Founder and CEO of TCR App Mobility — an ML-based deep tech startup from the area of road traffic safety and presymptomatic medical diagnostics (website, pitch deck, video presentation).

 

Over 9 years of experience in the development and commercialization of innovative solutions, gained during cooperation with stakeholders from 17 countries on 4 continents. Over 6 years of experience in the field of artificial intelligence (e.g., ANNs, deep learning, data mining), proven by successful validation and real-world implementation of advanced mathematical models.

 

Finalist of prestigious (domestic and international) startup competitions, conventions and festivals. Participant of distinguished business acceleration programs (e.g., Creative Destruction Lab AI Stream, INSEAD AI Venture Lab, Polish Development Fund's School of Pioneers). Exhibitor at more than 20 global tech conferences (e.g., MWC Barcelona, GITEX Dubai, South Summit Madrid, Salon des Inventions Geneva).

 

Seasoned machine learning engineer with extensive experience in physics, mathematics and data analysis. Award-winning architect of deep neural networks and multi-modal probabilistic algorithms with practical market application.​

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RESEARCH

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ML-based prediction of road traffic accidents caused by tiredness and inattention (2021–2023)

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TCR App Mobility’s mathematical models are based on two-year scientific research with novel findings about human cognition. It combined VR simulations (with non-invasive functional neuroimaging), real-world testing and neuroscience-related experiments. Each tester was equipped with our mobile application for a few weeks before entering a driving simulator with EEG, fNIRS and eye monitoring sensors. This workflow allowed us to precisely label attention lapses, correlating actual brain activity with physiological signals and behavioural anomalies. Our research sample encompasses individuals from diverse demographic backgrounds, covering a broad range of driving experiences and lifestyles. TCR App Mobility is implemented as a fully autonomous mobile application (agentic AI) with a proprietary data flywheel and a unique multi-modal dataset of digital biomarkers (focused on attention stability and high-dimensional health phenotypes).

 

Presymptomatic medical diagnostics on the basis of subtle driving anomalies (since 2025)

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Our ML-based algorithms are able to detect disease-specific changes in driving habits that are characteristic of chronic medical disorders (e.g., neurodegenerative diseases, as well as non-neurological conditions like diabetes and arthritis) years before the onset of clinical symptoms. For example, in the case of Parkinson’s, we focus our data labelling on multi-modal indicators of prodromal neurophysiological decline and sub-clinical motor impairment (reflected in behavioural anomalies like erratic steering or delayed reactions). By incorporating these unique patterns into our training workflow, we are able to identify driving behaviour shifts associated with presymptomatic Parkinson’s disease. TCR App Diagnostics translates complex neurophysiological impairments into measurable driving micro-corrections, embedding a clinical-grade tool in a consumer-grade device. We are turning the world’s road infrastructure into a neurological screening lab — identifying Parkinson’s disease a few years before the first tremor, using solely a smartphone.

 

Personalization of foreign language learning materials on the basis of eye behaviour and face expression analysis (2023–2024)

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Our mathematical model has integrated both convolutional neural networks and Transformers. At the beginning, biometric data (eye movement, pupil dilation, blinking traits, face expressions) were collected as testers engaged with diverse learning materials. The dataset was labelled on the basis of learning outcomes (like task performance or retention rates). The CNN is used to extract memory-related parameters from eye-tracking and face expression observations, capturing visual indicators of optimal cognitive engagement. Meanwhile, the Transformer is employed to handle temporal dependencies (modelling how they evolve over time), reflecting dynamic changes in effectiveness of knowledge acquisition. The combined CNN–Transformer architecture was trained with participation of volunteers from varied demographic backgrounds. Following this, the model was validated on a separate dataset to assess its generalization ability.​

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NOTABLE DISTINCTIONS

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With TCR App Mobility

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Acceptance into Creative Destruction Lab AI Stream (San Sebastian, 2025/26)​

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Graduation from INSEAD AI Venture Lab (2025)

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Top 16 Polish startups (including Top 3 Polish startups from the sector of modern economy) at the 16th European Economic Congress (2024)

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Top 20 European startups at Infoshare Contest (2024)

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Classification among Deep Tech Pioneers by Hello Tomorrow (2024)

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Top 20 startups at Mobileheroes Global (2024 and 2025)

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Top 25 startups at OIST Innovation Accelerator (2024)

 

With other startups

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Top 16 Polish startups (including Top 4 Polish startups from the sector of business processes) at the 17th European Economic Congress (2025)

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Winner of the 7th Edition of the Polish Development Fund’s School of Pioneers (2024)​

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EXPERTISE AND RESPONSIBILITIES

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Artificial intelligence

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Deep neural networks (e.g., RNNs, CNNs, PNNs, Transformers), machine learning (supervised, unsupervised, reinforcement), generative AI, RAG, MCP, fine-tuning, LLMs, agentic AI

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Data science

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Data mining, statistics, data processing, cloud computing (AWS, GCP), data structures, data visualization, data transmission, data architecture design​

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Software development

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C/C++, Python (e.g., PyTorch, TensorFlow, Matplotlib, NumPy, SciPy, scikit-learn), mobile applications (Flutter), web platforms (Django), vibe coding (e.g., Lovable, Cursor, Windsurf), workflow automation and deployment (n8n, Vercel)

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Mathematical modelling

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Algorithm development, analysis, testing and reviews

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Scientific research​

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Data analysis, research planning, documentation

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Business

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Startup management, business presentation, technology validation, marketing, pilots, customer acquisition, venture incubation/acceleration, fundraising