André Sekulla

Data Driven Applications for Autonomous Driving

project lead - it-security for sme energy suppliers Research interest: - Blockchain-based Collaboration - HCI for Blockchain - Human-Centered Machine Learning; [since 10/2018:] - phd student at DFG Graduiertenkolleg 'Locating Media' - University of Siegen - http://www.locatingmedia.uni-siegen.de - Promotionsprojekt: Blockchainbasierte Kollaboration

A real-time communication tool for the gastronomy and their customers. The gastronomy can directly communicate and generate content in one of three categories. With snapptime the gastronom gets the chance to stand out from other gastronomes and bring their customers back into their own local. To get the discount, the customer just needs to show the offer within the snapptime-app. The gastronomy can use the CMS for creating content, but also to get feedback on their content by analyzed data.

Getting to know the basics of Data Exploration and Machine Learning. Find different ways for visualization of data. Compare Machine Learning approaches and focus on one algorithm for the load forecasting. Using Deep Learning, a LSTM neural network, to forecast the load time series (error between three to five percent on an average time series).

Student Assistant at the Chair of Microsystems. - Tutoring the practical hardware course during the summer semesters ('13, '14, '15) [Embedded C, VHDL, Microcontroller, FPGA, Basics of electrical engineering] - Tutoring the computer architecture exercise during the summer semester '14

Working in the research project ARAMIS. Distribution of C-functions from a single-core to a multi-core embedded system. Developing new algorithms and new ways in the software architecture AUTOSAR for the distribution of software functions.

Mikrosystementwurf, Embedded Systems; Thesis: Data Science, Machine Learning, Deep Learning

Mathematik; Thesis: Verteilung von C-Funktionen auf ein Multicore-Steuergerät unter Beachtung des AUTOSAR Standards