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Team/ Andrei/ Education/ GUAP — Saint Petersburg State University of Aerospace Instrumentation
Education · GUAP

Computer Science

University · Saint Petersburg, Russia

master Engineer Sep 2002 - Jan 2008
6y Duration
10 Subjects
11 Skills
8 Pre-Pro
GUAP
Institution Saint Petersburg State University of Aerospace Instrumentation Website
// OVERVIEW

My education in Saint Petersburg State University of Aerospace and Instrumentation provided a strong technical foundation in computer systems, programming, and security. I studied topics ranging from low-level development (C++, Assembly) to system modeling and computational theory, which shaped how I approach problem-solving and system design.

This education established a deep understanding of how systems operate at different levels — from hardware-near logic to higher-level abstractions — supporting a structured approach to architecture and development.

As part of my thesis, I developed a secure macOS-based communication system, exploring real-time interaction and secure networking — an early step into building complex, real-world applications.

A key part of my growth, however, came from self-education. At the time, resources were limited, especially for macOS development, which pushed me to rely on English documentation, experimentation, and continuous learning.

This experience built a long-term habit of independently acquiring knowledge, which continues to shape how I approach new technologies, frameworks, and development methodologies today.

// CREDENTIAL
Level master
Field Computer Science
Title Engineer
Major Computers, complexes, systems and networks
Diploma ВСГ 1140109
Reg. No. 59346
// THESIS

Secure Video Conference Platform for macOS

Developed a secure video conferencing application for macOS using Objective-C. Implemented H.264 video codec integration and TCP/IP networking for real-time communication with encryption.

video-communication
objective-ch264-codectcp-ipmacos
// KEY SUBJECTS

System Development Methodologies

Foundation for understanding enterprise software development

software architecturedesign patternssdlc

Computer Networks

Basis for socket programming and real-time communication apps

tcp ipnetwork protocolsdistributed systems

Programming Languages

Low-level understanding for performance optimization

c languagecppasmalgorithms

Cryptography and Security

Foundation for security-focused development (thesis topic)

encryptionsecure communicationauthentication

Digital Signal Processing

Applied in Shopster ultrasound detection project

signal processingfourier transformfiltering

Operating Systems

Foundation for understanding iOS/macOS internals and system-level programming

process managementmemory managementkernel architecturefilesystems

Database Theory

Basis for PostgreSQL schema design and normalized data modeling

relational algebranormalizationquery optimizationtransaction isolation

Discrete Mathematics

Foundation for algorithm design and data structure selection

graph theorycombinatoricsformal logicset theory

Computer Architecture

Validates "computers, complexes, systems and networks" major and IoT/hardware projects

processor designmemory hierarchybus architectureembedded systems

Software Engineering

Foundation for technical leadership, team mentoring, and SDLC governance

project managementrequirements engineeringquality assuranceteam organization
// KNOWLEDGE & LANGUAGES
// KNOWLEDGE
UMLNetworkingEncryptionSecurityState Machines
// LANGUAGES
CC++ASMPascalPythonDelphi
// PRE-PROFESSIONAL FOUNDATIONS

Programming experience before and during university, before professional career

BASIC (ZX Spectrum) ~1992-1995 First programming on ZX Spectrum clone — game logic, text adventures
Pascal ~1995-1997 Algorithmic programming, school and early university courses
Delphi ~1997-2000 Visual application development, RAD tooling
FoxPro ~1997-1999 Database programming and reporting
VBA ~1998-2000 Office automation and macro development
C / Visual C++ ~1998-2002 Systems programming at university, Win32 API
Assembly (x86) ~1999-2001 Low-level hardware programming, processor architecture labs
Linux Administration ~2000-2002 Server setup, shell scripting, network services
// SELF EDUCATION

A structured approach to continuous learning and knowledge building.

In addition to formal education, I continuously develop my skills through technical literature, research, and hands-on experimentation.

A significant part of my expertise comes from continuous self-education, driven by real-world problems and evolving technologies.

This includes topics such as algorithms, system design, software architecture, and development methodologies like Agile, Extreme Programming, and Feature-Driven Development. Books on design patterns, testing, and structured engineering practices have significantly influenced how I approach system design and code quality.

I also rely on official documentation, engineering talks, and technical communities as ongoing sources of knowledge, integrating relevant insights into practical development processes.

// LEARNING APPROACH

First-principles learning from authoritative sources

books Technical books as primary learning source — original texts, not tutorials
official_documentation Apple Developer docs, Go docs, MDN, language specifications
conference_sessions Apple WWDC sessions for iOS/macOS platform knowledge
peer_learning Knowledge sharing with experienced colleagues and senior engineers
references RFCs, official manuals, language specifications, API references

No iOS or platform certifications. Deep understanding comes from primary

sources — original books, official documentation, WWDC sessions, and

knowledge sharing with experienced engineers. This first-principles

approach builds deeper understanding than certification-driven learning.

// CERTIFICATIONS

Staying current with AI, LLMs, and modern development practices.

Alongside practical experience, I actively pursue certifications to stay aligned with modern technologies and evolving best practices — particularly in AI, LLMs, and software development workflows.

This includes certifications from providers such as Anthropic, as well as ongoing programs in areas like deep learning and applied AI. These complement hands-on work by reinforcing structured knowledge and validating current approaches.

Rather than standalone achievements, these certifications are integrated into my workflow and continuously applied in real projects and experimentation.

View all certifications →
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