Leading Sanofi’s Biologics AI Moonshot (BioAIM) https://www.youtube.com/watch?v=yIn3GECO82A, which aims to accelerate biologics discovery by leveraging machine learning and artificial intelligence.

Leading the development of an end-to-end data management and analysis strategy and capabilities that will significantly impact the delivery of the novel biologics drugs of the future. This includes building an interdisciplinary team at the intersection of data management, lab automation, computational modelling and machine learning.

Biologics Engineering is responsible for the discovery and optimisation of next generation biological drug candidates for all key therapy areas across AstraZeneca, and for developing in-house biologics discovery platforms and novel drug modalities to address unmet medical needs.

Led research in Biological Computation at Microsoft, developing methods for understanding and programming information processing in biological systems:

• Jointly led scientific research with Dave Zhang on predicting DNA interactions from sequence (Nature Communications 2021, Nature Chemistry 2018).
• Jointly led scientific research with Paul Grant on programming cell populations (Nature Communications 2020). Main experiments performed in the Microsoft Station B wet lab.
• Led a team to develop the Visual DSD programming language for designing molecular circuits. Developed computational methods and incorporated them into the language. Used the language with collaborators to make scientific advances (Nature Nanotechnology 2013, 2017, 2019).
• Led a team to develop the Visual GEC programming language for designing genetic circuits. Developed computational methods and incorporated them into the language. Used the methods with collaborators to make scientific advances (Molecular Systems Biology 2016, Nature Communications 2018, 2020).

Led the creation of academic and industrial partnerships:

• Led a team to create a research partnership between Station B and the Novartis Cell & Gene Therapy division (Financial Times 2019).
• Led a team to develop the Station B platform and create research partnerships with Princeton University and Oxford Biomedica (Nature Biotechnology 2019, Fierce Biotech 2019, Bloomberg 2019).
• Led a team to establish the Station B initiative, with the aim of developing a platform for programming biological systems (Microsoft Research 2019, Financial Times 2019). Secured Microsoft funding to grow Station B to a 10-person team.
• Led a team to create the first molecular biology lab at Microsoft (Fast Company 2016).
• Proposed the concept for a Microsoft Office Envisioning video on a future version of Office for biotechnology. 2M views (Office Envisioning 2015).

Led strategy and communication with senior leadership:

• Strategic presentations to Microsoft senior leadership to obtain buy-in and financial support for Synthetic Biology research over a 10-year period. Included presentations to Microsoft’s CEO, President, Senior Leadership Team and Board of Directors.
• Worked extensively with Business Development and Corporate Strategy to create a strategic vision for Synthetic Biology at Microsoft, which enabled sustained investment and growth in Synthetic Biology research.

Created the Visual DSD programming language for designing nucleic acid circuits (Royal Society Interface 2009) and jointly created the Visual GEC programming language for designing genetic circuits (Royal Society Interface 2009).

Led a team to develop the Stochastic Pi Machine (SPiM) programming language and used it to model key biological processes, including gene regulatory networks (HFSP Journal 2008), the polymerisation of actin filaments (ENTCS 2009), rho GTP binding proteins (Theoretical Computer Science 2009), Epidermal Growth Factor Receptor networks (BMC Systems Biology 2009) and antigen presentation to T-cells (PLoS Computational Biology 2011).

Created the Stochastic Pi Machine (SPiM) programming language for computational modelling of biological systems. The language is based on a formal model of concurrency known as the pi-calculus, and the simulation algorithm is based on stochastic theory of chemical kinetics.

Developed a formal specification of the language syntax and semantics (CMSB 2007). Developed a graphical formalism for models in the language (TCSB 2006) and their execution traces (ENTCS 2008). Used the language for compositional modelling of synthetic gene circuits (TCSB 2006).

Contributing author and co-editor of the 2020 Science Report, highlighted in (Nature 2006). Supervised by Luca Cardelli and Stephen Emmott.

Department Scholarship. Overseas Research Scholarship. Winner in the Imperial College Ideas Challenge 2001. Thesis title Specifying and Implementing Secure Mobile Applications in the Channel Ambient System. Supervised by Susan Eisenbach, Nobuko Yoshida and Bashar Nuseibeh.

Award for outstanding dissertation. Scholarship for outstanding examination results. Dissertation title: Implementation of a Mobile Agent Language Based on Pi-Calculus. Supervised by Peter Sewell and Paweł Wojciechowski.

Final year spent at the University of Cambridge as part of a joint honours programme.

Award for best examination results.

National scholarship for A-level results. National award for best O-level results.