School of Humanities and Sciences
Showing 1-10 of 215 Results
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Ethan Allavarpu
Masters Student in Statistics, admitted Autumn 2022
Project Assistant, Healthy Planet Healthy PeopleBioI 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.
This 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. -
Michael Baiocchi
Associate Professor of Epidemiology and Population Health and, by courtesy, of Statistics and of Medicine (Stanford Prevention Research Center)
BioProfessor Baiocchi is a PhD statistician in Stanford University's Epidemiology and Population Health Department. He thinks a lot about behavioral interventions and how to rigorously evaluate if and how they work. Methodologically, his work focuses on creating statistically rigorous methods for causal inference that are transparent and easy to critique. He designed -- and was the principle investigator for -- two large randomized studies of interventions to prevent sexual assault in the settlements of Nairobi, Kenya.
Professor Baiocchi is an interventional statistician (i.e., grounded in both the creation and evaluation of interventions). The unifying idea in his research is that he brings rigorous, quantitative approaches to bear upon messy, real-world questions to better people's lives. -
Milad Bakhshizadeh
Postdoctoral Scholar, Statistics
Current Research and Scholarly InterestsHigh dimensional Statistics, Concentration inequalities, Random Matrix Theory, Structured signal processing, Inverse Problems, Phase Retrieval.
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Rebecca Becht
Undergraduate, Earth Systems Program
Undergraduate, StatisticsBioMember of the Stanford Women's Golf Team
