School of Medicine
Showing 4,161-4,170 of 4,717 Results
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Hua Tang
Professor of Genetics and, by courtesy, of Statistics
Current Research and Scholarly InterestsDevelop statistical and computational methods for population genomics analyses; modeling human evolutionary history; genetic association studies in admixed populations.
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Jean Y. Tang MD PhD
Professor of Dermatology
Current Research and Scholarly InterestsMy research focuses on 2 main areas:
1. Skin cancer:
- New therapeutics to treat and prevent non-melanoma skin cancer, especially by targeting the Hedgehog signaling pathway for BCC tumors
- Genomic analysis of drug-resistant cancers
- Identifying risk factors for skin cancer in the Women's Health Initiative
2. Epidermolysis Bullosa: gene therapy and protein therapy to replace defective/absent Collagen 7 in children and adults with Recessive Dystrophic EB -
Sindy Tang
Associate Professor of Mechanical Engineering, Senior Fellow at the Woods Institute for the Environment and Professor, by courtesy, of Radiology and of Bioengineering
On Leave from 04/01/2024 To 06/30/2024Current Research and Scholarly InterestsThe long-term goal of Dr. Tang's research program is to harness mass transport in microfluidic systems to accelerate precision medicine and material design for a future with better health and environmental sustainability.
Current research areas include: (I) Physics of droplets in microfluidic systems, (II) Interfacial mass transport and self-assembly, and (III) Applications in food allergy, single-cell wound repair, and the bottom-up construction of synthetic cell and tissues in close collaboration with clinicians and biochemists at the Stanford School of Medicine, UCSF, and University of Michigan.
For details see https://web.stanford.edu/group/tanglab/ -
Sami Gamal-Eldin Tantawi
Professor of Particle Physics and Astrophysics
BioFor over a decade I have advocated for dedicated research efforts on the basic physics of room temperature high gradient structures and new initiatives for the associated RF systems. This required demanding multidisciplinary collaboration to harness limited resources. The basic elements of the research needed to be inclusive to address not only the fundamentals of accelerator structures but also the fundamentals of associated technologies such as RF manipulation and novel microwave power sources. These basic research efforts were not bundled with specific developments for an application or a general program. The emerging technologies promise a broad, transformational impact.
With this underlying philosophy in mind, in 2006 the US High Gradient Research Collaboration for which I am the spokesman was formed. SLAC is the host of this collaboration, which comprises MIT, ANL, University of Maryland and University of Colorado, NRL and a host of SBIR companies. This led to the revitalization of this research area worldwide. The international collaborative effort grew to include KEK in Japan, INFN, Frascati in Italy, the Cockcroft Institute in the UK, and the CLIC team at CERN.
This effort led to a new understanding of the geometrical effects affecting high gradient operations. The collaborative work led to new advances in understanding the gradient limits of photonic band gap structures. Now we have a new optimization methodology for accelerator structure geometries and ongoing research on alternate and novel materials. These efforts doubled the usable gradient in normal conducting high gradient linacs to more than 100 MV/m, thus revitalizing the spread of the technology to other applications including compact Inverse Compton Scattering gamma-ray sources for national security applications, and compact proton linacs for cancer therapy. -
Peter Tass
Professor of Neurosurgery
BioDr. Peter Tass investigates and develops neuromodulation techniques for understanding and treating neurologic conditions such as Parkinson’s disease, epilepsy, dysfunction following stroke and tinnitus. He creates invasive and non-invasive therapeutic procedures by means of comprehensive computational neuroscience studies and advanced data analysis techniques. The computational neuroscience studies guide experiments that use clinical electrophysiology measures, such as high density EEG recordings and MRI imaging, and various outcome measures. He has pioneered a neuromodulation approach based on thorough computational modelling that employs dynamic self-organization, plasticity and other neuromodulation principles to produce sustained effects after stimulation. To investigate stimulation effects and disease-related brain activity, he focuses on the development of stimulation methods that cause a sustained neural desynchronization by an unlearning of abnormal synaptic interactions. He also performs and contributes to pre-clinical and clinical research in related areas.
