Daniel Törtei Email & Phone Number

Abu Dhabi, United Arab Emirates

Responsible for developing of the visual perception stack for aerial drones in GPS-denied environments: - custom relative localization, use of state-of-the-art visual-inertial solutions - custom global localization (US Patent Application No. 18/766,823), use of state-of-the-art visual- and multi-spectral deep learning solutions Built and led a diverse visual localization team consisting of software engineers and research engineers. Directed R&D efforts with external collaborators from NYU, USA. Interacted with project stakeholders.

New York, United States

Deep learning (CNN) for visual perception and human action recognition in retail:- Human pose estimation and keypoints based tracking (OpenVINO, Hungarian algorithm)- Video Transformer Network architecture fine-tuning and transfer learning with PytorchResponsibilities: custom dataset and annotation process conception and management, coding of preprocessing and postprocessing logic in Python and interfacing with Amazon AWS

Established and led administration of a Venture Capital start-up. Managed and led deep learning projects for external clients and in-house. Recruited and mentored software engineers for computer vision tasks:- SSD object detection framework for retail semantics, applying transfer learning on Tensorflow models (MobileNetV2, Neural Architecture Search network), data mining and data analysis- machine perception with ORB keypoints detection- internal hardware development of human fall detector using Raspbian and Raspberry Pi sensors coupled with Intel NCS

France

Improving online localization accuracy of a road user within a dynamic map in the scope of Road Database Client project. Multiple View Reconstruction based numerical optimization on relative position of the in-vehicle camera. Matlab based POCs and evaluation vs an RTK-GPS ground truth.Development in Visual Studio 2010.

Toulouse Area, France

Spartan6 (slx25) FPGA based integration of Xilinx's video IPs for image scaling operations. A microblaze-centered design. On-the-fly reconfiguration of the FPGA.Input video format: Aptina 960p25. Output videos (both in parallel on slx25 device): 720p50 and 576i50. Development kit used: Xilinx ISE 14.7.Xilinx video IPs: video I/O to AXI stream, video Scaler, video DMA and video Timing Controller.Reconfiguration: ICAP primitive w/ multiboot Flash.Debug: ChipScope and Oscilloscope.

Toulouse Area, France

Development of real-time SLAM SoPC architecture on an FPGA in context of navigation in aeronautics and mobile robotics. Development of embedded software and hardware architectures for real-time obstacle detection in the context of navigation in ADAS and mobile robotics.

Toulouse Area, France

Hardware development of floating-point matrix multiplication accelerator on Xilinx Virtex5 FPGAFish-eye camera calibrationMulti-threading of a C application

Novi Sad, Serbia

Development of Java/Matlab application with Marmitek X10 domotics microcontroller

Belgrade, Serbia

PLC programming in ST languageWriting scripts in Ruby, Excel

Doctor Of Philosophy (Ph.D.), Embedded Systems And Robotics

Joint PhD with University of Novi Sad, Serbia. Embedded systems prototyping, implementation and validation by using algorithm-architecture.

Master Of Science (Msc), Automation And Industrial Informatics

Final year of master's/engineering degree program at ENSEEIHT (Ecole Nationale Supérieure d'Electrotechnique, d'Electronique.

Master’S Degree, Electrical Engineering And Computer Science

Bachelor’S Degree, Electrical Engineering And Computer Science

Baccalaureate, Physics