Videos of AI Ukraine 2018
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About the conference
AI Ukraine is the biggest Ukrainian conference on practical usage of Data Science, Machine Learning, Big Data and Artificial Intelligence. It is a professional forum for meeting peers, sharing experiences and discussing the current issues in the fields.
Conference brought together technical specialists, researchers, managers, entrepreneurs and everyone who was interested in learning new AI and Big Data trends and research, real use cases and technical knowledge.
I already worked on a wide range of challenging applications: Speech processing (audio signals), Handwriting recognition (images), Document classification, Natural Language Processing (text) and
misc. projects involving other type of data, including sequential data, and mixtures of numerical and categorical data. My satisfaction is to make state-of-the-art technology work "in the wild" on real problems.
I am also concerned by the impact on society of the application for which I am contributing.
My dream would be to implement Machine Learning in a company that has contribution to environmental sustainability.
Sergiy has 10+ years of consulting experience in data science. He was responsible for multiple solutions across sectors, focusing on gauging and addressing Customer needs through big data and advanced algorithms. Specifically, Sergiy led individual customer-level solutions for product recommendations, store and product category performance measurement, operationalization monitoring, optimization solutions, large scale image recognition applications, and other projects. He is known for his outcome oriented approach and ability to bring techniques from Digital and Technology sectors to other domains, in addition to his extensive data science network and applied experience.
He received his BSc in Applied Math from University of Toronto and his PhD in Statistics from Harvard University, where after graduation he also developed and taught a graduate course in Parallel Statistical Computing and Interactive Visualization as a Lecturer.
Master degree in Computer Science, with specialized knowledge in machine learning, deep learning, pattern recognition, and feature engineering.
Development of machine learning techniques for biomedical signal analysis. Various projects include: • deep learning for biosignal processing • GANs for noise filtering • Biological age prediction using heart data •drowsiness detection of drivers using ECG
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