Dipl.-Ing. Meisam Ashraf

I-GOS is a startup company in the information technology sector initiated by Max Plank institute and DLR under ICARUS initiative. Nature of the work is ' internet of things'. My responsibilities: - Algorithm development for embedded software (C++, Python, Octave, gawk, bash) - Conceptual system design for service and operation - Database development for user data center (PostgreSQL)

Resman is a fast growing startup with national awards for innovations. I was in charge of software solutions owning the in-house software used to provide the technical service to the client. My responsibilities: - Product management (Atlassian) - Supervising the in-house and third party developers (Qt, C++ Mingw, git) - Mathematical flow modeling multiphase laminar and turbulent flow (COMSOL, Matlab) - Business development, discovering new markets, sales technical support

As a PhD researcher, I worked in the Mathematics department. About half of the research was performed in collaboration with SIMTECH group in Stuttgart. The project (MATMORA) involved development of mathematical solutions for uncertainty and risk quantification. My responsibilities: - Define the uncertainty in the input data to the model - Perform simulation of flow in porous media (Eclipse Reservoir Simulator, MRST) - Perform non-parametric statistical sensitivity and risk analysis (Matlab, Python)

Schlumberger is the largest intentional oil service company. I worked in offices in Iran (Tehran, Ahwaz) and UK (Oxford) as software support engineer. My main responsibilities: - Work with developers and users to reflect the user requirements in the release - Software test and support - Conducting training courses, presentations and workshops. I worked closely with research and technology centers in UK and Moscow.

Pre-trained models available in the OpenVINO Model Optimizer Inference Engine Handling input streams Processing model outputs The lightweight MQTT architecture

Logistic regression Analyze A/B test Data wrangling Data visualization

Lidar obstacle detection Autonomous driving computer vision Radar Range-Doppler estimation Lidar, camera and radar fusion via Kalman filter

Latest techniques in Deep learning are covered (Pytorch - Tensorflow): Convolutional Neural Networks, Recurrent Neural Networks, Generative Adversarial Networks.

Skills acquired: - Statistical non-parametric modeling - Scientific numerical calculation - Functional and numerical analysis

The major topic is modeling of flow in porous media. The application is in the oil and gas reservoir developments field.

Computational Fluids Dynamics (CFD), Scientific Computations and programming, Aerodynamics,Propulsion systems, Airborne structures, Aircraft Design