I am a machine learning and AI research scientist with 5 years of industrial software engineering experience. I work in the area of machine learning, data mining, analytics, and visualization. Areas of my expertise include software development, systems engineering, machine learning and AI research. I am proficient with large-scale data processing frameworks (Spark, Hadoop), graph databases (Neo4J), data visualization tools (D3, Gephi), and machine learning frameworks and libraries (TensorFlow, PyTorch, Sklearn).
In December 2020, I have defended my PhD thesis on data mining and pattern detection algorithms for large-scale dynamic networks. The thesis covers such topics as graph machine learning, attention mechanisms in neural networks, anomaly detection in dynamic networks, knowledge graphs, and applications to social network analysis and collective behavior.
Take a look at some of my projects and tutorials on my blog.