with underlying mathematical models (using MATLAB) for simulating cleaning processes and analyzing the impact of detergents in these processes• Developed user interface for end users to this tool and tested and improved it with users

• Transfer of production processes from R&D in photovoltaic cells to production• Planning of experimental trials using the Design of Experiment statistical method