Keith Tunstead
Senior Software Engineer at Fidelity Investments
Carlow, Ireland
Summary
👤
Senior🎓
Top SchoolKeith Tunstead is a Senior Software Engineer with nine years of hands-on experience building full-stack systems, machine learning models, and DevOps pipelines across startups and enterprise teams. He combines a Masters in Computer Science from Trinity College Dublin with practical experience shipping production APIs, realtime fintech services, and Web3 proofs-of-concept using AWS, Python, NodeJS, and microservices. A significant open-source contributor, he is the second-largest contributor to the popular pyspider web crawler, leading the project’s Python 3 port and improving its test and CI infrastructure. Keith also brings hardware and manufacturing experience from founding a briquette business and later repairing industrial electronics, which informs pragmatic, end-to-end problem solving. At Veritas he helped build a battery failure predictor that cut training time dramatically, and at TheOperator he cut response times and hosting costs through smart caching and spot fleet deployment. Based in Carlow, Ireland, he blends startup agility with disciplined engineering and a curiosity for systems both software and physical.
9 years of coding experience
2 years of employment as a software developer
Leaving Certificate, 515/610 Points (84% Overall), Leaving Certificate, 515/610 Points (84% Overall) at Carlow CBS Secondary SchoolBA(Mod), Computer Science, 2.1, BA(Mod), Computer Science, 2.1 at Trinity College DublinUdemy Academy
Github Skills (10)
testing10
unit-testing10
sqlalchemy10
unit-test10
python10
database-management9
couchdb8
amqp8
pytest7
crawler7
Programming languages (7)
Github contributions (5)
binux/pyspider
Oct 2019 - Nov 2019
A Powerful Spider(Web Crawler) System in Python.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:196 commits, 3 PRs, 5 comments in 15 days
Contributions summary:Keith's primary contribution involved porting the `pyspider` project to Python 3.6, demonstrated by modifications to the `setup.py` file, updating dependencies, and incorporating `unittest` across various test files. They also made significant changes by upgrading `python-six`, and making fixes related to database connections and CouchDB configurations. Additional commits reflect efforts to enhance the testing infrastructure, including integrating Travis CI tests.
pythonweb-crawlerspiderweb-spiderpython3
BeelGroup/Guided-Learning
Jan 2019 - Mar 2019
We present the the concept of Guided Learning, which out-lines a framework in which a reinforcement learning agent can effectively’ask for help’ as it encounters stagnation. Either a human or expert agentsupervisor can then effectively ’guide’ the agent as to how to progressbeyond the point of stagnation. This guidance is then encoded in a novelway using a separately trained neural network referred to as a ’TaughtResponse Memory’ that can be recalled when another ’similar’ situa-tion arises in the future. This paper applies Guided Learning on topof an evolutionary algorithm but also shows how Guided Learning isalgorithm independent and can be applied in any reinforcement learn-ing context. The results show that our initial implementation of GuidedLearning provided in this paper gives superior performance and yields,on average, an increase of 136% in the rate of progression of the mostfit genome with best and worst case results yielding 137% and 110%respectively and an average increase of 112% in rate of progression forthe average genome with best and worst case results of 558% and 47%respectively. All results were achieved with minimal guidance. Such re-sults occur because the agent can exploit more information and thus,the need for exploration of the solution space is reduced. The results ob-tained show good promise for Guided Learnings potential as such resultswere obtained with only a partial implementation and much future workstill remains.
Contributions:52 commits in 1 month
memorygenomedeep-reinforcement-learningworstworst-case
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