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Prof. Tomer Michaeli’s research interests focus in the areas of computer vision; machine learning; signal processing, and image restoration, generation, and manipulation. Working with Technion researchers from biomedical engineering and nanotechnology, he helped develop DeepSTORM3D — a microscopic method that allows scientists to map the biological processes of living cells at super resolution.
Microscopes as a rule produce two-dimensional images. Currently, 3D images are obtained through layer scanning and computerized integration, but the process is problematic and requires a long scanning time. DeepSTORM3D harnessed Prof. Michaeli’s expertise to develop an artificial neural network capable of producing 3D images from microscopy data of real samples with 10 times the resolution of standard microscopes. The breakthrough discovery was published in Nature Methods.
Prof. Michaeli received both his bachelor’s and doctoral degrees in electrical engineering from the Technion in 2005 and 2012, respectively. He then conducted postdoctoral studies at the Weizmann Institute of Science before joining the Technion faculty in 2015.
He has received several awards including the Marr Prize in 2019 for his paper on SinGAN, a generative model trained on a single natural image, and the Krill Prize of the Wolf Foundation in 2020. And not even a decade out of his doctoral studies, he has co-authored close to 90 papers in peer-reviewed journals.