Mike Hawrylycz joined the Allen Institute for Brain Science in Seattle, Washington, in 2003 as director of informatics and one of the institute’s first staff. His group is responsible for developing algorithms and computational approaches in the development of multimodal brain atlases, and in data analysis and annotation. Hawrylycz has worked in a variety of applied mathematics and computer science areas, addressing challenges in consumer and investment finance, electrical engineering and image processing, and computational biology and genomics. He received his Ph.D. in applied mathematics at the Massachusetts Institute of Technology and subsequently was a postdoctoral researcher at the Center for Nonlinear Studies at the Los Alamos National Laboratory in New Mexico.
Michael Hawrylycz
Investigator
Allen Institute for Brain Science
From this contributor
Knowledge graphs can help make sense of the flood of cell-type data
These tools, widely used in the technology industry, could provide a foundation for the study of brain circuits.
Knowledge graphs can help make sense of the flood of cell-type data
Explore more from The Transmitter
What is the future of organoid and assembloid regulation?
Four experts weigh in on how to establish ethical guardrails for research on the 3D neuron clusters as these models become ever more complex.
What is the future of organoid and assembloid regulation?
Four experts weigh in on how to establish ethical guardrails for research on the 3D neuron clusters as these models become ever more complex.
Insights on suicidality and autism; and more
Here is a roundup of autism-related news and research spotted around the web for the week of 8 December.
Insights on suicidality and autism; and more
Here is a roundup of autism-related news and research spotted around the web for the week of 8 December.
Exclusive: Springer Nature retracts, removes nearly 40 publications that trained neural networks on ‘bonkers’ dataset
The dataset contains images of children’s faces downloaded from websites about autism, which sparked concerns at Springer Nature about consent and reliability.
Exclusive: Springer Nature retracts, removes nearly 40 publications that trained neural networks on ‘bonkers’ dataset
The dataset contains images of children’s faces downloaded from websites about autism, which sparked concerns at Springer Nature about consent and reliability.