Team

New Science Lab is an interdisciplinary team combining competencies in artificial intelligence, modeling and simulation, marine engineering, and product development, together with experience in deep-tech commercialization.

Sławomir Dudek

Business Strategy, Commercialization & Fundraising

Entrepreneur and manager with over 25 years of experience building, developing, and restructuring businesses at the intersection of technology, e-commerce, healthcare, and services. Combines a technical background — applied mathematics and technical physics — with management experience gained at Gillette Poland, Pelion, KPMG Advisory, Delfarma, Cefarm Białystok, and clinika.pl. At HullGen, responsible for business strategy, commercialization, partnership development, and preparing the project for financing and deployment.

Tomasz Pochylski

Business & Operations

Entrepreneur and technology project operator. Co-founder and former CEO of Bitfold — a hardware deep-tech project developed by a team of around 30 people, which raised nearly PLN 20 million in public funding and comparable private capital. Responsible for operational project management, execution structure, and the transition from prototype to a structured product.

Krzysztof Witek

Marine Industry & Commercial Development

Engineer with experience in ocean technology, product development, deployment, and working with industrial partners in the marine market. CEO of Raiton, where he develops projects related to hydrogen technologies, including autonomous watercraft. Responsible for relations with technology partners, research institutions, and investors, and brings a practical perspective on the market and HullGen applications.

Prof. Zbisław Tabor, PhD, DSc

AI & Research Lead

Professor at AGH University of Science and Technology in Kraków. AI researcher and practitioner with experience developing algorithms for industrial and medical applications. Specializes in machine learning, deep learning, computer vision, and model interpretability. Combines research and deployment competencies. At HullGen, responsible for AI layer development, research direction, and technical coherence of the solution.

Michał Sikorski

AI Developer

AI and robotics engineer with experience building machine learning models and applying them in technical and robotic systems. Works with Python, TensorFlow, PyTorch, OpenCV, and ROS. At HullGen, responsible for developing the implementation and algorithmic layer of the system, supporting the transition from model concept to working prototype.

Maksym Prykhodko

ML Integration & Rules Engine

Developer focused on Python and ML system integration. Builds systems where strict engineering rules meet generative AI — with experience in time-series data processing, signal filtering, and backend data analysis using PyTorch and FastAPI. In the project, responsible for the software layer enforcing design standards in the hull model.

Konrad Jojczyk

Engineering & Physics-Aware AI Lead

Graduate of the Institute of Computer Science at the Faculty of FTIMS, Lodz University of Technology, and a finalist of the Physics Olympiad. He brings 18 years of experience in software engineering, people management (Line Management), and coordinating multiple teams as a Tech Lead. He specializes in operationalizing artificial intelligence across every stage of the product lifecycle — from research, planning, and documentation automation, through advanced testing, to direct integration of AI models within application architecture. An expert in adapting to rapidly evolving technological trends. He is responsible for coordinating research and technical work, as well as the selection and formalization of the physical laws used to describe the behavior of generated shapes.

Mateusz Wiśniewski

Mathematical Modelling & AI Data

Graduate in mathematical modelling and data analysis. Focused on machine learning and data engineering. He designs and develops models and neural networks supporting research problem-solving, combining an analytical approach with practical AI deployment. He works primarily in the Python ecosystem, using technologies such as PyTorch, TensorFlow, scikit-learn, and OpenCV for data processing, model development, and results analysis. He is responsible for mathematical modelling, data engineering, selection and formalization of physical laws, and development of components supporting the evaluation and optimization of generated geometries.

Working methods

In our research and development work we use semi-autonomous AI agents that operate under the direction and supervision of our engineers. This allows a small, highly specialized team to run more threads in parallel than a typical team of this size. Every result that goes on to further work passes through a human — the agent accelerates, it does not decide.