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Hi! I am a Ph.D. candidate at Brown University's Computer Science department. I am interested in databases, data management, data exploration and algorithms in general. Research topics include, but not limited to, query processing, storage management, data exploration and distributed processing. Currently I am doing research in novel data exploration techniques under supervision of Prof. Ugur Cetintemel and Prof. Stan Zdonik.


Searchlight is an interactive data exploration system for very large data sets. It is continuation of the Semantic Windows (SW) project. Users can search for window-like objects satisfying some interesting constraints on shape and content. The user can combine different constraints within a single query. For example, the user might ask for a time-interval having characteristics similar to the specified query interval (e.g., in terms of the pattern), and also having additional properties of its own (e.g., mean, variance, etc.).

Users can also search for groups of objects with inter-related properties, e.g., "windows with similar brightness" or "windows with the distance of 100km between each other". We call such queries "higher-order queries".

The system brings Constraint Programming (CP) techniques inside DBMSs. Data exploration is treated as a data-driven, online search problem, where CP machinery is used to quickly identify interesting solution candidates, and the DBMS efficiently validates them. Searchlight supports distributed computation, work balancing for both the CP-based search process and the validation, and dynamic distribution of resources between the two for better query execution times.

This framework is implemented by me in C++ as integration of an existing CP solver from OR-Tools into the query executor of SciDB, a popular open-source array DBMS. The implementation extensively reuses the existing distributed query execution infrastructure. At the same time it introduces its own layer of search-related capabilities, including dynamic search distribution, resource management and dynamic data distribution.

Semantic Windows

Semantic Windows (SW) is a novel interactive data exploration approach in which users query for multidimensional "windows" of interest via standard DBMS style queries enhanced with exploration constructs. Users can specify SWs using (i) shape-based properties, e.g., "identify all 3-by-3 windows", as well as (ii) aggregate content-based properties, e.g., "identify all windows in which the average brightness of stars exceeds 0.8". This SW approach enables the interactive processing of a host of useful exploratory queries that are difficult to express and optimize using standard DBMS techniques.

SW was implemented by me in C++ as a standalone client working with PostgreSQL via the standard driver. The client was written from scratch, including caching, network and distribution layers.

Sedna is a free native XML database which provides a full range of core database services: persistent storage, ACID transactions, security, indices, hot backup. Flexible XML processing facilities include W3C XQuery implementation, tight integration of XQuery with full-text search facilities and a node-level update language. Sedna project webpage

I participated in the project as a team member, making contributions into transaction processing, logging and recovery systems, version-based storage engine, XQuery parsing, static query optimization via query rewriting. Fully implemented the hot-backup subsystem and recovery testing system, based on controlled failures with random crashes. The work was mainly done in C++.


  • Current Ph.D. Candidate, Computer Science
    Brown University, Providence, RI
    Dissertation topicEnabling Integrated Search and Exploration over Large Multidimensional Data
  • May 2012 Master of Science, Computer Science
    Brown University, Providence, RI
    ThesisInteractive Data Exploration Using Semantic Windows
    GPA 4.0/4.0
  • June 2007 Bachelor of Science, Computer Science/Applied Math
    Lomonosov Moscow State University (MSU), Moscow, Russia
    Graduated with Honors
    Thesis Research and Development of Transaction Processing Methods Based on Snapshots
    GPA 4.97/5.0


  • September 2010 - Current Brown University
    Research Assistant, Data Management Research Group
    • Performing research in interactive data exploration for large data sets
    • Research and implementation of novel data exploration frameworks Searchlight and Semantic Windows
  • June 2015 - August 2015 HP Labs
    Research Associate Intern, Analytics Group
  • September 2012 - December 2012 Brown University
    Graduate Teaching Assistant, Database Management Systems Course
    • Consulting students, grading
    • Managing "Database Designer" project for designing an OLAP database using MySQL/Amazon EC2
  • July 2007 - July 2010 Institute for Systems Programming of the Russian Academy of Sciences (ISP RAS)
    R&D, Management of Data and Information Systems Group (MODIS)
    • Participated as a researcher and developer in Sedna (native XML DBMS) project
  • Program Committee Member
    • SYRCoDIS 2012, 2013, 2014

Download CV in pdf

Conference papers