Prisca Dotti
👋 Hi, I’m Prisca, a machine learning scientist and bioinformatician passionate about applying mathematical and computational methods to solve complex problems in biology and medicine.
I hold a PhD in Biomedical Engineering (University of Bern) and an MSc in Mathematics (EPFL). Currently, I work as a Data Analyst at the SIB Swiss Institute of Bioinformatics, where I design and evaluate ML/AI strategies for genomic datasets.
My research and work experience bridge deep learning, mathematics, and biomedical sciences, with a focus on:
- AI-driven biomedical imaging (3D U-Net, CNNs, GNNs)
- Imaging and genomic data analysis and feature selection
- Reproducible workflows and collaborative open science
- Interdisciplinary projects between computational and biological domains
Research Highlights
- Deep learning for subcellular calcium imaging
Developed the first AI-driven framework for detection, segmentation, and classification of Ca²⁺ release events in cardiac cells.- 📄 Published as first author in Cell Calcium (2024)
- 📂 Open dataset on Zenodo
- 💻 GitHub Repositories:
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International collaborations
Visiting Research Scientist at the University of Melbourne, validating deep learning models with synthetic data and mechanistic models. - Open-source contributions
Contributor to PAGEpy, a bioinformatics package for genomic feature selection and classification.
Publications
- Prisca Dotti et al. (2024).
A deep learning-based approach for efficient detection and classification of local Ca²⁺ release events in full-frame confocal imaging.
Cell Calcium. DOI link
Conferences
- ESC Working Group on Cardiac Cellular Electrophysiology – Toledo, Spain (2022)
- Biophysical Society Annual Meeting – San Diego, USA (2023)
- German Physiological Society – Berlin, Germany (2023)
- Bern Data Science Day – Bern, Switzerland (2023)
Beyond Research
Outside research, I am committed to inclusion and accessibility. Since 2012, I’ve volunteered with the Ticino Association of Parents and Friends of Children in Need of Special Education, leading inclusive camps for neurodiverse youth.
Skills
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🖥️ Programming & Tools
Python (PyTorch, TensorFlow, scikit-learn, SciPy, pandas, scikit-image,
PyTorch Geometric, matplotlib, seaborn), Git, ImageJ, Slurm (HPC), Bash/CLI, working knowledge of C++, R, and MATLAB -
📊 Data Science & AI
Deep learning, machine learning, reinforcement learning, feature extraction,
model development, pipeline implementation, quantitative analysis, data visualization -
🧬 Bioinformatics & Computational Biology
Genomic data processing, image analysis, confocal microscopy -
➗ Mathematics
Mathematical analysis, topology, statistics, algorithm design,
linear algebra, graph theory, signal processing -
🌍 Languages
Italian (native), English (fluent), French (fluent), German (intermediate)