About

Professional experience

04/2024 – present AI Research Manager at Zebra Technologies (London, UK)

11/2023 – 03/2024 AI Manager at SS&C Blue Prism (London, UK)

Lead and manage the AI Labs, a team of 9 ML Research Engineers, reporting to VP Engineering.

09/2022 – 10/2023 ML Technical Lead at SS&C Blue Prism (London, UK)

Responsible for technical AI leadership across the SS&C Blue Prism product portfolio.
Provided thought leadership across strategic and operational functions, and worked with Senior Director of Product Management to establish and structure the company’s product initiatives on large language models.
Helped kick-start an incubation engineering team to rapidly deliver on the LLM roadmap.
Established an alternative approach to a high-impact document processing project whose delivery was at risk.
Continued development of Smart Vision (see below) and collaboration with engineering to productionise the prototype, resulting in the first Blue Prism Enterprise release to rely on a cloud-hosted ML service.
Technical guidance, performance management and career development for the machine learning team.

06/2021 – 08/2022 Lead ML Research Engineer at Blue Prism AI Labs (London, UK)

Established product vision for a core product feature (now released as Smart Vision) to leverage computer vision models to understand desktop screens and enable users to automate GUI application workflows.
Progressed the project from inception to the point of deploying a functional prototype to alpha customers.
Project manager leading a team of 6 ML engineers: coordinating R&D roadmap and delivery, establishing working practice, providing technical guidance (certification: AgilePM Foundation & Practitioner.
Hands-on contributor as well as technical product lead function, managing stakeholders across product management, architecture, engineering, legal, security, as well as presenting to senior management.
Technologies: Python, PyTorch, Docker, microservices architecture, Azure DevOps.

07/2019 – 05/2021 ML Research Engineer at Blue Prism AI Labs (London, UK)

Worked on 3 research projects: program synthesis from demonstrations, optical character recognition dedicated to rendered fonts on screens, and computer vision applied to application GUIs.
Independently designed, developed, and validated an improved OCR capability which has been integrated into the core product. Led stakeholder interactions, advised product engineering, and provided technical support.
Drove academic engagement: based on a series of internal talks I gave, we organised a conference tutorial on Reinforcement Learning for Information Retrieval, presented 3x at SIGIR 2021, ECIR 2021, Search Solutions 2020.

04/2018 – 06/2019 Machine Learning Lead, Core Team at Synthesized (London, UK)

Led machine learning development at a start-up focusing on data simulation to address data inefficiencies.
Designed the ML backend architecture and developed the generative models for highly semantic tabular data.
Presented technical product vision and market differentiators to early customers, partners, and investors.

04/2017 – 01/2022 Tensorforce

TensorFlow library for applied reinforcement learning, Github: 3,300 stars.
One of the three creators of the framework and the sole maintainer of the framework since 2018.
Designed the modular and flexible architecture of the framework as it is today.
Managed the open-source community by actively supporting users with the application of the framework to their reinforcement learning use cases, which has led to longer-term research collaborations and publications.

10/2015 – 01/2020 PhD in Computer Science (University of Cambridge, UK)

Research project: Evaluating visually grounded language capabilities using microworlds.
Highly commended as one of two runners-up in the UK-wide CPHC/BCS Distinguished Dissertation Award 2020.
Supervised 3 MPhil projects/theses:
- 2017/18: “Evaluating image description systems with truth-conditional semantics” (Palantir Prize awarded to Highly Commended MPhil Projects).
- 2017/18: “How clever are the models exhibiting ‘super-human’ performance on the CLEVR VQA dataset?”.
- 2016/17: “Emergence of communication in visually-grounded signalling games” (Google Prize for Best MPhil Project Report 2017).
Supervised various Computer Science modules: Advanced Algorithms, Artificial Intelligence I + II, Complexity Theory, Databases, Information Retrieval, Machine Learning and Bayesian Inference, Machine Learning and Real-World Data, Natural Language Processing, Prolog, Types.

07/2015 – 09/2015 Internship at Illumina (UK)

Research project: new models for representing genome reference data.
Implemented framework for a DNA graph sequence data structure in Python and C++.
Investigated and evaluated the use of this framework for various DNA alignment applications.

06/2014 – 09/2014 Research Assistantship at Karlsruhe Institute of Technology (Germany)

Research project: dynamic state estimation for rigid motions.
Implemented current algorithms for dynamic rigid motion estimation based on projected Gaussian distributions using Matlab.
Developed simulations to evaluate existing and newly implemented estimation techniques.

10/2015 – 01/2020 PhD Computer Science (University of Cambridge, UK)

PhD thesis: Evaluating visually grounded language capabilities using microworlds.
Supervisor: Ann Copestake, Professor of Computational Linguistics.
Highly commended as one of two runners-up in the UK-wide CPHC/BCS Distinguished Dissertation Award 2020.

10/2014 – 07/2015 MPhil Advanced Computer Science (University of Cambridge, UK)

Thesis: Active learning to rank for assessing the linguistic quality of sentences.

04/2012 – 04/2014 BSc Mathematics (Karlsruhe Institute of Technology, Germany)

10/2010 – 04/2014 BSc Informatics (Karlsruhe Institute of Technology, Germany)

Thesis: Modeling uncertain data using monads and an application to the sequence alignment problem (in cooperation with German Cancer Research Center Heidelberg).