Probabilistic modeling
Graphical models
Deep learning
Bayesian decision theory
Data cleaning & visualization (pandas, matplotlib, seaborn, folium)
Statistical hypothesis testing (scipy.stats, statsmodels)
Clustering, regression, decision trees, SVMs, cross-validation, etc. (scikit-learn, RankLib)
Recommendation engines (collaborative filtering, truncated SVD)
Convolutional neural networks (Keras)
Probabilistic modeling (pymc, pyflux)
Time-series analysis (pyflux, arch)
NoSQL and SQL databases (Elasticsearch, Yandex Clickhouse, PostgreSQL, MySQL)
Elastic stack (Filebeat, Logstash, Elasticsearch)
Apache Kafka, Strimzi.io, Apache Spark (structured streaming)
Docker, docker-compose, OpenShift (OKD)
Amazon AWS
Monitoring (Prometheus, Grafana), GitLab CI/CD
python, scala, ruby
With the goals of quantifying the road-network coverage in OpenStreetMaps and improving it, convolutional neural networks (CNNs) were trained to identify roads in aerial imagery. A python package was coded on top of Keras/Tensorflow, integrating the communication with mapping services, image pre-processing, training and validation of CNNs, as well as predictions on trained models.
Analytic data, logged to local disk in the VMs of backend services, was read with Filebeat and streamed to Logstash, where each JSON was validated by a custom plugin. Clean data was then passed on to Kafka, where Spark (structured streaming) was used to enrich it with geo-spatial information in real time. Finally, Yandex Clickhouse served as a data-lake with Apache Superset providing self-service access.
With POI data stored in Elasticsearch, the aim was to improve the ranking of location search results displayed in mobile clients by machine-learning from customer app-usage. A python package was coded from scratch to explore and define features, to handle communication with Elasticsearch and its RankLib plugin, to upload trained models and search templates, and to graphically/statistically compare models.
To visualize and query discrete events as supply and demand that varies smoothly and continuously as a function of space and time, a computationally efficient algorithm for density estimation based on orthogonal polynomials was formulated and implemented in python, using process-based parallelization.
Consulting a major ride-hailing venture on data science and data infrastructure
Design, implementation, deployment, tuning, and maintenance of lambda-architecture data platform
Real-time streaming data enrichment with geo-spatial information
Convolutional neural networks for road-network extraction from aerial imagery
Interactive framework for machine-learned ranking POI full-text search results
Highly parallel orthogonal-polynomial density estimation for real-time supply/demand analytics
Hiring and recruitment
Principal investigtor in research projects on computational materials modeling
Scientific computing on own HPC resources
Budget responsability for independently raised third-party funding (ca. € 1 Mio.)
Personnel responsability and supervision of doctoral theses
Consulting industrial partners
Managerial duties (collaborative research center, hiring committees)
Lectures at the Department of Physics (amongst others, on Computational Physics)
Design of elementary building blocks for molecular electronics
Code development (fortran) and optimization (blas/lapack)
Functionalization and optimization of materials and interfaces for organic solar cells
Organization and scripting of multi-tiered copmuter-simulation processes
Solving mixture models on spectral data from laboratory experiments
Prototyping quantum-mechanical models in python
Quantum-chemical simulations of molecular semiconductors
Eigenmode analysis of molecular vibrations in Mathematica
Numerical solution of non-linear differential equations
Data retrieval with sliding-window Fourier transformation
Regression analysis of X-ray diffraction patterns
PhD thesis: Structure and Optical Response of Conjugated Molecules
graduation with honors
MSc thesis: High Pressure Studies on the Structure and Optical Properties of Poly(para-Phenylene) Based Systems
graduation with honors
ERASMUS exchange in Grenoble, France
graduation with honors
Physics student's representative body at Humboldt-Universität zu Berlin
Category fundamental science
State of Styria, Austria
European Commission
Austrian Science Foundation (FWF)
For scientific journals such as Nature Nanotechnolgy, Nature Communications, Physical Review Letters, or Advanced Materials
On conference such as Optical Probes, International Conference on Synthetic Metals, or PyData Berlin
For funding agencies, e.g., Deutsche Forschungsgemeinschaft (DFG) or Department of Energy (USA)
Special Issue 13 of Advanced Functional Materials, vol. 25 (2015)
Symposium O at the Spring Meeting of the European Materials Research Society (E-MRS) in Lille, France
Symposium J at the Spring Meeting of the European Materials Research Society (E-MRS) in Strasbourg, France
38 talks at international scientific conferences such as the ICSM, MRS, ECME among others in China, USA, Japan, Italy or Switzerland
20 invited guest lectures, among others at the University of Groningen (Netherlands) or the Weizmann Institute of Science (Israel)
You have questions?