Ph.D. Candidate at UCLA applied math.
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Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
ENIAC
March 16, 2021 – April 7, 2021
code for paper: Provably Correct Optimization and Exploration with Non-linear Policies
View ProjectFlorenceFeng.github.io
February 23, 2021 – January 19, 2022
FlorenceFeng.github.io — GitHub repository
View ProjectAsyncQVI
January 31, 2019 – March 15, 2019
A light C++11 package for three reinforcement learning algorithms.
View ProjectIPSVRG
January 26, 2019 – May 4, 2019
A light MATLAB package for acceleration of SVRG and Katyusha X by inexact preconditioning.
View ProjectAsyncQVI
October 30, 2018 – March 16, 2019
A light c++11 package for three reinforcement learning algorithms.
View ProjectTMAC
June 3, 2016 – April 25, 2017
TMAC: A Toolbox of Modern Async-Parallel, Coordinate, Splitting, and Stochastic Methods
View ProjectCultural Fit Analysis
The candidate's projects are primarily academic/research-oriented, focusing on optimization and machine learning algorithms. This indicates a strong fit for roles requiring deep analytical skills and research capabilities. The diversity of projects across C++, Python, and MATLAB suggests adaptability in technical environments. However, the lack of team-based projects or industry experience makes it difficult to fully assess collaboration and broader cultural fit.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. No psychometric test results or interview feedback provided.