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aberystwyth, united kingdom
It's currently 9:39 PM here
Joined May 29, 2014
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Owain J.
@owaindjones
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aberystwyth, united kingdom
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Full-stack / "many-stack" software engineer
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$558.00 USD
C Programming
Python
Linux
Shell Script
OpenGL
•
Experience
Software Engineer
Oct 2015 - Present
Responsible for the development of the MARS Portal ( https://mars.noc.ac.uk ), providing a common web interface for scientists and technicians to view oceanographic projects. This was the predecessor to the Oceanids C2 project, a UK government funded project to increase national capability involving autonomous oceanographc research. I have spent most of my time NOC developing large parts of the C2 system from the ground up. [Python, Docker, Kubernetes, Flask, PostgreSQL+TimescaleDB, ...]
Software Developer
Jul 2012 - Aug 2013 (1 year, 1 month)
Worked within the Remote Sensing Group at PML for the Industrial Year placement of my computer science degree. Developed lots of little tools used internally (lots of Bash, Python and the dreaded C-Shell), made lots of little improvements to our public websites (primarily the NEODAAS 'MultiView' website), and also handled satellite imagery data requests for our customers / other PML staff.
Software Developer
Jun 2010 - Aug 2011 (1 year, 2 months)
As some very interesting summer work, I was hired by Newport University's Cognitive Robotics Research Center, to set up a cluster of HP servers for the lab, as well as some programming work; modifying the SimSpark robotics simulator to make it a playable football simulation. I continued to assist the robotics team during their time at the National Eisteddfod for Wales.
The following year, I spent the summer at the CRRC assisting with some research for the "RoboSkin" European project. I wrote a framewo
Education
Intelligent Systems MSc
(1 year)
Computer Science BSc
(4 years)
Qualifications
Machine Learning
Coursera
2013
Publications
Oceanids C2: An Integrated Command, Control, and Data Infrastructure for [...] Marine Systems
Frontiers in Marine Science: Ocean Observation
(This paper describes in detail the large project I have been involved in since its conception 5 years ago - a unified, web-based control interface for the oceanographic research community to more effectively operate autonomous research platforms in the ocean in order to make best use of them for collecting scientific data. I was, along with the others in my small team, responsible for the design and implementation of this microservices architecture, RESTful API (OpenAPI v2/v3) based system.)
Marine Science from an Armchair: A Unified Piloting Framework for Autonomous Marine Vehicles
Conference proceedings - Oceans 2019, Marseille, France, 17-20 June 2019
The UK's National Marine Equipment Pool contains over 40 Autonomous Marine Vehicles for use by the UK marine science community. In order to deliver science consistently, the different types of vehicle each require considerable training and a large pool of trained operators to monitor and pilot these vehicles whilst at sea. In this paper, we present the development of a new unified piloting framework. Our work allows pilots to monitor and control a range of AMV types from any web-capable device.
Shadow detection for mobile robots: Features, evaluation, and datasets
Spatial Cognition & Computation, 18 (2). 115-137
Shadows have long been a challenging topic for computer
vision. This challenge is made even harder when we assume
that the camera is moving, as many existing shadow detection
techniques require the creation and maintenance of a back-
groundmodel. This article explores the problem of shadow
modelling from a moving viewpoint (assumed to be a robotic
platform) through comparing shadow-variant and shadow-
invariant image features —primarily color, texture and edge-
based features.
Identification and Production of Simple Tactile Gestures
Proceedings of the ACM/IEEE International Conference on Human-Robot Interaction, Workshop on Advances in Tactile Sensing and Touch- Based Human-Robot Interaction. Boston, Massachussetts, March 5-8, 2012
This paper describes a method for identifying and producing three
“simple” tactile gestures of “tap,” “poke” and “push”. The gesture
data is collected from a large sample size of over 200 people using
a small humanoid robot fitted with 648 capacitive sensors. A
temporal pressure profile is produced for each tactile gesture and
reproduced by the robot. The profiles show a measurable
difference in both the pressure applied and the duration of the
applied pressure between each tactile gesture. The human
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