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Synopsys
Software Engineer
June 25, 2026 – Present
Super-Loss
December 29, 2020 – January 26, 2021
PyTorch implementation of the paper "SuperLoss: A Generic Loss for Robust Curriculum Learning" in NIPS 2020.
View ProjectTruncated-Loss
November 11, 2019 – November 12, 2019
PyTorch implementation of the paper "Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels" in NIPS 2018
View ProjectAdversarial-Training-for-Free
May 2, 2019 – May 8, 2019
Unofficial implementation of the paper 'Adversarial Training for Free'
View ProjectDeep-Co-Training-for-Semi-Supervised-Image-Recognition
January 29, 2019 – August 25, 2019
Unofficial implementation of the paper 'Deep Co-Training for Semi-Supervised Image Recognition'
View ProjectCultural Fit Analysis
The candidate's personal projects are heavily focused on machine learning research, specifically implementing academic papers. This indicates a strong interest in deep learning and algorithm development. The current role as a Software Engineer at Synopsys suggests professional experience, but the specific responsibilities are not detailed. The alignment with a general 'Software Engineer' target role is moderate; the candidate's demonstrated passion leans towards a specialized ML/AI engineering role. The breadth of skills is limited to Python based on project technologies.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. No psychometric test results or interview feedback provided.