My Work

Web Applications

I deal with all aspects of creating scalable and robust web applications and backends.

System architecture, information architecture, data modelling using relational and non-relational datastores, data processing, backend and web development using open source tools like Python and Django are my daily bread.

Typical applications involve:

  • Python and Django, Flask or tipfy web application development
  • Data modelling using relational and non-relational datastores (PostgreSQL, Riak, MongoDB, Redis, Solr, Hadoop and more)
  • Data processing, data mining, analytics and reporting
  • Targeting Google App Engine, Amazon Web Services and other cloud platforms
  • RESTful APIs definition and integration
  • Backends for mobile applications
  • Data retrieval and screen scraping
  • Social services integration
  • Website performance optimization
  • Browser extensions
  • HTML5, CoffeeScript, jQuery, Sass, Css Frameworks and media queries are my friends too

Business Applications

I help companies small and large to make most of their business.

I study workflows and find bottlenecks in processes. Then I create tools to help people focus on their job and perform their tasks more efficiently saving them from tedious repetitive tasks.

Typical applications involve:

  • Process automation
  • Document flow and management
  • Content and client management systems
  • Invoicing and document approval
  • Resource and process planning systems
  • Financial analysis applications
  • Domain specific languages
  • Seamless integration of Google Apps with web applications and Google App Engine
  • Google Marketplace and Gmail Contextual Gadgets applications
  • Google Apps Script automation

Scientific applications

I'm passionate about many things and one of them is applied science.

Data mining, machine learning, artificial intelligence, wavelet transforms, signal and image processing. All of these helps me create smarter and more functional applications for everyday use.

I have MSc degree in Software Engineering and Artificial Intelligence.

Typical applications involve:

  • Extracting information from big datasets
  • Solving classification and regression problems
  • Recommendation (collaborative filtering) systems
  • Signal and image denoising and enhancement
  • Feature extraction and pattern recognition
  • Data compression
  • Discrete and continous wavelet transform applications
  • Medical data processing
  • Financial data processing
  • Scientific computing with Python, Numpy and Cython

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