School of Humanities and Sciences
Showing 1-10 of 177 Results
-
Ethan Allavarpu
Masters Student in Statistics, admitted Autumn 2022
Project Assistant, Woods InstituteBioI am pursuing an M.S. in Statistics 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 B.S. in Statistics from the University of California, Los Angeles (UCLA). Next summer (2023), I will join Apple as a Data Science and Visualization Intern within the Hardware Engineering team.
This past summer (2022), I was a Data Science Intern with Bridg working on data querying, natural language processing (NLP), and machine learning with Python, SQL, and Snowflake on terabytes of data (over 100 billion observations) to improve insights on product descriptions and feature standardization across various sources. During my senior year at UCLA, I was a Data Analyst Intern with SCAN Health Plan performing NLP and unsupervised learning (agglomerative clustering) in Python to analyze call center data while also creating Tableau dashboards. I also was a Data Science Consultant with UCLA’s Data Science Center, working as a consultant to meet ad-hoc and long-term requests from clients in varied fields. Additionally, I was the president of Bruin Sports Analytics, combining sports and analytics by guiding our data journalism, research, and consulting teams to produce deliverables for sports fans and UCLA’s intercollegiate teams.
I am always willing to discuss potential work opportunities or my path with prospective undergraduate or graduate students or data science enthusiasts. Feel free to contact me via email, LinkedIn, or my personal website. -
Milad Bakhshizadeh
Postdoctoral Scholar, Statistics
Current Research and Scholarly InterestsHigh dimensional Statistics, Concentration inequalities, Random Matrix Theory, Structured signal processing, Inverse Problems, Phase Retrieval.
-
Emmanuel Candes
Barnum-Simons Chair of Math and Statistics, and Professor of Statistics and, by courtesy, of Electrical Engineering
BioEmmanuel Candès is the Barnum-Simons Chair in Mathematics and Statistics, a professor of electrical engineering (by courtesy) and a member of the Institute of Computational and Mathematical Engineering at Stanford University. Earlier, Candès was the Ronald and Maxine Linde Professor of Applied and Computational Mathematics at the California Institute of Technology. His research interests are in computational harmonic analysis, statistics, information theory, signal processing and mathematical optimization with applications to the imaging sciences, scientific computing and inverse problems. He received his Ph.D. in statistics from Stanford University in 1998.
Candès has received several awards including the Alan T. Waterman Award from NSF, which is the highest honor bestowed by the National Science Foundation, and which recognizes the achievements of early-career scientists. He has given over 60 plenary lectures at major international conferences, not only in mathematics and statistics but in many other areas as well including biomedical imaging and solid-state physics. He was elected to the National Academy of Sciences and to the American Academy of Arts and Sciences in 2014.
