The image of a crazy researcher with frizzy hair and big glasses in a lab is stereotypical - but what does research in computer science actually look like? We have invited four researchers from Google to tell us all about their story, work and career path - join us to find out about the mysteries of research in a technical field!
UX Researcher
Google Health
ML Researcher
Perception Researcher
Compiler Researcher
Although Natalie worked as an engineer for 4 years after graduating from the University of Maryland, she decided to pivot to pursue her true passions and work on the human side of technology. She received a Masters in Human-Computer Interaction from Carnegie Mellon, where she was able to nerd out over robotics, while still thinking creatively of how to design technology that improves people's lives. Natalie has worked at Google since 2016, doing user research in emerging technologies from virtual reality hardware and software experiences, augmented reality, to visual search aka Google Lens.
Subhrajit Roy is a research scientist at Google where he works on developing novel deep learning algorithms for predicting adverse events in hospitals. Previously, he worked as a research staff member at IBM Research Australia where he co-designed machine learning systems for seizure management in epileptic patients. His work led to Forbes magazine including him in their prestigious 30 Under 30 list.
Electronics undergrad at UTFSM (Chile), PhD in robotics at INRIA/Mines-Paristech (France), post-docs at KULeuven (Belgium) and MPI-Inf (Germany).
Rodrigo works as senior research scientist in Google Zürich since 2017. His mission statement reads as "Robot eyes opener".
Links:
https://scholar.google.com/citations?user=SVNNgu4AAAAJ&hl=en
Ondrej is an engineer in the Compiler Research group based in Paris. Before joining Google, his main research interests were machine learning, probabilistic graphical models for decision making. He was always interested in low-level details, and how computers work, and working at the intersection of machine learning, compilers and performance optimization matches perfectly these interests.
GDSC Munich Lead
GDSC Munich Lead
GDSC Munich Core Team
GDSC Munich Core Team
GDSC Munich Advisor
GDSC Munich Advisor
GDSC Munich Core Team
GDSC Munich Core Team
Technical University of Munich
GDSC Munich Core Member
GDSC Munich Core Member
TUM
GDSC Munich Core Team
GDSC Munich Core Team
