Difference between revisions of "CV:General"

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  |title = Research Software Development Engineer
 
  |title = Research Software Development Engineer
  |sub = <small><i> - Ocean 5 Technologies</i></small>
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  |sub = <small><i> - Ocean 5 Technologies Singapore</i></small>
 
  |date = 2017 - present
 
  |date = 2017 - present
 
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Working with a team of electrical and mechanical engineers, we developed a tractor system and a drill-like 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 and programming distributed embedded control systems for pilot input, hydraulics, engine, and power, as well as the Python backend and UI of the analytics platform.
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* Designed and implemented a distributed messaging framework to support pilot-from-shore capabilities for underwater vehicles.
{{CVMinor|CAN bus {{*}} RS-232 {{*}} embedded systems {{*}} distributed systems}}
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* Developed a controller for a tractor-drill combine while collaborating with E&E and mechanical engineers, to make certain types of rocky terrain feasible for agriculture.
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{{CVMinor|Embedded systems {{*}} distributed systems and messaging }}
 
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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, which has since evolved to be based on convolutional neural nets.
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Completed a 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, which has since evolved to be based on convolutional neural nets.
 
{{CVMinor|Supervised learning {{*}} imaging}}
 
{{CVMinor|Supervised learning {{*}} imaging}}
 
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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].
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Completed a 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 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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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.
 
{{CVMinor|Unsupervised learning {{*}} information retrieval}}
 
{{CVMinor|Unsupervised learning {{*}} information retrieval}}
 
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{{CVMinor|Web development {{*}} agile}}
 
{{CVMinor|Web development {{*}} agile}}
 
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|title = JP Morgan Spring Week 2013
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|date = 2013
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{{CVContent|
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Competition to implement a performant implied volatility calculator. Team awarded second-best for code review and performance, and best for presentation.
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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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*CS234 Reinforcement Learning (Winter 2019) {{CVMinorSpan|GPA 4.0}}
*CS234 Reinforcement Learning (Winter 2019) - ongoing
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*CS231n Convolutional Neural Networks for Visual Recognition (Spring 2017) {{CVMinorSpan|GPA 3.7}} - Project: <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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  |title = University College London  
 
  |title = University College London  
  |sub = <small><i> - MEng Computer Science, First Class Honours</i></small>
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  |sub = <small><i> - MEng Computer Science, First Class</i></small>
 
  |date = 2011 - 2015
 
  |date = 2011 - 2015
 
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*Final year research project - <i>[http://lqkhoo.com/wiki/index.php/Main_Page#Predicting_Personality_from_Twitter_.282015.29 Predicting Personality from Twitter]</i>
 
*Final year research project - <i>[http://lqkhoo.com/wiki/index.php/Main_Page#Predicting_Personality_from_Twitter_.282015.29 Predicting Personality from Twitter]</i>
 
*Information Retrieval and Data Mining Prize (research and poster session)
 
*Information Retrieval and Data Mining Prize (research and poster session)
*[http://www.cs.ucl.ac.uk/computer_science_news/article/undergraduate-research-group-projects-prize-winners/ Best Undergraduate Research Group Project of the Year] - <i>[http://lqkhoo.com/wiki/index.php/Main_Page#Task_Identification_using_Search_Engine_Query_Logs_.282014.29 Task Identification Using Search Engine Query Logs]</i>
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*[https://web.archive.org/web/20140610022250/http://www.cs.ucl.ac.uk/computer_science_news/?tx_ttnews%5Btt_news%5D{{=}}1144&cHash{{=}}4617ee2bfc0eb070cd6a367203945ace Best Undergraduate Research Group Project of the Year] - <i>[http://lqkhoo.com/wiki/index.php/Main_Page#Task_Identification_using_Search_Engine_Query_Logs_.282014.29 Task Identification Using Search Engine Query Logs]</i>
*Developed a platform-agnostic [http://lqkhoo.com/wiki/index.php/Main_Page#RoboHome home automation system] for remote surveillance, command and control
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*Developed an Android app for the Restless Beings charity to conduct field studies on children in poorly-developed countries
 
*Developed an Android app for the Restless Beings charity to conduct field studies on children in poorly-developed countries
 
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*I studied principles of anatomy, physiology, cellular pathways etc. Withdrew in second year to transition to computer science
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*Withdrew in second year to transition to computer science.
 
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{{CVInlineBlock|MATLAB}}
 
{{CVInlineBlock|MATLAB}}
 
{{CVInlineBlock|JavaScript}}
 
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{{CVInlineBlock|C}}
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{{CVInlineBlock|C / C++}}
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{{CVInlineBlock|C#}}
 
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{{CVInlineBlock|MediaWiki}}
 
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{{CVInlineBlock|LaTeX}}
 
{{CVInlineBlock|LaTeX}}
 
{{CVInlineBlock|Sibelius}}
 
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|title = Academic interests
 
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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.
 
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{{CVInlineBlock|Machine learning}}
 
{{CVInlineBlock|Neural networks}}
 
{{CVInlineBlock|Reinforcement learning}}
 
{{CVInlineBlock|Time series}}
 
 
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Revision as of 16:54, 26 March 2020

Professional experience
Research Software Development Engineer - Ocean 5 Technologies Singapore
2017 - present
  • Designed and implemented a distributed messaging framework to support pilot-from-shore capabilities for underwater vehicles.
  • Developed a controller for a tractor-drill combine while collaborating with E&E and mechanical engineers, to make certain types of rocky terrain feasible for agriculture.
Embedded systems • distributed systems and messaging
R&D Scientist - Digital:MR
2015

Completed a 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

Completed a 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
JP Morgan Spring Week 2013
2013

Competition to implement a performant implied volatility calculator. Team awarded second-best for code review and performance, and best for presentation.

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 - Project: Bounding out-of-sample objects
University College London - MEng Computer Science, First Class
2011 - 2015
Imperial College London - School of Medicine - MBBS Medicine
2009 - 2011
  • 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
Spoken languages and personal interests
English
Mandarin
Japanese
Malay
Piano