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Eng.D student at Tsinghua University (Embodied intelligence, AI safety)
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
PACT
May 20, 2026 – Present
[ICML 2026 Spotlight] Official implementation of "PACT: Self-Evolving Physical Safety Alignment for Diffusion Policies in Embodied Manipulation".
View ProjectEmbodiedActiveDefense
July 16, 2025 – July 26, 2025
Official implementation for "Reinforced Embodied Active Defense: Exploiting Adaptive Interaction for Robust Visual Perception in Adversarial 3D Environments" (TPAMI 2025)
View Projecthopfield-torch
May 15, 2022 – May 18, 2022
PyTorch implementation of Hopfield network for MNIST.
View Projectcn-summary
December 19, 2021 – July 6, 2022
repository for generation Chinese summary with multiple algorithms
View ProjectLaVan-Pytorch
October 28, 2021 – May 23, 2022
Reproduce work "LaVAN: Localized and Visible Adversarial Noise - ICML2018"
View Projectface-recognition-iai
October 20, 2021 – February 2, 2022
Repository of course final assignment for Pattern Recognition class in IAI, BUAA.
View ProjectRL-iai
September 17, 2021 – March 8, 2022
Repository of code for Reinforcement Learning course in IAI, BUAA
View ProjectyuYuanCup
October 2, 2020 – May 22, 2021
build a colorful LED tracking self-controlled car.
View ProjectCultural Fit Analysis
The candidate's project portfolio is heavily skewed towards academic research in machine learning, computer vision, and reinforcement learning, primarily using Python. While this demonstrates strong technical capabilities in those areas, it shows a significant mismatch with a 'Frontend Developer' target role. There is minimal evidence of frontend-specific technologies (e.g., modern JavaScript frameworks, CSS preprocessors, build tools) or design-oriented projects. The inclusion of HTML and JavaScript in one project ('RL-iai') is minimal and not indicative of a frontend specialization. This suggests a poor cultural fit for a dedicated frontend role.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's project descriptions are concise and technical, but do not provide insight into collaboration, problem-solving approaches, or communication style.