James Liang

I'm from Melbourne, Australia. Passionate about data science, running, music, and good restaurants.

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Hi there!

I am currently a student at Monash University, where I study a Bachelor of Computer Science and Commerce, majoring in Data Science and Econometrics. I am also the Publications Director for the Monash Computing and Commerce Association (CCA), where I write about tech related things that interest me and oversee the management of all our publications.

Outside of Uni, I also interned at CSIRO’s Data61, Australia's national science organisation, where I focused on a Large Language Model approach to Topic Taxonomy Completion for literature review streamlining.

I am broadly interested in the realm of machine learning from both a research and industry perspective. Especially as the field continues to evolve and its applications expand, I want to make it so that the uninteresting things are automated, allowing people to feel more comfortable, and live life pursuing what truly impassions them.

Feel free to check out any of my personal works below, and happy reading!

Cheers!

James

Article Publications

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The clouded separation between Algorithms against Intelligence

In a world where AI algorithms can create subject expertise and artistic expressions, what becomes of human intelligence?

Personal Projects

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TopicGemini

Leveraging Large Language Models (LLMs) to improve traditional Topic Modelling methods. In particular, TopicGemini explores the usage of LLMs for granular topic extraction and k cluster determination.

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Project Water

Water is a scarce commodity in many parts of the world. Accurately predicting its availability while reducing the need to routinely check would enable lower costs in monitoring that might be better allocated to creating new water resources. In this kaggle competition, my model ranked within the Final Top 10%.

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Animal Crossing - Sentiment Analysis

A sentiment analysis report on Animal Crossing: New Horizons, examining how the game was received by Professional critics vs. Casual gamers during the first few months of release - and why its review scores on Metacritic were so low :(