Personal Portfolio

AI engineering ambition backed by strong software fundamentals.

I’m Tymofii Kalnytskyi, a Computer Science & Artificial Intelligence student at Adelphi University with a 3.9 GPA, building full-stack AI products, developer tools, and polished interfaces. My work combines technical depth, clean execution, and a strong focus on real product quality.

3.9 GPA Computer Science & Artificial Intelligence
20+ Students Mentored in AI and web development
100+ Hours Project-based fellowship training
Selected Work

Projects selected to show technical range, product sense, and execution quality.

See all projects
AI Product

MemoryChat

A full-stack chatbot experience built around locally hosted inference, multi-turn memory, and a custom interaction layer designed to feel fast, readable, and production-minded.

Next.js TypeScript LLM
AI Engineering

AI Bug Finder

A code intelligence tool that combines AST-based static analysis with machine learning to detect risky Python patterns and prioritize issues by likely severity.

Python FastAPI Scikit-learn
Database Systems

CircuitRacer Data Model

Designed and iterated a Formula-1-inspired relational schema, incorporating instructor feedback around derived attributes, relationship paths, and composite-key correctness.

SQL ERD Data Modeling
Project Spotlight

Switch between projects to see what each one proves.

What it proves

MemoryChat shows that I can build AI products as systems, not just demos: local model integration, conversation state decisions, TypeScript architecture, and a custom interface that feels intentional.

Technical Toolkit

Tools and systems I use to build end-to-end work.

  • Languages: Python, Java, C, C++, JavaScript, TypeScript, SQL, R, HTML5, CSS3
  • AI and ML: LLMs, NLP, Scikit-learn, Logistic Regression, feature engineering, Ollama, FastAPI
  • Full-stack tools: React, Next.js, Node.js, Flask, PostgreSQL, Docker, Git, Linux
  • Design and delivery: Figma, Adobe Creative Suite, responsive UI systems, and REST APIs
Current Direction

Focused on AI, product engineering, and clear execution.

I’m most interested in building practical AI products, strong application backends, and interfaces that feel as intentional as the systems behind them.

The through-line across my work is simple: make the technical core strong, make the product experience clear, and make the final result feel finished.

Experience

Recent experience that shaped how I build and communicate.

The Knowledge House

Delivered instruction in AI, React, JavaScript, HTML, and CSS while mentoring 20+ students.

Software Fellowship

Completed 100+ hours of project-based instruction and presented product ideas to 25+ funders.

ITGenio

Built full-stack applications and educational games across Python, SQL, JavaScript, C++, and Java.

Execution Style

Moves comfortably between teaching, product thinking, implementation, and systems-level problem solving.

About

More on how I think, learn, and approach engineering work.

Beyond the projects themselves, I care about clarity, fast iteration, and building things that feel complete. The about page goes deeper into the mindset behind the work.

Read About Me
Contact

Open to internship and early-career engineering opportunities.

I’m interested in internships and early-career AI Engineer or Software Engineer roles where strong implementation quality, product thinking, and technical rigor all matter.