Introduction to convolutional neural networks

Enzo Ferrante currently a CONICET researcher and AXA RF Fellow starting a new research line on computational methods for biomedical image analysis at the Research institute for signals, systems and computational intelligence (CONICET / Universidad Nacional del Litoral) in Santa Fe, Argentina.

In 2012 he received his Systems Engineering Degree from UNICEN University, Tandil, Argentina. In May 2016, he defended his PhD thesis in Computer Sciences, at the Université Paris-Saclay (CentraleSupeléc / INRIA) in France (Paris) where he worked on deformable registration of multimodal medical images under the supervision of Prof. Nikos Paragios.

[/dica_divi_carouselitem][dica_divi_carouselitem title=”Pablo Polosecki” sub_title=”IBM Thomas J. Watson Research CENTER, USA” button_url_new_window=”1″ image=”http://giambiagi2020.df.uba.ar/wp-content/uploads/sites/33/2020/09/Pablo_Polosecki-7.jpg” image_lightbox=”off” image_position=”image_left” image_size=”30%” _builder_version=”4.6.1″ _module_preset=”default”]

Introduction to computational neurology

Pablo Polosecki works at IBM Research since 2016. His research involves the development of predictive models of neurological and psychiatric disease from brain images.

He graduated with a MSc in Physics in 2008 from the University of Buenos Aires. He later completed his PhD in neuroscience at The Rockefeller University in 2015.

During his PhD, he combined functional MRI and electrophysiology to study the neural code for face processing and the control of visual attention.

[/dica_divi_carouselitem][dica_divi_carouselitem title=”Pablo Meyer” sub_title=”IBM Thomas J. Watson Research CENTER, USA” button_url_new_window=”1″ image=”http://giambiagi2020.df.uba.ar/wp-content/uploads/sites/33/2020/09/Meyer-Pablo.jpg” image_lightbox=”off” image_position=”image_left” image_size=”30%” _builder_version=”4.6.1″ _module_preset=”default”]

From molecules to humans, interpretable models in biology

Pablo Meyer Rojas graduated as physicist from Universidad Nacional Autónoma de México (UNAM). Afterwards, he obtained an interdisciplinary MsC in physics and biology from University of Paris.

He deepened his interests doing a PhD in biology at Rockefeller University in New York, working on circadian rhythms with Nobel Prize winner Michael W. Young. Currently he works at IBM’s Thomas J. Watson Research Center, in the computational biology division. His main interest is understanding how the level of single molecules and genetic circuits can determine mesoscopic phenomena such as cell death, circadian rhythms and olfactory perception.

[/dica_divi_carouselitem][dica_divi_carouselitem title=”Luis Moyano” sub_title=”CONICET, Instituto Balseiro, Universidad Nacional de Rio Negro” button_url_new_window=”1″ image=”http://giambiagi2020.df.uba.ar/wp-content/uploads/sites/33/2020/09/Luis-Moyano.jpg” image_lightbox=”off” image_position=”image_left” image_size=”30%” _builder_version=”4.6.1″ _module_preset=”default”]

Introduction to representation learning

Luis is adjunct researcher (CONICET) and professor at the Universidad Nacional de Río Negro. He obtained his masters degree at Instituto Balseiro (2000) and his Phd in Physics at Centro Brasileiro de Pesquisas Físicas-CBPF (2006, Rio de Janeiro). He was project leader at IBM Research (Rio de Janeiro), BBVA Innovación (Madrid) and Telefónica Research (Madrid).

His current research is at the intersection between physics and machine learning, including complex network representation learning with application to biological and social systems.

[/dica_divi_carouselitem][dica_divi_carouselitem title=”Cecilia Jarne” sub_title=”CONICET, Universidad Nacional de Quilmes” button_url_new_window=”1″ image=”http://giambiagi2020.df.uba.ar/wp-content/uploads/sites/33/2020/09/Cecilia-Jarne.jpg” image_lightbox=”off” image_position=”image_left” image_size=”30%” _builder_version=”4.6.1″ _module_preset=”default”]

Recurrent neural networks and dynamics

Cecilia studied physics at Universidad Nacional de La plata, where she also obtained her PhD degree. Until 2017 she was a postdoctoral researcher at the Instituto de Física de Buenos Aires. Since 2015 she is a professor at the Departamento de Ciencia y Tecnología de la Universidad de Quilmes and CONICET assistant researcher at the same institution.

She has authored research papers on Markov processes and signal analysis, being co-author in more than 40 papers from the Pierre Auger Collaboration. Her main research interests include stochastic processes, signal analysis, complex systems, recurrent neural networks, AI and scientific software development.

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