I'm driven by the passion to merge engineering with business strategy, crafting innovative solutions that tackle some of the toughest challenges out there. With a solid background in AI, full-stack development, and strategic business planning, I've had the privilege of co-founding startups and leading projects that blend technology with market demands. My curiosity extends beyond just the commercial aspects—I'm equally fascinated by the scientific advancements that redefine what's possible. Right now, I'm diving into opportunities that seamlessly integrate engineering, business, and research to spark innovation and deliver impactful results.

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Delving deep into the core fundamentals of computing, because sometimes the most 'basic' things are deceptively complex. Here are some projects where I strip everything down to the bare metal to understand how things really work:

• rustylox - My own interpreter for the Lox language, crafted in Rust, inspired by the Crafting Interpreters book. Also provides live playground.
• CoreLox - Reimplementation of Lox as bytecode-based virtual machine, written from scratch in C. While RustyLox brought Lox to life in Rust, CoreLox strips it down to its essentials—minimalist, efficient, and purpose-driven. This is Lox interpretation, closer to the metal.
• torchlet - A neural network library influenced by Andrej Karpathy's Micrograd, extended to integrate seamlessly with PyTorch. Includes essential optimizations and C extensions for heavy computations via Cython.
• grep - A reimagined take on the classic regex matching tool, built from scratch with handcrafted regex logic.

Artificial Intelligence is a constant in my work, and I've tackled numerous applications in both proprietary and personal projects. Here are a few of my personal ventures:

• KANwise: Implementation of Kolmogorov–Arnold Networks (KANs) in PyTorch with a Keras-like interface, based on the KAN paper.

• torchlet: A full neural network library inspired by Andrej Karpathy's Micrograd, extended with PyTorch integration and optimized using Cython.

• Speech2Text: A FastAPI-based Speech-to-Text API using OpenAI’s Whisper for transcription. Features user tracking and support for REST/WebSocket requests.

I'm a big fan of GPU acceleration, and I've worked on several projects that leverage the power of NVIDIA CUDA for high-performance computing. Here are a few examples:

• CUDA-NPP-EdgeDetection - A GPU-accelerated edge detection pipeline using both a custom Sobel filter implemented in CUDA and the highly optimized NVIDIA NPP library.

• hamming-one: CUDA-optimized, massively parallelized Hamming one algorithm in ( O(n * l) ) amortized time complexity for finding the closest string in a set of binary strings.

• kmeans-clustering: K-Means Clustering with both GPU (CUDA) and CPU implementations. Introduces several compiler level optimizations such as loop unrolling via templated kernel functions.

• electrostatic-simulation - Implementation of a CUDA-accelerated simulation of an electrostatic field with visualized particles (protons and electrons) in a 2D space. The simulation is capable of displaying the electrostatic field, showing particle interactions, and visualizing these in real time at 30 FPS or higher.

During my time at the Warsaw University of Technology, I’ve worked on some exciting and challenging projects. Here's a sneak peek:

• Flight Application: A comprehensive flight data management system for my OOD course. The project demonstrates parsing, serializing, and deserializing flight data using a console interface, and includes multiple modules such as FlightDataParser, NetworkDataParser, and FlightDataGUI for managing and visualizing data.

• Battleships Game: A fully functional Battleship game written in WinAPI as part of my PiGE course. Classic game, modern code. Well, maybe not totally modern, given that it's WinAPI...

• ADS (Algorithms and Data Structures): A collection of algorithm and data structure implementations in C++. This is my go-to reference for brushing up on fundamentals and a learning resource for others.

Not everything has to be serious! Here are some projects I work on for fun or experimentation:

• Genom Motif Analyzer: A simple, yet elegant tool for identifying, analyzing, and visualizing DNA motifs in genome sequences using BioPython.

• graphs-isomorphism: A Python project for checking isomorphism in simple, undirected graphs. Includes a neat visualization tool using PyVis.

• AdventOfCode2023: My solutions to Advent of Code 2023. I'm learning Go in the process but may switch to C, C++, or Python when things get tricky (or when I feel adventurous).

• C-projects: A collection of early C projects from my first semester. This is where it all began, and I keep it around to see how far I’ve come.

• LinkedIn

I'm always on the lookout for the next big challenge, so if you've got an interesting project or idea, let's connect! I'm particularly excited about projects that push the envelope in AI, software development, and where these intersect with business strategy.