Difference between revisions of "CV:General"

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Development of control hardware and an analytics platform for GPS-and-sensor-equipped agricultural vehicles to be deployed in remote locations with unreliable internet access. Part of a government initiative to improve accountability and yield through technology and data. Working with a team of electrical and mechanical engineers, we developed a tractor system and a drill-like assembly for making certain rocky terrain feasible for agriculture. I am responsible for building and programming distributed embedded control systems for pilot input, hydraulics, engine, and power, as well as the Python backend and UI.
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Development of control hardware and an analytics platform for GPS-and-sensor-equipped agricultural vehicles, for deployment in remote locations with unreliable internet access. Part of a government initiative to improve accountability and yield through technology and data. Working with a team of electrical and mechanical engineers, we developed a tractor system and a drill-like assembly for making certain rocky terrain feasible for agriculture. I am responsible for building and programming distributed embedded control systems for pilot input, hydraulics, engine, and power, as well as the Python backend and UI.
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Feasibility study on sentiment analysis of images in social media, funded by a research grant from [https://www.gov.uk/government/organisations/innovate-uk 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, that has since evolved to be based on convolutional neural nets.
 
Feasibility study on sentiment analysis of images in social media, funded by a research grant from [https://www.gov.uk/government/organisations/innovate-uk 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, that has since evolved to be based on convolutional neural nets.
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Research internship through the Bright Minds Intern Competition programme in the Machine Learning and Perception research group, working with Principal / Senior Researchers  [https://www.microsoft.com/en-us/research/people/pkohli/ Pushmeet Kohli], [http://research.microsoft.com/en-us/people/yobach/ Yoram Bachrach], [http://www.ulrichpaquet.com/ Ulrich Paquet], and [http://www.radlinski.org/ Filip Radlinski].
 
Research internship through the Bright Minds Intern Competition programme in the Machine Learning and Perception research group, working with Principal / Senior Researchers  [https://www.microsoft.com/en-us/research/people/pkohli/ Pushmeet Kohli], [http://research.microsoft.com/en-us/people/yobach/ Yoram Bachrach], [http://www.ulrichpaquet.com/ Ulrich Paquet], and [http://www.radlinski.org/ Filip Radlinski].
  
I worked on Project SmartFence - an application for web access control. Users block or allow the few sites they know about and SmartFence infers the suitability for 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.
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I worked on Project SmartFence - an application for web access control. Users simply block or allow a few sites they know about, and SmartFence infers the suitability of the rest of the web for them. 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.
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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.
 
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.
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*I studied principles of anatomy, physiology, etc. before withdrawing in second year to transition to computer science
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*I studied principles of anatomy, physiology, etc. Withdrew in second year to transition to computer science
 
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*Outstanding Student of the Year 2008 - Double award (Chemistry, Music) {{!}} Most imaginative hovercraft design
 
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{{CVInlineBlock|Japanese}}
 
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{{CVInlineBlock|Piano}}
 
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Revision as of 16:09, 12 January 2019

Li Quan Khoo Icon-mail.pngchangtau2005@gmail.com  •  li.khoo.11@ucl.ac.uk
Icon-home.pnghttp://lqkhoo.com Icon-github.pnghttps://github.com/lqkhoo
Icon-linkedin.pnghttp://www.linkedin.com/pub/li-quan-khoo/89/a27/8aa
Professional experience
Research Software Development Engineer - Ocean 5 Technologies
2017 - present

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

Keywords: 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, that has since evolved to be based on convolutional neural nets.

Keywords: 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 simply block or allow a few sites they know about, and SmartFence infers the suitability of the rest of the web for them. 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.

Keywords: 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.

Keywords: Web development, agile
Education
Stanford University (Center for Professional Development) - Graduate Certificate in AI
2017 - present
  • CS231n Convolutional Neural Networks for Visual Recognition (Spring 2017) - Capstone: Bounding out-of-sample objects
  • CS234 Reinforcement Learning (Winter 2019) - ongoing
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, 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++
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