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General Information
| Full Name | Joanna Marks |
| Languages | Polish, English, German |
| Contact | joanna.marks23@imperial.ac.uk |
Education
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2024-now PhD in Statistics and Machine Learning
Imperial College London and University of Oxford, UK - Under the supervision of Deniz Akyildiz and Riccardo Passeggeri
- Investigating the interplay between Optimal Transport (OT) and generative modeling, with a focus on latent variable models. Currently working with Gabriel Rioux on developing a novel, scalable algorithm for Gromov-Wasserstein distance computation to align complex probability spaces.
- Fully funded within the EPSRC Center for Doctoral Training in Statistics and Machine Learning (StatML CDT).
- Completed doctoral-level modules in Deep Learning, Advanced Bayesian Methods, Statistical Inference, and Causal Inference.
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2023-2024 MSc. in Statistics
Imperial College London, UK - Bona Fide Scholarship (Competitive scholarship awarded to top Polish students to partially fund their studies).
- Thesis project supervised by Ed Cohen on "Mean-field limits for discrete-time Hawkes processes on homogeneous and inhomogeneous graph structures."
- Modules included: Deep Learning, Machine Learning, Advanced Simulation Methods, and Bayesian Methods.
- Graduated with Distinction.
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2020 - 2023 BSc. in Mathematics
University of Warwick, UK - Second-year project on modelling football match results.
- Modules included: Probability Theory, Markov Processes, Stochastic Processes, and Statistical Inference.
- Graduated with First Class Honours.
Work Experience
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2024 - 2025 Quantitative Analyst (Part-time)
Amelco UK, London, UK - Helped develop Python-based pricing models for basketball pre-match markets, incorporating team and player strength, pace, and efficiency.
- Helped develop a time-series library for fitting custom state-space models using JAX.
- Worked with traders and product teams to translate model outputs into market prices, sanity checks, and risk controls; created diagnostics to monitor model performance.
Research Experience
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2023 The Mary Lister McCammon Summer Research Fellow
Imperial College London, Department of Mathematics, London, UK - Developed a stochastic model to simulate the development of cancer cells in a joint system with lymphocyte cells.
- Introduced an interaction matrix into the stochastic model to account for interactions between cancer cells and lymphocyte cells.
- Collaborated with an MSc student to compare the stochastic model with an analogous continuous model.
- Worked as part of a cohort of fourteen fellows, participated in science communication training, and presented the research to a broad audience.
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2022 Research Intern
University of Oxford, Department of Statistics, Oxford, UK - Developed and implemented a mixed additive model in Python to assess pass difficulty and estimate the passing ability of a football player.
- Worked under the supervision of Professor Christl Donnelly and PhD candidate Matthew Penn.
- Conducted independent research, implemented it on real-world data, and contributed to pre-match reports for Oxford City Football Club.
- Research was mentioned in Nature [link].
- An article based on the model was published in Significance, the Royal Statistical Society's magazine: [link].
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2023 Undergraduate Research Support Scheme
University of Warwick, Department of Statistics, Coventry, UK - Developed a mid-season table for the Polish volleyball league, accounting for the strength of each opponent played.
- Worked under the supervision of Dr. Nick Tawn and Professor David Firth.
Teaching Experience
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2025-now Teaching Assistant
Imperial College London, Department of Mathematics, UK - Taught an MSc level course - Methods for Data Science (which inludes topics on regression, clustering, neural networks and dimensionality reduction techniques)
Other Interests
- Running, CrossFit, Reading, Sports fan (tennis and volleyball in particular)