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 ondata 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 myblog.

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1. anomaly-detectionanomaly-detectionPublic

   Anomaly detection in time-series networks. Spatio-temporal Anomaly Detection

   Jupyter Notebook 12 1

2. epfl-lts2/sparkwikiepfl-lts2/sparkwikiPublic

   Scala 57 8

3. WikiBrainWikiBrainPublic

   Studying collective memories of internet users using Wikipedia viewership statistics

   Jupyter Notebook 27 5

4. SparkTestSparkTestPublic

   Sample of a Spark Scala project in Intellij Idea

   Scala 8 11

5. my-first-bindermy-first-binderPublic

   MyBinder workshop

   Jupyter Notebook 1

6. 20news_dynamics20news_dynamicsPublic

   Clustering 20news dataset using graphs and Hebbian Learning

   Scala 1 1