Stanford Doerr School of Sustainability
Showing 1-10 of 17 Results
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Aakash Ahamed
Research Assistant, Geophysics Faculty Programs
BioAakash Ahamed (BS, with honors, Franklin and Marshall College; MSc, Boston College; PhD, Stanford University) is a hydrologist developing scientific methods for satellite and airborne remote sensing measurements with applications to water resources, natural hazards, and agricultural systems. His doctoral work focused on developing satellite-based models of groundwater mass changes in California's aquifers. Aakash previously worked as a support scientist in the Hydrological Sciences Lab at NASA Goddard Space Flight Center, where he constructed satellite-based models of flood and landslide hazards. He has also developed remote sensing analyses and software at Ceres Imaging, a successful precision agriculture start up based in Silicon Valley, and interned as a GIS analyst at the World Wildlife Fund for Nature in Washington, DC.
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Ethan Allavarpu
Masters Student in Statistics, admitted Autumn 2022
Project Assistant, Woods Support for Steve LubyBioI am currently pursuing a Master of Science (M.S.) in Data Science at Stanford University (with coursework in Statistics, Computer Science, and Computational and Mathematical Engineering). Before Stanford, I graduated summa cum laude with a Bachelor of Science (B.S.) in Statistics from the University of California, Los Angeles (UCLA). I am always eager to contribute to research and gain more experience through data science internships. My technical prowess, determined work ethic (I completed my four-year undergraduate degree at UCLA in three years), and effective communication skills make me a valuable addition to any team.
Next summer (2023), I will join Apple as a Data Science Intern. Currently, I am a research assistant within the Luby Lab at Stanford, working on processing, standardizing, and visualizing data regarding brick kiln production in South Asia. Last year, I interned with Bridg as a Data Science Intern, working on data querying, data transformations, natural language processing (NLP), and machine learning with Python and SQL--with integrations in Snowflake (and Snowpark, Snowflake's Python API)--on terabytes of data (over 100 billion observations). My projects improved insights from product descriptions and standardized features across multiple sources.
My experiences have prepared me to work in virtually any domain. I am always willing to discuss potential work opportunities or my path with prospective undergraduate or graduate students or data science enthusiasts via LinkedIn or email.
