Alek Fröhlich

Computational Statistics and Machine Learning

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Ph.D. Student,

CSML, Italian Institute of Technology (IIT),

Genoa, Italy.

I am a first year ELLIS Ph.D. student at the Italian Institute of Technology under the supervision of Massimiliano Pontil (CSML) and Karim Lounici (École Polytechnique).

I am broadly interested on bridging machine learning and medicine, where data is often scarce, models are commonly misspecified, and confounding factors abound. On the theoretical side, my interests lie in causality, uncertainty quantification, and developing rigorous guarantees for machine learning algorithms. On the applied side, I have been using machine learning and statistics to explore the vast amount of information contained in hematoxylin and eosin whole slide images and improving decision-making in clinical settings, particularly breast cancer care.

selected publications

2024

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    PersonalizedUS: Interpretable Breast Cancer Risk Assessment with Local Coverage Uncertainty Quantification
    Alek Fröhlich, Thiago Ramos, Gustavo Cabello, and 3 more authors
    2024
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    Machine learning can reliably predict malignancy of breast lesions based on clinical and ultrasonographic features
    Isabela Carlotti Buzatto, Sarah Abud Recife, Licerio Miguel, and 7 more authors
    Breast Cancer Research and Treatment, Jul 2024
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    Elements of learning theory and their application in the prediction of malignancy of breast lesions
    Master Thesis
    Jul 2024

2023

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    Computational pathology pipeline enables quantification of intratumor heterogeneity and tumor-infiltrating lymphocyte score
    Daniel Tiezzi, Alek Fröhlich, Stefano Pagnotta, and 1 more author
    Dec 2023

2022

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    Foundations of machine learning: functional analysis with an eye to kernel methods
    Bachelor Thesis
    Mar 2022