Stanford University
Showing 141-150 of 156 Results
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Fabio Hübel
Graduate Visiting Researcher Student, Aeronautics and Astronautics
BioVisiting Student Research at Marco Pavone's Group (Autonomous Systems Lab).
Master Thesis in autonomous navigation and exploration for quadrupeds. -
Wouter Huiting
Postdoctoral Scholar, Chemical and Systems Biology
BioWouter received his training at the University of Groningen, the Netherlands. Here he obtained a B.Sc.and M.Sc. in Human Movement Sciences (2008-2015), followed by a M.Sc. in Clinical and Molecular Neurosciences (2014-2016). He performed his doctoral research at the University of Groningen, obtaining his PhD degree in Molecular Cell Biology in 2021. Wouter continued his research in 2022 with a position as postdoctoral scholar at the Jarosz lab, at the department of Chemical and Systems Biology. Here he pursues his interest in the molecular forces underlying proteomic adaptation of cells and systems in development and disease. Outside of Stanford, Wouter is an avid sportsman, and likes cooking, hiking, birding, and in general loves to enjoy nature and wildlife with his wife and son.
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Alissa Hummer
Postdoctoral Scholar, Bioengineering
BioAlissa is a Schmidt Science Fellow in the labs of Emma Lundberg and Wah Chiu. She is integrating microscopy techniques with AI to study and model cellular processes. Prior to her postdoc, Alissa completed her PhD at the University of Oxford, where she developed machine learning models for therapeutic antibody optimization and design.
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Elima Hussain
Postdoctoral Scholar, Radiology
BioDr. Elima is working with GE Healthcare on developing rapid dual-contrast PET/MRI protocols for staging and assessment of rectal cancer. She is also working on development of AI based segmentation models for muscle and fat separation using pelvic MRI images in pelvic floor disorder patients. This project is undergoing in collaboration with Stanford AIMI center and AWS cloud computation support. Her research interests include translation of quantitative MRI and PET/MRI, radiomics, machine learning for predicting treatment response in rectal cancer, gynecologic malignancies, and inflammatory bowel diseases.
