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PhD Candidate @ USC
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Assessing your cultural and operational fit
AWS-SageMaker-XGBoost
June 15, 2024 – June 17, 2024
Train, Tune, and Evaluate XGBoost on Amazon SageMaker
View Projectprivate_traffic_prediction
September 11, 2023 – December 2, 2024
Private traffic prediction
View ProjectPrivate-NonConvex-Federated-Learning-Without-a-Trusted-Server
March 13, 2022 – March 3, 2023
Private-NonConvex-Federated-Learning-Without-a-Trusted-Server — GitHub repository
View ProjectLogistic_Regression
March 7, 2022 – April 12, 2023
Model=Logistic Regression Model, Algorithm=Minibatch SGD, Data=MNIST
View ProjectIncentive_Systems_for_New_Mobility_Services
December 30, 2021 – October 7, 2024
The implementation of "Incentive Systems for Fleets of New Mobility Services" incentivization platform
View ProjectCongestion-Reduction-via-Personalized-Incentives
April 6, 2021 – May 14, 2024
Congestion Reduction via Personalized Incentives
View ProjectRobust-Traffic-Flow-Prediction
February 4, 2020 – June 21, 2020
A new formulation to minimize both average and variance of the error.
View ProjectCultural Fit Analysis
The candidate's projects indicate a strong interest in research-oriented and complex problem-solving within data science, which aligns with roles requiring innovation and deep analytical thinking. The diversity of projects (traffic, federated learning, NLP, AWS SageMaker) suggests adaptability and a broad learning curve. However, all projects are personal, which might indicate less experience in collaborative, production-level environments.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback provided.