Machine learning and computer vision researcher with an established track record of building successful customer applications. Passionate about developing new solutions in domains such as image/video analysis, augmented reality (AR), finance, recommendation engines, and data mining.
Availability: Available in 15 days
Position: Lead, Project Manager, Advisor
Experienced Physical Data Scientist with diverse industry experience in sensors and actuators, algorithm design for the telecommunications industry and defense, university education and research centers. Professional expertise includes design and measurement systems on prototypes, microelectronic, data analysis, artificial intelligence, software and hardware test and measurements.
KNOWLEDGE BASE:Math, Statistic and optimization, Control system design and Analysis, Signal processing and communications, image processing and computer vision, nuclear Magnetic resonance, image processing, Test and measurement, Computational finance, mapping , GPS, GIS, Computational Biology, Code generation, Code verification, Application deployment, database connectivity and reporting, simulation graphics and visualization, Machine learning, Neural nets, Deep Learning, Swarm intelligence.
TECHNOLOGY STACK: Deep learning with Theano as a compiler for mathematical expressions in Python that combines NumPy’s syntax with the speed of optimized native machine language. Composes mathematical expressions in a high-level description that mimics NumPy’s syntax and semantics, while being statically typed and functional (as opposed to imperative). These expressions allow Theano to provide symbolic differentiation. Before performing computation, Theano optimizes the choice of expressions, translates them into C++ (or CUDA for GPU), compiles them into dynamically loaded Python modules, all automatically. Common machine learning algorithms implemented with Theano are from 1.6× to 7.5× faster than competitive alternatives (including those implemented with C/C++, NumPy/SciPy and MATLAB) when compiled for the CPU and between 6.5× and 44× faster when compiled for the GPU. All this technology is applied in GIS (Geografical Information Systems) with optimized augmented reality systems for image processing and navigation Systems.
Project Term: 01/2016 - 04/2017
Industry: Aeronautical & Satellite equipment services, Geographical Information Systems, Augmented Reality Vision
Role: Research advisor development
Description coming soon.
Description coming soon.