Speakers

Ariel Rokem

Data Scientist, The University of Washington eScience Institute

Trained in cognitive neuroscience (PhD: UC Berkeley, 2010) and computational neuroimaging (Postdoc, Stanford, 2011-2015), Ariel Rokem is now a data scientist at the University of Washington eScience Institute, where he continues to develop software for the analysis of human neuroimaging data, develops tools for reproducible and open research practices, and collaborates with researchers from a variety of fields to advance data-intensive research.

http://arokem.org

Ariel Rokem

Fatma (Imamoglu) Deniz

Data Scientist, Helen Wills Neuroscience Institute, BIDS, UCB

Fatma Deniz is a data science fellow at the Berkeley Institute for Data Science, a postdoctoral researcher UC Berkeley’s Helen Wills Neuroscience Institute and the International Computer Science Institute. She is interested in how sensory information is encoded in the brain and uses machine learning approaches to fit computational models to large-scale brain data acquired using functional magnetic resonance imaging (fMRI). In addition, she works on improving internet security applications using knowledge gained from cognitive neuroscience (MooneyAuth Project: https://www.mooneyauth.org). She is a passionate teacher, coder, baker, and cello player.

Fatma Deniz

Chris Holdgraf

Data Scientist, Helen Wills Neuroscience Institute, BIDS, UCB

Chris is a graduate student in Bob Knight’s cognitive neuroscience laboratory. He uses applied statistics and machine learning to study the brain, utilizing encoding and decoding models of electrophysiology signals to study how our experience with the auditory world affects the way that we process sounds. He’s a regular contributor to the MNE-python project for MEG and EEG data analysis in Python and to a handful of tools in the scientific python ecosystem. Chris believes strongly in the importance of teaching, communicating science, and connecting with the non-academic world. He’s interested in the practice of teaching data analysis, statistics, and programming to scientists and is exploring ways to improve these practices in undergraduate and graduate education. He’s involved in the Berkeley Data Science Education Program, assisting faculty in preparing courses for the Data 8 undergraduate course in data science.

Chris Holdgraf

Maryana Alegro

Computer Scientist, Grinberg Lab, Memory and Aging Center, Dept. of Neurology, UCSF

Maryana Alegro is a computer scientist who received her MS and PhD in electrical engineering from the University of São Paulo Polytechnic School. Her major experience is in medical image processing, especially MRI and histological images and, more recently, polarized light imaging. She is currently a post-doc at the UCSF Grinberg Lab where she is responsible for writing image-processing tools that can assist researchers in studying dementia. She also has strong experience as an enterprise software developer, having worked on the development of several medical systems for the Brazilian government.

Maryana Alegro

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