Difference between revisions of "CV:General"

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{{CVSectionHeader|title = Professional experience}}
 
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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
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  |date = 2017 - 2021
 
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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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* Designed and implemented a distributed messaging framework to support pilot-from-shore capabilities for underwater vehicles.
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* Developed a controller to distribute energy from a hydraulic powerplant in a tractor-drill combine depending on workload or sensor input.
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* Prototyped a Pytorch-based computer vision system for robotic survey of undersea pipelines.
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{{CVMinor|Embedded systems / distributed systems {{*}} imaging }}
 
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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.
+
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.
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{{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 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 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.
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{{CVMinor|Unsupervised learning {{*}} information retrieval}}
 
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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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{{CVMinor|Web development {{*}} agile}}
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|title = JP Morgan Spring Week 2013
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|date = 2013
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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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*AA274A Principles of Robot Autonomy I (Fall 2020) {{CVMinorSpan | GPA 4.0}}
*CS234 Reinforcement Learning (Winter 2019) - ongoing
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*CS234 Reinforcement Learning (Winter 2019) {{CVMinorSpan|GPA 4.0}}
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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, etc. before withdrawing 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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*Outstanding Student of the Year 2008 - Double award (Chemistry, Music) {{!}} Most imaginative hovercraft design
 
*Outstanding Student of the Year 2008 - Double award (Chemistry, Music) {{!}} Most imaginative hovercraft design
 
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{{CVInlineBlock|PyTorch}}
 
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{{CVInlineBlock|C / C++}}
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{{CVInlineBlock|C#}}
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{{CVInlineBlock|TypeScript}}
 
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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}}
 
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{{CVInlineBlock|English}}
 
{{CVInlineBlock|English}}
 
{{CVInlineBlock|Mandarin}}
 
{{CVInlineBlock|Mandarin}}
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{{CVInlineBlock|Japanese}}
 
{{CVInlineBlock|Malay}}
 
{{CVInlineBlock|Malay}}
{{CVInlineBlock|Japanese}}
 
 
{{CVInlineBlock|Piano}}
 
{{CVInlineBlock|Piano}}
 
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<noinclude>[[Category:CV]]</noinclude>
 
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Latest revision as of 00:05, 27 January 2022

Professional experience
Research Software Development Engineer - Ocean 5 Technologies Singapore
2017 - 2021
  • Designed and implemented a distributed messaging framework to support pilot-from-shore capabilities for underwater vehicles.
  • Developed a controller to distribute energy from a hydraulic powerplant in a tractor-drill combine depending on workload or sensor input.
  • Prototyped a Pytorch-based computer vision system for robotic survey of undersea pipelines.
Embedded systems / distributed systems • imaging
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
  • AA274A Principles of Robot Autonomy I (Fall 2020) GPA 4.0
  • 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
C / C++
C#
TypeScript
JavaScript
MediaWiki
LaTeX
Sibelius
Spoken languages and personal interests
English
Mandarin
Japanese
Malay
Piano