Hi! I am Alex Doumanoglou, a researcher in Computer Vision and Machine Learning and an outstanding software engineer. Here you may find what I do best when it comes to my profession.
I am a researcher in computer vision and machine learning with exceptional software development skills that allow me to quickly turn research ideas to fully working prototypes. I am self-motivated, problem solving oriented, with strong can-do attitude and extremely fond of developing solutions for complex problems. I am interested in getting involved in product oriented challenging projects that target high quality standards.
Technologies used: Unity3D, C#, ZeroFormatter, Zenject, UniRx, C++17, boost, amqpcpp, rxcpp, docker, Excel VBA.
Worked as a software architecture consultant and developer, bringing experience on software design patterns and good practices for code re-usability, debugging and maintainability to a development team of 4 individuals.
Technologies used: C#, WPF, MVVM Light, XAML
Technologies used: (OOP) MATLAB
Technologies used: C++, C++/CLI, C#, OpenGL, Ogre, RealXtend, Unity3D, OpenNI, Microsoft Kinect SDK, PCL, OpenCV, boost, eigen, cgal, VTK, FFTW, Qt, CUDA.
Developed a multi-view capturing software that could be used to calibrate a multi-view color camera setup, including intrinsic and extrinsic parameters and perform multi-view recording and playback. The software was developed in C++/CLI with OpenCV and boost and supported an arbitrary number of camera devices.
Developed a Computer Aided Design (CAD) Control to be used with the Microsoft .NET Framework, oriented for land surveying engineers.
Technologies used: .NET Framework (C# & VB.NET), SlimDX.
Extended the desktop software ERP used by a language school by adding support for manual and automated SMS sending to students and/or their guardians and automating the production of finance and other statistical reports concerning the school’s operation.
Technologies used: Delphi, ADO, SQL.
Developed algorithms in C programming language for improving the performance of a speech recognition system (powered by CMU sphinx) in noisy environments. Key elements include a voice activation detection module and adaptive background noise filters. The software developed was targeting a portable device running Windows CE.
The acoustic radar utilized a microphone array for audio signal capturing and via digital signal processing it identified the direction of the incoming audio, giving an estimate for the location of the audio source. Two signal processing algorithms were implemented: beamforming and Time Delay of Arrival (TDOA) via waveform correlation. Moreover, the radar's software was able to perform audio source recognition utilizing pattern recognition techniques. Involved in design and construction of 3 printed circuit boards (PCBs), developed software in C for Texas Instruments’ TMS320C6711 DSP and user interface software for the PC connected to the PCBs in C++/CLI.
Tools used: Orcad, P-SPICE, MultiSim, AltiumDXP
Developed simulations in order to determine bit error rates for signal transmission over wireless and satellite channels. Studied error correction codes. Algorithms were developed in C and MATLAB.