My scope of interests and I'm good in these: machine learning, computer vision, mathematical modeling, algorithms, pattern recognition, signal processing, data mining, GRID. Throughout my experience, I worked (invited) in several interesting projects (mostly in area of machine learning): • 2009: "Simulation of the emitted electrons in the substance (low-temperature plasma)" for the collider of heavy particles in collaboration with the Moscow Institute of Physics and Technology. As provided by the physical model was developed an algorithm implemented as a visual simulation model. Subsequently, the algorithm has been scaled and translated to computing on video cards in order to achieve statistical significance, and confirm the results. • 2011: Project in the field of intelligent transportation systems (Laboratory at Kajaani/Oulu, Finland): authentic 3D driving simulator, environments for simulation (3d cities, tracks), and behavior measurement. My task in this project is to develop the algorithm for driver's fatigue estimation by means of telemetry and signals, which are preprocessed by biomedical team. • 2012-Now: "Classification of skin lesions’ images (malignant melanoma)" [see above, NST], Visualization and classification of problems of brain signals registration (ERBS, tensor magic) [Narvik], synthetic projects, counseling laboratory of DSP (NArFU) and so on. [P.S.: I've reached the successful or made a significant contribution to all projects] To summarize my experience (especially in machine learning), you must have strong analytical skills, deep understanding of the subject area, the ability to understand the business processes. The theory is often far removed from practice, knowledge of standard algorithms and problems can be almost useless. The key point is the data, data mining and feature engineering(!), appropriate statistics analysis and understanding of workflow in each chain of the pipeline. In half of the projects I have come when some work has already been done (sometimes it's been years), people just did a lot of machine learning and came to a standstill, making strange conclusions. It should as far as possible to analyze the situation from different angles, find interconnections, and detect patterns. I possess dynamic thinking, wide area of thought, meticulous attention to detail. I can quickly grasp and analyze information from different sources, which allows me to manage multiple projects simultaneously and the current situation. I like to solve complex problems, hypothesize and draw conclusions, communicate, listen, and make presentations. My main programming languages and development tools: • MATLAB (Octave) It allows you to concentrate on the task and quickly implement prototypes of algorithms, oblivious to memory management, garbage collection, etc. • C++ (less C, Qt) • Python, R • SQL and PL/SQL, ABAP Objects Also used : Java, C# (+ ASP.NET), Ruby. I worked primarily with Oracle databases (less : MongoDB, PostgreSQL, MySQL). Used VSC: Git, Mercurial; Project management software: JIRA, Redmine, Bitrix24.