My Projects
Understanding physical systems, from stellar objects to biological cells, picks my interest and fascinates me! I love understanding how complex phenomena can be “captured” through equations with the ultimate goal of appropriately modeling them and thus foresee their behavior!
I have experience in developing benchmarking frameworks for bioinformatics and AI-driven biomedical research, with an emphasis on reproducibility, validation and reliable decision-making. Here are some of the projects I have been involved in or explored so far.
Gravitational wave surrogate modeling
Deep Learning methods in surrogate modeling of gravitational waveforms.
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Synthetic data for variant calling benchmarking
Framework for generating synthetic genomics datasets for benchmarking tumor-only somatic variant callers.
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Synthetic data evaluation metrics
ELIXIR-led scoping review on evaluation metrics for synthetic data across genomics, transcriptomics, proteomics, phenomics, imaging and electronic health records.
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LLM evaluation for reproducible AI reporting
Benchmarking LLM-generated AI method annotations against expert human-curated annotations to evaluate reproducibility and reporting quality in life science AI publications.
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