School of Engineering
Showing 101-120 of 306 Results
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Sadegh Ghorbani
Visiting Post Doc, Geballe Laboratory for Advanced Materials
Casual - Non-Exempt, Office of Technology Licensing (OTL)
Staff, Program-Heilshorn, S.BioA biotechnologist with a focus on protein-based hydrogels, aimed at exploring the intricate processes of neurogenesis, brain tumors, and the signaling pathways governing their cell-cell and cell-matrix adhesion. Through the utilization of customizable hydrogels that incorporate cell-adhesive sequences, our primary objective is to mimic the native microenvironment of the nervous system within 3D systems, allowing us to discern the intricate responses of cells on engineered and functional bio-interfaces. My work is driven by dual-core objectives. Firstly, I am committed to enhancing the treatment of peripheral nerve injuries by devising a therapeutic approach that is both efficient and effective. Secondly, I am involved in investigating the complex interactions between brain cancer cells and neuronal cells in precisely defined microenvironments.
#Biomaterials #Biointerface #Tissue_engineering #Neuroscience #Brain_tumors #Biotechnology #Cellular_biology -
James F Gibbons
Professor (Research) of Electrical Engineering, Emeritus
BioA pioneer in the use of ion implantation and rapid thermal process techniques for solid-state physics, Gibbons also conducts research into semiconductor device analysis, fabrication, and process physics. Current research is focused on the growth and processing of thin semiconductor films and nanostructures that offer potential for advanced semiconductor and optical device development.
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Kay Giesecke
Professor of Management Science and Engineering
Current Research and Scholarly InterestsKay is a financial technologist whose research agenda is driven by significant applied problems in areas such as investment management, risk analytics, lending, and regulation, where data streams are increasingly large-scale and dynamical, and where computational demands are critical. He develops and analyzes statistical machine learning methods to make explainable data-driven decisions in these and other areas and efficient numerical algorithms to address the associated computational issues.
