Dr. Tobias Reitmaier

Head of SW project management: Disciplinary leadership of the excellence pool for SW project management (25 employees). Process Management & Optimization: Exploring the use of new technologies for streamlining of SW management processes. Competence management: Ensuring and promoting the employee development with help of regular employee appraisals (GPD, TAR). Project Staffing: Responsible that all SW projects are equipped with the requested competencies and capacities. Hiring of new SW project managers.

Management of a complex SW project (including topics like autonomous driving and cyber security) for one major OEM in an international setup (more than 45 developers). Customer interface and internal contact person for all SW relevant topics. Ensuring all project goals considering scope, budget and time from the acquisition phase to the SOP. Controlling & monitoring of SW changes in respect to the V-model and quality standards. Ensure the compliance and maintenance of the ASPICE and ISO26262 processes

Test Management within the SW project for one major OEM: Coordinating all testing and approval activities. Evaluation of all SW problems. Performing the acquisition for a new SW project including evaluation and clarification of all SW specifications regarding technical feasibility with customer. Supporting of the SW project management for another major OEM: Getting familiar with SW project management. Taking over proto SW releases and proto SW approvals. Active participation in weekly customer meetings.

Third-party funding: elaborating an application for a research unit by the DFG (German Research Foundation) that establish new research directions in the field of collaborative, interactive learning systems in open-ended environments. Shared management of the working group Organic Computing: it consists of four research associates and several student assistants. Managing of several PhD students particularly in the field of Big Data.

Setting up a framework: developing of a Java framework, which includes a variety of machine learning techniques, within a team. Teaching activities: lab exercises for lectures Real-Time Systems (C-programming based on PandaBoards and QNX) and Data Mining (Java-programming based on RapidMiner). Holding the lecture Real-Time Systems and designing the internship IES (construction and C-programming of Asuro robots). Management activities: taking over of key tasks during the development phase of the department.

Auto-CO2-Pass: project work for developing an intelligent evaluation software for a soot sensor (Continental AG). Preprocessing of the measurement data, implementation of a SVR based solution, and memory optimization of the trained SVR. OPTASENS: project work in the field of deflectometry for developing a high-precision measuring technique (accuracy of 40 nanometers) for reflective optical surfaces (with diameter of 800 mm). Optimization of the calibration process and carrying out of a feasibility study.

Research work in the field of advanced machine learning in order to combine the advantages of discriminative and generative modeling techniques. Third-party funding: Elaborating an DFG proposal relating to active learning. Teaching activities: Led Soft Computing lab exercises.

Active Learning, Machine Learning, Semi-supervised Learning, Unsupervised Learning, Probabilistic Modeling, Gaussian Mixture Models, Discriminative Modeling, Support Vector Machines, Graph-based Modeling, Clustering

Fundamentals of Computer Sciences, Software-Engineering, Realtime Systems, Soft Computing, Computational Geometry, Lineare Algebra, Analysis, Numerical Mathematics, Parallel Programming

Major Field of Studies: Soft Computing, Pattern Recognition, Data Mining, Computer Architecture, Realtime Systems, Computational Geometry, Algorithmics, Efficient Algorithms, Graph Drawing, Fundamentals of Digital Image and Signal Processing; Minor Field of Studies: Informatics in Medicine