Zheng (Winston) Ma

Data Scientist

https://talent.gravityer.com/zheng-winston-ma

飘蓬随风

University of Waterloo

Key Strengths

Strong foundational knowledge in Python for data science and machine learning.
Extensive personal project experience in various machine learning domains including graph neural networks, reinforcement learning, and natural language processing (transformers).
Demonstrated interest in advanced topics like distributed training and agentic AI systems.
Experience with collaborative filtering and local LLM chatbot development.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's project portfolio shows a strong inclination towards research-oriented and complex technical challenges, which aligns well with an innovative and problem-solving culture. The diversity of projects, from graph-based learning to reinforcement learning and LLMs, suggests adaptability and a continuous learning mindset. However, the lack of team-based or professional project descriptions makes it difficult to assess collaboration and broader cultural integration.

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. The candidate's projects indicate a strong independent work ethic and initiative in exploring complex technical areas.

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Projects

simple_mcp

June 13, 2026 – Present

Skeleton to start implementing any MCP server in Python

View Project

distributed_training_examples

May 23, 2026 – Present

Example for PyTorch distributed training

View Project

OGCIL

May 20, 2026 – Present

Graph class-incremental learning (GCIL) enables graph neural networks to learn new classes over time while retaining knowledge of old ones. Codebase for MM 2025 paper Towards Effective Open-set Graph Class-incremental Learning

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proteomics_agent_public

April 23, 2026 – Present

A lightweight agentic AI system for querying and summarizing local PDF.

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transformer_translate_v2

April 23, 2026 – Present

A Pytorch reimplementation of Attention is All You Need

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olg_cf

September 14, 2025 – Present

Collaborative filtering based recommendation system with local LLM chatbot.

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dianovo

November 23, 2024 – November 12, 2025

De no peptide sequencing algorithm for DIA mass spectrometry data.

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Shared-YAML-Publications

November 15, 2024 – November 20, 2024

Shared-YAML-Publications — GitHub repository

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graphpi_protein_inference

July 7, 2024 – September 8, 2024

Protein inference algorithm based on graph neural network.

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cs885_assignments

October 7, 2022 – Present

UWaterloo CS885 reinforcement learning assignments.

View Project

Key Strengths

Strong foundational knowledge in Python for data science and machine learning.
Extensive personal project experience in various machine learning domains including graph neural networks, reinforcement learning, and natural language processing (transformers).
Demonstrated interest in advanced topics like distributed training and agentic AI systems.
Experience with collaborative filtering and local LLM chatbot development.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. The candidate's projects indicate a strong independent work ethic and initiative in exploring complex technical areas.

Zheng (Winston) Ma

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Experience

Projects

Key Strengths

Cultural & Operational Fit