Our Story

Our four co-founders first met at University College London during their PhD research. Having worked for prestigious financial institutions, they were frustrated by the manual machine learning developing process and manual code optimising process, which are time-consuming, resource-intensive and requires deep domain expertise. 

To overcome these difficulties, they built an AI optimisation platform to automate the entire process of creating, deploying and optimising AI as well as software performance optimisation. This is how TurinTech was born in 2018.

University College London

Meet The Team

Our Advisors

Our Research Partners

Our Awards

2020: University College London Centre for Blockchain Technologies Call for Proposals Winner

The UCL Centre for Blockchain Technologies (CBT) is the largest center in the world by number of associates. Currently, the CBT’s community comprises of over 160 research and industry associates of qualified expertise and knowledge in distributed ledger technologies. The centre focuses on technical, socio-economic and legal-policy research in distributed ledger technologies and counts more than 150 scientific publications. This Call for Proposals Competition supports and awards best community members with research grants on distributed ledger technologies.

TurinTech team’s proposal “A Fair and Independent Blockchain Evaluation Framework and Advisor” was shortlisted as one of nine winners.

16th Annual Humies Awards

The Sixteenth Annual Humies Competition, which awards $10,000 in cash prizes for computational results deemed to be competitive with results produced by human beings, but are generated automatically by computer. The awards, sponsored by John Koza (who is widely acknowledged as the "Father of Genetic Programming") annually solicit newly published papers that describe work fulfilling one or more of eight criteria, including such features as winning a regulated competition against humans or other programs, producing results that are publishable in their own right, solving a problem of indisputable difficulty in its field, and several others.

TurinTech team is one of the three award winners out of 19 candidates. Our paper “Darwinian Data Structure Selection” won the Bronze Award. This paper was published in the proceedings of the 2018 26th ACM Joint European Software Engineering Conference and Symposium on the Foundations of Software Engineering (ESEC/FSE).

Symphony Hackathon “Most Cutting-edge Technical Development ” Winner

Most Cutting-edge Technical Development-The most unique and technologically advanced project. This project will take an innovative approach in using Symphony APIs to enhance a workflow in a never-before-seen way.

2017 9th & 2016 8th International Symposium on Search-Based Software engineering Best Challenge Paper Award

The SSBSE is the premier international research symposium on Search-based Software Engineering focusing on the formulation of software engineering problems as search problems, and the subsequent use of complex heuristic techniques to attain optimal solutions to such problems. A wealth of engineering challenges - from test generation, to design refactoring, to process organization - can be solved efficiently through the application of automated optimization techniques. SBSE is a growing field - sitting at the crossroads between AI, machine learning, and software engineering - and SBSE techniques have begun to attain human-competitive results.

In 2017, TurinTech team’s “Optimising Darwinian Data Structures on Google Guava” won the Best Challenge Paper Award in technical track out of 26 submissions from 14 countries.

In 2016, TurinTech team’s “HOMI: Searching Higher Order Mutants for Software Improvement” won the Best Challenge Paper Award out of 48 submissions.

2015 10th International Workshop on Mutation Analysis

Mutation 2015 is the 10th in the series of international workshops focusing on mutation analysis. It is in conjunction with the 8th International Conference on Software Testing, Verification, and Validation (ICST 2015).

Mutation is acknowledged as an important way to assess the fault-finding effectiveness of tests. Mutation testing has mostly been applied at the source code level, but more recently, related ideas have also been used to test artifacts described in a considerable variety of notations and at different levels of abstraction. Mutation ideas are used with requirements, formal specifications, architectural design notations, informal descriptions (e.g., use cases) and hardware. Mutation is now established as a major concept in software and systems V&V and uses of mutation are increasing.