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PhD in Computer Science and Engineering

University of Minnesota, Minneapolis, MN

• Thesis: Dynamic Bayesian Networks - Estimation, Inference and Applications
• Advisor: Prof. Arindam Banerjee

MS in Computer Science

University of Colorado, Boulder, CO

BS in Computer Science

Dnipro National University, Dnipro, Ukraine

Research Staff Member

IBM Research, Yorktown Heights, NY

Research Assistant

University of Minnesota, Minneapolis, MN

Data Scientist

NASA Ames Research Center, Mountain View, CA

Software Developer

Cisco Systems, Boulder, CO

A broad class of machine learning algorithms that focuses on understanding the underlying data distribution and generate new samples with statistical properties similar to the original dataset.

Forward protein design predicts the structure and function of a protein based on its amino acid sequence, while the inverse design estimates a protein sequence with a desired structure and function.

Automatic extraction of structured representations from text data, involving identifying entities, disambiguating their meanings, and mapping them to a graph-based representation for efficient storage, retrieval, and reasoning.

The task of transforming the style or tone of a given text while preserving its semantic meaning and structure.

The task of analyzing the visual content of an image and generating a coherent and textual description that accurately describes the content of an image.

Information theoretic view of neural networks analyzing their properties to gain understanding on how they represent and process information, as well as for designing efficient architectures.

The task of identifying patterns that deviate from the expected behavior of a system or dataset.