Stanford University
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Oscar Rodriguez
Graduate, Stanford Center for Professional Development
BioPursuing a Graduate Certificate in Artificial Intelligence. Outside of Stanford, I work on Machine Learning infrastructure for Gemini training setups at Google.
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Carlos Jose Rodriguez Santiago
Ph.D. Student in Chemical Engineering, admitted Autumn 2022
BioCarlos Rodriguez Santiago is a Chemical Engineering PhD candidate working in the lab of Dr. Judith Shizuru to develop protein therapeutics that will facilitate hematopoietic stem cell transplantation without the need for chemotherapy or radiation. His PhD thesis work is at the intersection of immunology, oncology, and protein engineering. Carlos is also a Sarafan CheM-H Lipshultz Graduate Fellow participating in the Chemistry/Biology Interface (CBI) Predoctoral training program which aims to cultivate interactions and thinking across disciplinary lines to enable innovations that improve human health.
Prior to his PhD work, Carlos helped found the Protein Engineering Knowledge Center (PEKC) at Stanfords Innovative Medicines Accelerator (IMA). There he collaborated with researchers to discover and engineer antibodies against therapeutically relevant targets. Several antibodies discovered by Carlos have officially been licensed out for further therapeutic development. -
Justin S. Rogers
Research Oceanographer, Civil and Environmental Engineering
Staff, Program-Fringer O.BioPh.D. Civil & Environmental Engineering, Stanford University, 2016
M.S. Civil & Environmental Engineering, University of Wisconsin-Madison, 2006
B.S. Civil Engineering (Minor in Chemistry), University of Arizona, 2004
Research interests:
-Coastal resilience, risk, sea level rise, extreme events, compound hazards
-Impact of climate change on human and natural systems in coastal and nearshore environments
-Core model development for coastal applications, storm surge, tropical cyclones, flood risk, bottom boundary layers, turbulence, and multiscale physics.
I leverage the power of cloud computing, HPC systems and modern code frameworks, and adapt multiple analysis methods including dynamical models, machine learning, statistical methods, and field observations.
