Jianhao Yan

Data Scientist

https://talent.gravityer.com/jianhao-yan

Now PhD Student at WestlakeNLP/Zhejiang University. Former Researcher @ Wechat AI.

Zhejiang University

Key Strengths

Extensive experience with Python, Jupyter Notebook, and Shell scripting, crucial for Data Scientist roles.
Strong background in research-oriented projects, particularly in Natural Language Processing (NLP) and Machine Learning (ML), evidenced by multiple academic paper repositories.
Demonstrated ability to work with advanced ML concepts like temporal reasoning, off-policy guidance, and robust edits.
Familiarity with Cuda and C++ indicates potential for performance optimization in ML models.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's projects are predominantly academic and research-focused, indicating a strong inclination towards theoretical and experimental work. While this aligns with advanced data science roles, the lack of diverse project types (e.g., industry applications, product development) and limited experience outside of a university setting might suggest a need for adaptation to a more product-driven or fast-paced corporate environment. The candidate's experience is primarily in personal projects, which may not fully reflect team collaboration or stakeholder management skills.

Soft Skills & Operational Fit

The provided data does not contain sufficient information to assess soft skills or operational fit. Project descriptions are brief and do not detail collaboration or problem-solving approaches.

AI is analyzing your overall score…

Identifying your key strengths…

Evaluating your skill match against the job requirements…

Assessing your cultural and operational fit

Projects

RobustKeyEdit

May 22, 2025 – May 26, 2025

Official repository for ACL 2025 Main Conference Paper "Keys to Robust Edits: From Theoretical Insights to Practical Advances"

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LUFFY

April 20, 2025 – Present

Official Repository of "Learning to Reason under Off-Policy Guidance"

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RefuteBench-2.0

February 25, 2025 – June 24, 2025

Official code for RefuteBench 2.0~

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LLMEval

January 14, 2025 – April 24, 2025

LLMEval — GitHub repository

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RefuteBench

February 20, 2024 – March 7, 2024

RefuteBench — GitHub repository

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understand-icl-from-repetition

September 30, 2023 – February 23, 2024

understand-icl-from-repetition — GitHub repository

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Graph-aS-Tokens

February 12, 2023 – November 29, 2024

Graph-aS-Tokens — GitHub repository

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digging_errors_nmt

October 19, 2022 – December 5, 2022

digging_errors_nmt — GitHub repository

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Multi_Unit_Transformer

October 4, 2020 – November 15, 2020

Multi_Unit_Transformer — GitHub repository

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DS_Temporal

March 11, 2019 – August 26, 2019

Code for NAACL-19 paper "Relation Extraction with Temporal Reasoning Based on Memory Augmented Distant Supervision"

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Key Strengths

Extensive experience with Python, Jupyter Notebook, and Shell scripting, crucial for Data Scientist roles.
Strong background in research-oriented projects, particularly in Natural Language Processing (NLP) and Machine Learning (ML), evidenced by multiple academic paper repositories.
Demonstrated ability to work with advanced ML concepts like temporal reasoning, off-policy guidance, and robust edits.
Familiarity with Cuda and C++ indicates potential for performance optimization in ML models.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

The provided data does not contain sufficient information to assess soft skills or operational fit. Project descriptions are brief and do not detail collaboration or problem-solving approaches.

Jianhao Yan

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Experience

Projects

Key Strengths

Cultural & Operational Fit