YushengZhao

Data Scientist

https://talent.gravityer.com/yushengzhao

School of Computer Science, Peking University (2022-); School of Computer Science and Engineering, Beihang University (2018-2022)

Peking University

Key Strengths

Extensive research experience in machine learning, particularly in graph neural networks, large language models, and computer vision, evidenced by numerous publications in top-tier conferences (ICDE, NeurIPS, ACM MM, ICML, AAAI, ACL, ICLR).
Strong proficiency in Python, demonstrated across all listed projects.
Experience with various deep learning frameworks and tools (Jupyter Notebook, Dockerfile) for research and development.
Current role as a Data Scientist at Peking University aligns directly with the target role.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's project history is heavily focused on academic research and publications, indicating a strong drive for innovation and theoretical contributions. This aligns well with roles requiring R&D and problem-solving in novel domains. However, the lack of diverse project types (e.g., industry applications, open-source contributions beyond research repos) and limited technology breadth (primarily Python) might suggest a narrower focus, which could impact adaptability in broader team environments or projects requiring a wider range of tools. The single current employment at a university also limits insight into corporate cultural fit.

Soft Skills & Operational Fit

Insufficient data to assess soft skills and operational fit. The candidate's profile primarily highlights academic research achievements.

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Projects

SampleLottery

February 9, 2026 – Present

[ICLR 2026] Sample Lottery: Unsupervised Discovery of Critical Instances in RLVR of LLMs

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bundle-neurips25

October 1, 2025 – December 9, 2025

[NeurIPS 2025] Dynamic Bundling with Large Language Models for Zero-Shot Inference on Text-Attributed Graphs

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LEAF

May 24, 2025 – August 18, 2025

[ACL 2025] Embracing Large Language Models in Traffic Flow Forecasting

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ASSESS

May 22, 2025 – August 18, 2025

[ICML 2025] Test-time Adaptation on Graphs via Adaptive Subgraph-based Selection and Regularized Prototypes

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TRACI-AAAI25

December 17, 2024 – November 20, 2025

[AAAI 2025] TRACI: A Data-centric Approach for Multi-Domain Generalization on Graphs

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ABPEM

December 15, 2024 – April 29, 2025

[AAAI 2025] Attention Bootstrapping for Multi-Modal Test-Time Adaptation

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DyHSL

October 9, 2022 – October 14, 2022

[ICDE 2023] Dynamic hypergraph structure learning for traffic flow forecasting

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TD-STP

July 3, 2022 – November 1, 2022

[ACM MM 2022] Target-Driven Structured Transformer Planner for Vision-Language Navigation

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BUAA_Computer_Organization_Projects

September 11, 2020 – September 12, 2020

北航《计算机组成课程设计》课程2019 Autumn代码

View Project

mmdet_attacker_fusion

August 16, 2020 – September 30, 2020

mmdet_attacker_fusion — GitHub repository

View Project

Key Strengths

Extensive research experience in machine learning, particularly in graph neural networks, large language models, and computer vision, evidenced by numerous publications in top-tier conferences (ICDE, NeurIPS, ACM MM, ICML, AAAI, ACL, ICLR).
Strong proficiency in Python, demonstrated across all listed projects.
Experience with various deep learning frameworks and tools (Jupyter Notebook, Dockerfile) for research and development.
Current role as a Data Scientist at Peking University aligns directly with the target role.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Insufficient data to assess soft skills and operational fit. The candidate's profile primarily highlights academic research achievements.

YushengZhao

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Experience

Projects

Key Strengths

Cultural & Operational Fit