Seminario del Dr. Gilmer Valdes: «Lockout: Sparse Regularization of Neural Networks»

El próximo viernes 31 de marzo a las 15:30 en el salón 102 de Facultad de Ingeniería (UdelaR) se hará el seminario que dictará el Dr. Gilmer Valdes (University of California, San Francisco) .

La charla será en español


Dr. Valdes is an associate professor with appointments in the Departments of Radiation Oncology, Epidemiology and Biostatistics at UCSF and in the joint program in Computer and Precision Health between UCSF and UCB. After completing his doctoral training in medical physics at UCLA, Dr. Valdes completed a fellowship and clinical residency in Therapeutic Medical Physics at UPENN. His work during early training focused on development of machine learning algorithms and advanced modeling to predict patient outcomes, tailor treatments based on the type and quality of data available (particularly for prostate cancer patients), and more recently, on development of methods that permit inspection and interpretation of machine learning models (MediBoost, The Additive Tree, Expert Augmented Machine Learning, Lockout). Finally, he was fortunate to have been awarded an NI BIBK08 career award to support the development of accurate and interpretable machine learning algorithms for their application to medicine.

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