Difference between revisions of "CV:General"

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*CS231n Convolutional Neural Networks for Visual Recognition (Spring 2017) - Capstone: <i>[http://lqkhoo.com/wiki/index.php/Main_Page#Bounding_Out-of-Sample_Objects_.282017.29 Bounding out-of-sample objects]</i>
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Revision as of 06:01, 26 August 2019

Professional experience
Research Software Development Engineer - Ocean 5 Technologies Singapore
2017 - present

Working with a team of electrical and mechanical engineers, we developed a tractor system and a drill assembly equipped with sensors and GPS, for making certain types of rocky terrain feasible for agriculture. Part of a government initiative to improve accountability and yield through technology and data, especially in remote locations with unreliable internet access. I am responsible for building embedded control systems for pilot input, hydraulics, engine, and power, as well as the Python backend and UI of the analytics platform.

CAN bus • RS-232 • embedded systems • distributed systems
R&D Scientist - Digital:MR
2015

Feasibility study on sentiment analysis of images in social media, funded by a research grant from the UK government's technology strategy board. Starting from the Yfcc100m and YLI datasets comprised of 100 million images, labels, and metadata, I investigated both novel and existing methods and developed a commercial product, which has since evolved to be based on convolutional neural nets.

Supervised learning • imaging
Research Intern - Microsoft Research Cambridge
2014

Research internship through the Bright Minds Intern Competition programme in the Machine Learning and Perception research group, working with Principal / Senior Researchers Pushmeet Kohli, Yoram Bachrach, Ulrich Paquet, and Filip Radlinski.

I worked on Project SmartFence - an application for web access control. Users block or allow a few sites they know about, and SmartFence automatically infers the suitability of the rest of the web. We developed several different cluster/kernel-based models and visualization schemes. The final model generates a high dimensional embedding of websites from search sessions (think associated filtering). I delivered a prototype for the OneWeek company-wide hackathon, and a patent was applied for.

Unsupervised learning • information retrieval
Founding Developer - www.unientry.org
2013

Internship with UniEntry to develop a pilot site to help sixth form students find the right university. Developed a platform that filters information from the UK's Higher Education Statistics Agency and gives recommendations based on students' registered information and grades.

Web development • agile
Education
Stanford University (Center for Professional Development) - Graduate Certificate in AI
2017 - present
  • CS234 Reinforcement Learning (Winter 2019) GPA 4.0
  • CS231n Convolutional Neural Networks for Visual Recognition (Spring 2017) GPA 3.7 - Capstone: Bounding out-of-sample objects
University College London - MEng Computer Science, First Class Honours
2011 - 2015
Imperial College London - School of Medicine - MBBS Medicine
2009 - 2011
  • I studied principles of anatomy, physiology, cellular pathways etc. Withdrew in second year to transition to computer science
Concord College, Shrewsbury - GCE A levels (Pre-A*) - AAAAab
2008 - 2009
  • Outstanding Student of the Year 2008 - Double award (Chemistry, Music) | Most imaginative hovercraft design
Competencies
Python
PyTorch
MATLAB
JavaScript
C
C#
MediaWiki
LaTeX
Sibelius
Academic interests

I am interested in all forms of data-driven decision-making, especially when there is a direct impact on quality of life or productivity, e.g. imaging and natural language systems, assistive technologies, robotics, or medical applications. I value simplicity, clarity, and the ability to adapt and learn, in both systems and people.

Machine learning
Neural networks
Reinforcement learning
Time series
Spoken languages and personal interests
English
Mandarin
Japanese
Malay
Piano