Roger Zhu

Data Scientist

https://talent.gravityer.com/roger-zhu

Student of Advanced Science at UQ Major in Computer Science Minors in Statistics and Data Science

Member since June 28, 2026

Key Strengths

Demonstrated proficiency in Python for data science and machine learning tasks.
Experience with various machine learning models including XGBoost, Decision Trees, Neural Networks, and VAEs.
Familiarity with NLP techniques, including fine-tuning T5-small for summarization.
Exposure to distributed computing with PySpark and Hadoop.
Practical application of LLM and RAG agents for recommendation systems.
Experience with Docker for containerization.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's projects are primarily personal and academic, demonstrating a strong interest in data science and machine learning. However, without information on collaborative projects or work experience, it is difficult to fully assess cultural fit within a team or corporate environment. The diversity of projects suggests an inquisitive and self-driven individual.

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. The candidate's project descriptions indicate a proactive approach to learning and applying new technologies.

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Identifying your key strengths…

Evaluating your skill match against the job requirements…

Assessing your cultural and operational fit

Projects

movielens-spark-analysis

June 8, 2026 – Present

User genre preference clustering and recommendation mining on MovieLens 1M; PySpark, Hadoop, ALS, and association rules in a Dockerised distributed cluster.

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Multimodal-Book-Review-LLM-RAG-Agent

May 8, 2026 – Present

Personalised multimodal book recommendation agent: hybrid FAISS retrieval (BGE text + CLIP cover images) with a LangGraph tool-calling agent that dynamically selects and chains retrieval tools at runtime.

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Split-Keyboard-Custom-Firmware

April 25, 2026 – Present

Split-Keyboard-Custom-Firmware — GitHub repository

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Concept-Unlearning-in-Variational-Autoencoders

April 25, 2026 – Present

Measuring residual information in latent representations

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Biomedical-Report-NLP-Summariser

January 11, 2026 – Present

I Fine-tuned a T5-small Natural Language model. converts radiology reports into clear, layperson-friendly summaries while preserving clinical accuracy.

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ALGOJAM-2025-PUBLIC

March 23, 2025 – April 8, 2025

Public Algojam

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imc-prosperity3

March 6, 2025 – Present

imc-prosperity3 — GitHub repository

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XGBoost-Decision-Tree-Neural-Network-Comparison

June 19, 2024 – June 19, 2024

My report for COMP4702: Machine Learning, A comparison between XGBoost, Decision Trees, and Neural Networks for a binary classification task.

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flushyr

June 1, 2024 – February 17, 2025

flushyr — GitHub repository

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Path-of-Exile-Chaos-Divine-Calculator

February 20, 2024 – February 20, 2024

Input some chaos, then based on the current exchange rate, outputs how many divine its worth.

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Key Strengths

Demonstrated proficiency in Python for data science and machine learning tasks.
Experience with various machine learning models including XGBoost, Decision Trees, Neural Networks, and VAEs.
Familiarity with NLP techniques, including fine-tuning T5-small for summarization.
Exposure to distributed computing with PySpark and Hadoop.
Practical application of LLM and RAG agents for recommendation systems.
Experience with Docker for containerization.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. The candidate's project descriptions indicate a proactive approach to learning and applying new technologies.

Roger Zhu

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Projects

Key Strengths

Cultural & Operational Fit