Jingnan Zheng

Data Scientist

https://talent.gravityer.com/jingnan-zheng

PhD Student in NExT++

NUS

Key Strengths

Strong foundational knowledge in Python for data science and machine learning, evidenced by numerous personal projects.
Extensive experience with large language models (LLMs), including research and implementation of agent-based evaluation and safety mechanisms.
Demonstrated ability to work with collaborative filtering and recommendation systems, including invariant collaborative filtering.
Proficiency in C++ and Cython for performance-critical components, indicating an understanding of optimization.
Experience with shell scripting for automation and system interaction.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's projects are heavily research-oriented and academic, focusing on LLMs, recommendation systems, and simulation. While these align with a Data Scientist role, the lack of diverse project types (e.g., business applications, production deployments) and the absence of team-based project descriptions make it difficult to fully assess cultural fit for a typical industry role. The candidate's experience is listed as 'Data Scientist' at NUS, which is a research institution, further reinforcing a research-heavy profile. This might indicate a stronger fit for R&D-focused data science roles rather than general product-oriented ones.

Soft Skills & Operational Fit

The provided data is insufficient to assess soft skills or operational fit. The candidate's project descriptions are concise, but there is no information regarding teamwork, problem-solving approaches, or communication style in a professional setting.

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Projects

Risky-Bench

February 3, 2026 – Present

Official implementation of "Risky-Bench: Probing Agentic Safety Risks under Real-World Deployment"

View Project

Self-Guard

January 31, 2026 – Present

Official implementation for "Self-Guard: Defending Large Reasoning Models via enhanced self-reflection"

View Project

Must-Read-LLM-Papers

September 16, 2025 – September 16, 2025

Must-Read-LLM-Papers — GitHub repository

View Project

RSafe

May 16, 2025 – Present

Official implementation for "RSafe: Incentivizing proactive reasoning to build robust and adaptive LLM safeguards"

View Project

MaskDroid

June 8, 2024 – September 10, 2024

MaskDroid — GitHub repository

View Project

ALI-Agent

May 23, 2024 – Present

Official implementation for "ALI-Agent: Assessing LLMs'Alignment with Human Values via Agent-based Evaluation"

View Project

CF_Rec

June 22, 2023 – August 2, 2023

A framework for collaborative filtering

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PopGo

April 15, 2023 – January 21, 2025

PopGo — GitHub repository

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InvCF

February 6, 2023 – July 27, 2023

Official code of "Invariant Collaborative Filtering to Popularity Distribution Shift" (2023 WWW)

View Project

Carla-GUI

July 6, 2020 – August 22, 2021

GUI tool for creating simulation scenarios with Carla simulator

View Project

Key Strengths

Strong foundational knowledge in Python for data science and machine learning, evidenced by numerous personal projects.
Extensive experience with large language models (LLMs), including research and implementation of agent-based evaluation and safety mechanisms.
Demonstrated ability to work with collaborative filtering and recommendation systems, including invariant collaborative filtering.
Proficiency in C++ and Cython for performance-critical components, indicating an understanding of optimization.
Experience with shell scripting for automation and system interaction.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Jingnan Zheng

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Experience

Projects

Key Strengths

Cultural & Operational Fit