If You Could Read My Mind…
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Elisabeth-Herz-Kremenak-Saal
Plenary
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in englischer SpracheEtliche Wissenschaftler arbeiten mittels Visualisierungstools und Computermodellen daran, die komplexen Vorgänge des Gehirns darzustellen und zu verstehen. Ziel dieser Methoden ist es, z.B. Krankheiten oder Therapieerfolge vorhersagen zu können. Aber lassen sich damit künftig auch visuelle Bilder oder gar Gedanken und Erinnerungen aus unserem Hirn auslesen?
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MA Josh CHARTIER
Ph.D. Candidate, Chang Lab, University of California San Francisco
| 2010-2014 | Student Electrical Engineering, Rice University, Houston, TX |
| 2011-2012 | Undergraduate Researcher, The Dabaghian Lab, Baylor College of Medicine; Rice Unversity, Houston, TX |
| 2012 | Amgen Scholar, Laboratory for Intelligent Imaging and Neural Computation, Columbia University, New York, NY |
| 2012-2014 | Undergraduate Researcher, Rice Realtime Neural Engineering Lab, Rice University, Houston, TX |
| 2013 | Visiting Researcher, The Sabes Lab, The University of California, San Francisco, CA |
| 2013-2014 | Integrated Vitals Monitoring from a Distance, Senior Design - Rice Unversity, Houston, TX |
| 2014-2019 | Ph.D. student, Bioengineering, UC Berkeley and UC San Francisco |
| since 2015 | Ph.D. Candidate, The Chang Lab, The University of California, San Francisco, CA |
| 2019 | Software Engineering Intern, Daydream, Google, San Francisco, CA |
Ph.D. Jack GALLANT
Professor and Head, Gallant Lab, Department of Psychology, University of California Berkeley, CA
| 1983-1988 | Ph.D., Yale University, New Haven, CT |
| 1988-1992 | Post-doctoral Research Fellow, California Institute of Technology, Pasadena, CA |
| 1992-1995 | Post-doctoral Research Fellow, Washington University Medicine School, WA |
| The overall goal of Prof. Gallant's research program is to discover how the brain represents information under natural conditions (i.e., natural stimulation and natural tasks), and to create computational models that accurately predict brain activity under naturalistic conditions. He currently uses fMRI, statistical and computational modeling to produce detailed human cortical maps of information related to vision, language and decision making; to characterize individual differences in cortical organization in humans; and to understand dynamic thought processes in the human brain; and to decode human brain activity. |
Dipl.-Ing. Dr. Veronika SCHÖPF
Consulting Manager; Guest Professor; Accenture GmbH; Medical University of Vienna
| 2005-2008 | Research Assistant, University of Munich |
| 2008-2013 | Postdoctoral Fellow, Medical University of Vienna |
| 2013-2015 | Assistant Professor, Medical University of Vienna |
| 2014-2019 | Professor, University of Graz |
| since 2019 | Guest Professor, Medical University of Vienna |
| Consulting Manager, Accenture GmbH, Vienna |
