Education

Doctoral Candidate in Computer Science — University of Wrocław, 2020–Present Developing novel AI models for time series analysis and anomaly detection. Research spans probabilistic AI, nonparametric Bayesian methods, and dynamical systems.

M.Sc. in Mathematics — University of Wrocław, 2018–2020 Thesis: Applying probabilistic modeling in ultra high-frequency trading. Applied HMM-based models to predict mid-price change with accuracy competing with SoTA.

M.Sc. in Computer Science — University of Wrocław, 2018–2020 Thesis: Novel architectures for mid-price change in LOB, based on DeepLOB. Tested TCN, GRU, Transformers for ultra high-frequency trading.

B.Sc. in Mathematics — University of Wrocław, 2015–2018 Thesis: Theoretical properties of the game of cops and robbers on graphs.

B.Sc. in Computer Science — University of Wrocław, 2015–2018 Thesis: Applying SVM models in ultra-high frequency trading.

Experience

Founder — Consulting Mikołaj Słupiński, Wrocław, Feb 2026–Present ML/AI consulting — bringing research-grade solutions to production.

Technical Researcher — RTB House, Feb 2026–Present Research at the intersection of deep learning and real-time bidding systems.

Research and Teaching Assistant — University of Wrocław, Oct 2024–Present Research in statistical learning, self-supervised learning, representation learning, and Bayesian statistics.

Lead Data Scientist — QuantUp Sp. z o.o., Wrocław, Sep 2025–Jan 2026

  • Owned end-to-end development of Herodotus AI chatbot
  • Led AI strategy across client projects
  • Established engineering standards for production-grade ML
  • Mentored junior data scientists

Data Scientist — QuantUp Sp. z o.o., Wrocław, Aug 2024–Sep 2025

  • Built end-to-end ML pipelines: data acquisition, feature engineering, model training, deployment
  • Developed deep learning and statistical models for forecasting and optimization

Stipendist — University of Wrocław, Oct 2021–Jun 2024 OPUS-18 “Learning Latent Data Structure from Observations” research project. Focus on learning dynamical models with latent Markovian structure.

Visiting Researcher — GEOMAR Helmholtz-Zentrum für Ozeanforschung, Kiel, Germany, Nov 2022–Jan 2023 Time-series prediction and anomaly detection for environmental monitoring.

Software Developer — Opera Software ASA, Wrocław, Jul 2021–Dec 2021 Development of Opera Mini Browser, data visualization, user behavior analysis.

Data Scientist — NavAlgo (now Pathway), Wrocław, Nov 2019–Jun 2021 Anomaly detection models from research to production. CI/CD infrastructure with Jenkins.

Engineering Intern — Microsoft, Berlin, Jul 2019–Sep 2019 Deployed neural network models to production on mobile devices using TensorFlow Lite.

Engineering Intern — Opera Software ASA, Wrocław, Jul 2017–Sep 2017 Opera Mini browser for Android.

Awards & Grants

  • 2024 — PLGrid computational grant (plgmarkov)
  • 2024 — Stipend from cosmose.ai for training Polish team at IOAI
  • 2022 — Helmholtz Visiting Researcher Grant
  • 2021 — 2nd place, best student paper in applied mathematics (Polish Mathematical Society)
  • 2020 — Faculty award for best master’s thesis in Mathematics
  • 2018–2019 — Rector’s scholarship for best students
  • 2016–2017 — Rector’s scholarship for best students

Technical Skills

  • AI/ML: PyTorch, TensorFlow/TFLite, scikit-learn, Deep Learning, PGMs, Bayesian Inference, Time Series, Anomaly Detection
  • Data: Pandas, NumPy, Data Pipelines, Feature Engineering, SQL
  • Production: Python, Docker, AWS, CI/CD, Git, Linux, REST APIs
  • Research: Rapid prototyping, literature review, experiment design, technical writing

Languages

  • Polish — Native
  • English — Advanced (conversationally fluent)

Summer Schools

  • 2022 — Oxford Machine Learning Summer School
  • 2021 — Nordic Probabilistic AI School (ProbAI)
  • 2021 — 4th Int. Summer School on Deep Learning