Darren Shaw Technical Lead and Full Stack Developer
darrenshaw.org / email@example.com / @shawdm / 07740 345673
I’m a technical lead and developer in IBM’s Emerging Technology group with 16 years’ experience of taking ideas from research through to proof of concept and production systems. I’ve been responsible for the successful delivery of projects for Wimbledon, Roland Garros, The US Open, RBS, Shop Direct and Homebase.
I have a reputation for making things work on difficult projects in pressure situations, leading many of IBM’s sports event innovation projects since 2013.
I am able to learn new technology quickly, particularly at a stage where it is unreliable and with little documentation. The ability to work both with a customer (presenting project pitches, running Design Thinking workshops, writing bids and requirements documents) and the development team (design, code, project management and mentoring) across the full scope of a project is something I enjoy.
Initially a weakness, mentoring is a skill I’ve developed in recent years and is now something that I take satisfaction from and have a reputation for.
2001-2017 IBM Emerging Technology
Technical lead and developer for “WhatMakesGreat”, a project using machine learning with structured and unstructured data to understand what makes a great Wimbledon champion. The output of this project was used in articles for The Telegraph, Wimbledon’s Facebook page, digital advertising at Heathrow airport, print newspapers and IBM’s marketing campaign.
Technology Used: Watson Discovery Service, Watson Personality Insights, NodeJS, DB2, Cloud Foundry/Bluemix.
RBS Hybrid Chat Bot Prototype (2016)
Lead developer for the chat user interface. The interesting challenge was to avoid the transition between bot and human being seamless, but still remain smooth. Research indicated that users want to know if they are talking to a human or machine.
US Masters, Roland Garros, ABM Amro, Wimbledon (2016)
Technical lead and developer for a real-time social media analytics system. A machine learning classifier was used to identify content relevant to each tournament and natural language processing to understand the text. At peak, the system analysed 400 messages per second. It was used by the four tournaments to direct their social media output.
Technology Used: Watson Natural Language Classifier, Alchemy Language API, Apache Spark, NodeJS, Java, Cloud Foundry/Bluemix.
Technical lead and developer for an AI chat bot. The bot was capable of answering both statistical questions (“how many French players made the second round in 1999?”) and questions that needed to be answered from unstructured data (“how do Wimbledon keep the pigeons away?”). Machine learning allowed the bot to answer unstructured data queries, combined with research technology (Controlled English) to answer structured data queries.
Technology Used: Watson Engagement Advisor, Controlled English, NodeJS, DB2, Cloud Foundry/Bluemix.
Design Thinking (2014-2017)
I’ve led Design Thinking workshops since 2014 when I piloted the technique with the Emerging Technology group. I adapted the process and led the first Design Thinking workshops with UK IBM clients. I’ve since run workshops for: Instrumental, Unilever, KPMG, Carphone Warehouse, Wimbledon, EDF, British Gas and Stop the Traffik.
Technical lead and mentor for an Extreme Blue project to prototype click and collect ordering using Homebase’s existing store infrastructure. The mobile app provided a better customer experience and a simpler process for employees. The design decisions allowed Homebase to maximise the value of their in-store staff, something online retailers could not compete with.
Shop Direct Fantasy Fashion (2013)
Technical lead and mentor for an Extreme Blue project to prototype a fantasy fashion game for Shop Direct’s “Very” brand. The project allowed customers to predict fashion trends, increasing time spent browsing Very’s catalogue, promoting social sharing and providing Shop Direct with data that could be used to predict future sales.
Technology Used: PHP, MySQL.
Technical lead for Meedan’s social network, using statistical machine translation to facilitate discussion between native English and Arabic speakers. Meedan was an early social network and the first to make use of machine translation. It allowed users to correct translations, improving both the site and the underlying machine translation algorithms, pre-dating the same approach Google use.
Technology Used: PHP, MySQL, IBM Research Machine Translation.
Awards and Publications
23 Patents Issued
Including IBM’s High Value Patent Award for “Cooperative non-repudiated message exchange in a network environment” a verifiable, shared chat transcription log.
Hermes Creative Award 2017 - Best Use of User Generated Content
I was the lead developer for “Watson Poet”, an AI based system that generated poems from social media messages. The system was used in an IBM marketing campaign, winning the Hermes award.
Best Fan Engagement - 2016 Sports Technology Awards
IBM and Wimbledon won against competition from the Rugby World Cup and European Golf Tour. The Cognitive Social Command Centre I led the development of was referenced in the reasons for IBM and Wimbledon winning the award.
Best use of Social Media - 2015 BT Sports Industry Awards
IBM and Wimbledon won the award for best use of social media in sports events. I was the technical lead on Wimbledon’s social media analytics tools, referenced in the award.
Alsbridge Innovation Award 2014
The Fantasy Fashion project I led for Shop Direct won the innovation in outsourcing award.
Building a ‘living database’ for human-machine intelligence analysis
Joint author on a paper presented at Fusion 2015. The paper proposed a new way for intelligence agencies to make use of unstructured information from a range of sources.
Computer Science BSc (Hons), 1st class, University of Portsmouth, sponsored by IBM.
I’m a (still learning) fashion and portrait photographer. I’ve been published in The Guardian, BBC Online, Hampshire Life, Guys+Girls, HairstylesOnly and I shot a cover of HairNow.