🦀 Alex Shvets

Alex Shvets has a strong background in machine learning and research. 🦀 Alex is currently working as a Machine Learning Engineer at Zephyr AI starting in 2023. Prior to this, they held the position of Sr. Applied Scientist at Microsoft from 2021 to 2023. Alex also worked at ShareThis as a Sr. Machine Learning Engineer from 2019 to 2021, where they developed and productized NLP web services for similarity search and recommendations. Before that, they worked as a Machine Learning Engineer at Instrumental Inc. from 2018 to 2019, where they developed end-to-end machine learning solutions and engineered evaluation frameworks for reproducibility issues. Alex gained research experience at the Massachusetts Institute of Technology as a Research Scientist from 2016 to 2018, focusing on ML/DL algorithms for medical and satellite image applications. 🦀 Alex also worked as a Research Scientist at Rice University from 2014 to 2016, where they designed algorithms and applied machine learning techniques to analyze experimental data. At the beginning of their career, Alex worked as a Software Engineer at the Russian Research Center "Kurchatov Institute" from 2009 to 2010. Overall, Alex has a diverse background in machine learning, research, and software engineering.

Alex Shvets received a Ph.D. in Computational Physics from the University of Strasbourg between 2010 and 2014. Prior to that, they earned a Master's Degree in Applied Mathematics and Physics from the National Research Nuclear University MEPhI (Moscow Engineering Physics Institute) from 2007 to 2009, and a Bachelor's Degree in the same field from the same institution from 2003 to 2007.

In terms of additional certifications, Alex completed several online courses and programs. They obtained certificates in topics such as Convolutional Neural Networks, Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization, Neural Networks and Deep Learning, and Structuring Machine Learning Projects from Coursera Course Certificates in 2017. They also completed a course in Machine Learning from Coursera Course Certificates in 2017. Additionally, Alex earned certifications in Statistics in Medicine from Stanford University in 2016, and Introduction to Probability - The Science of Uncertainty from edX in 2016, among others. They completed various courses in fields such as Neural Networks, Statistical Learning, and Biology Meets Programming: Bioinformatics for Beginners.