Narek Hovhannisyan

AIGenie is a group of AI-powered analytical solutions as a part of a cloud-native SaaS observability platform called Wavefront. As a Java back-end developer, I designed and developed modern, performance-crucial systems that provided insight into time-series data. I worked closely with front-end and data science teams to support the development from idea to release. The system collects data from key-value value storage using a stream processing approach invented at Google and effectively applies developed algorithms to achieve a reasonable outcome. I provided the front-end team with reliable and convenient REST API endpoints to trigger the algorithms mentioned above. As a result, several US patents and articles were published in the sphere of time-series forecasting and anomaly detection.

For published papers, please see https://scholar.google.com/citations?user=o3T4ahEAAAAJ.

A fully virtual computer infrastructure that can compile, link, load, execute and debug a simple, functional programming language. I have designed and developed this system with my university peer using mainly C++. The simple programming language is first compiled into an assembly code which is then executed inside the virtual machine allowing some simple debugging operations, such as step in, step out, step over, and breakpoint. The system virtualizes all major parts of the computer infrastructure, from CPU registers to memory.

A parser for advanced mathematical expressions represented in TeX format. The parser was able to parse advanced elements like integrals, logarithms, sums, and list operations. Moreover, it was able to parse expressions containing nested and recursive functions. It was designed and implemented using the complex abstract syntax tree (AST) by my colleague and me. This system is currently a part of a modern fintech solution.