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Anton Solomko, PhD, has a diverse work experience in the fields of data science, mathematical finance, and dynamical systems. Anton is currently employed as a Senior Data Scientist at Envelop Risk, where they develop and deploys probabilistic machine learning models to quantify cyber risks. Additionally, they conduct research on cyber catastrophe and systemic risk modeling.

Prior to their current role, Anton worked as a Data Scientist at Envelop Risk, where they were involved in developing machine learning algorithms for event detection to assess companies' reputation risks based on global media and social posts.

Anton has also held academic positions, including Visiting Professor at Scuola Normale Superiore and Researcher (External Collaborator) at UniCredit & Scuola Normale Superiore. In these roles, they conducted research on topics such as deterministic-stochastic systemic risk models, dynamics and ergodic properties, and applications of dynamical systems techniques to mathematical finance. Anton used quantitative, statistical, and machine learning approaches to solve analytical problems and build models.

Anton's earlier work experience includes roles as a Data Science Intern at Polecat Intelligenceā„¢, where they conducted research on machine learning algorithms for event detection and fine-tuned geotagging algorithms. Anton also developed and maintained a test automation framework.

Anton has a strong academic background, having worked as a Visiting Researcher at Scuola Normale Superiore and as a Postdoctoral Researcher at the University of Bristol. During these positions, Anton conducted research on topics such as dynamical systems, stochastic processes, and ergodic theory, resulting in publications in leading mathematical journals.

Anton's early career started as a Junior Researcher at the ILTPE - B.Verkin Institute for Low Temperature Physics and Engineering of the NAS of Ukraine. In this role, they focused on research in ergodic theory and spectral theory of dynamical systems. Anton also designed and taught courses at Kharkiv National University and organized scientific summer schools for students.

Anton Solomko, PhD, obtained their Doctor of Philosophy - PhD in Mathematics from the National Academy of Sciences of Ukraine. Anton completed this degree from 2009 to 2013. Prior to that, they earned a Master of Science - MS in Mathematics and Computer Science from V. N. Karazin Kharkiv National University from 2008 to 2009. Before their Master's degree, they completed their Bachelor of Science - BS in Mathematics and Computer Science from the same university from 2004 to 2008.

In addition to their formal education, Anton Solomko has also obtained various certifications. Anton completed the TensorFlow in Practice Specialization, Convolutional Neural Networks in TensorFlow, Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning, Natural Language Processing in TensorFlow, and Sequences, Time Series and Prediction courses through Coursera, obtaining the certifications in the year 2020. Anton also completed the Deep Learning Specialization, Sequence Models, Convolutional Neural Networks, Structuring Machine Learning Projects, Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization, and Neural Networks and Deep Learning courses from Coursera in the year 2019. Prior to that, in 2016, they obtained the Introduction to Machine Learning certification from the National Research University ā€” Higher School of Economics & Yandex School of Data Analysis. Furthermore, in 2014, they obtained the FCE - Council of Europe Level B2 certification from Cambridge English Language Assessment.