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Page currently under reconstruction (4th October 2014). Expected to finish in several hours. Please check back later :)

Welcome!

I'm Li, a 4th year student at University College London currently working on an MEng in Computer Science. I'm most interested in applications of machine learning to large data sets. I haven't decided on a specific research area, primarily because I don't think I've seen enough of the field yet. However, my current interests slant towards applying machine learning to areas related to data mining, semantic computation, and natural language processing. The data I've worked with in the past are web-based (AOL search logs, Bing session data, mined Twitter data, YAGO2).

Why computer science? At first, I decided to enter the field because I love building things. Stacks. Factories. Interfaces. Semaphores. Software are teeming cities running like clockwork on top of layers and layers of abstraction. I thought that I wanted to be a developer for sure, but then I began to see some really interesting problems and approaches to solving them in the field, so I focused my efforts on research too. Computer science (and AI / machine learning) is very much in the middle of interdisciplinary research, and I think this is where the most exciting things are happening. Actually, previously I was a medical student in Imperial College London - I left after two years - but that's a story for another time ;)

+ For people unfamiliar with computer science, machine learning really is just pattern recognition. If you can reduce a problem to a pattern recognition problem, then you can apply machine learning to solve it. It is a powerful technique that we can use to try and find features / trends / patterns hidden within huge amounts of data (DNA, stock ticks, the internet), or to classify that data into different categories (think algorithm that recognizes faces, road signs, or system intrusions based on anomalous behaviour patterns).

Pastimes

Currently wiki is mostly used to construct and publish dynamic/modular documents since wikitext/HTML is easier to work with than LaTeX in some cases. MediaWiki also works as a convenient CMS for the dev diary.

Developer diary

• Dev:SynthJS