Yixin Wang
Software Engineer @ Meta
United States
New York
Computer Software
Front-End Design, PyTorch, Machine Learning, Python (Programming Language)
Experience
Software Engineer
Meta
Bellevue, Washington, United States
Software Engineer Intern
Bausch + Lomb
Bridgewater, New Jersey, United States
• Designed an end-to-end prototype in Figma for Eye Care Professionals and patient workflows and developed the web page layout using React.js and Next.js to expand revenue streams and enhance patient experience • Implemented an automated UPC code mapping system using Python and Tkinter to streamline new product launches in corporate sites, significantly reducing processing time to a near-instantaneous process and avoiding manual errors • Conducted a comprehensive five-year market analysis of traditional hydrogel daily disposable contact lenses using SQL, contributing to 24Q3 strategic planning and marketing campaigns
Undergraduate Research Assistant
NYU Courant Institute School of Mathematics, Computing, and Data Science
Project: Faster randomized partial trace estimation Paper: Tyler Chen, Robert Chen, Kevin Li, Skai Nzeuton,Yilu Pan, and Yixin Wang. “Faster randomized partial trace estimation”. Paper in SIAM Journal on Scientific Computing 46.6 (2024), A3427-A3447. arXiv: 2310.12364 [math.NA]. Poster: "Typicality-Based Algorithm for Partial Trace Estimation". Poster at SIAM-NNP. Newark, NJ, Oct. 2023. | Poster at ASE60. Cambridge, MA, Jul. 2023.
Teaching Assistance/Grader
NYU Courant Institute School of Mathematics, Computing, and Data Science
New York, New York, United States
CSCI-421 Numerical Computing (Spring 2024) MATH-235 Probability & Statistics (Spring 2024) MATH-233 Theory of Probability (Spring 2023, Fall 2023)
Machine Learning Research Intern
SLB
Cambridge, Massachusetts, United States
• Built a general supervised learning framework using PyTorch for Logging While Drilling (LWD) scenarios that directly estimates quadrupole mode dispersion curve from dispersion data and simultaneously obtains formation shear slowness • Reduced processing time for whole logging interval (~10,000 ft) from 261 minutes on a 48-CPU cluster to 65 seconds on a single CPU workstation, enabling real-time data processing at the wellsite and in downhole conditions • Co-authored the paper “Real-Time LWD Sonic Processing Enabled by Data Driven Machine Learning,” presented at the SPWLA 65th Annual Logging Symposium, Rio de Janeiro, Brazil, May 2024 • Co-invented the U.S. patent “IN-SITU REAL-TIME BOREHOLE SONIC PROCESSING,” filed with USPTO (Serial Number 18/898,243), Sept 26, 2024
Celebrity Marketing Intern
GroupM
Shanghai, China
Education
Cornell University
Computer Science
New York University
Mathematics and Computer Science
Yixin Wang's Contact Information
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