Collaborators

This page is for AI3SD Members (either individuals or companies) who are either actively looking for collaborators (either for funding applications or specific projects or to offer their technical or scientific expertise) or who are happy to be contacted regarding potential collaborations. If you wish to be listed here please either fill in our Individual Collaborators Form or our Companies Collaborators Form.    

Individual Collaborators

Dr Grant Hill - Lecturer in Theoretical Chemistry, University of Sheffield
Email: grant.hill@sheffield.ac.uk
Research Interests: Quantum chemistry method development, reaction mechanism prediction, molecular properties, intermolecular interactions, self-assembly, solvation.
Collaboration Interests: A mix of academic and industrial collaborators
Dr Ben Huckle - External Collaboration Lead, GlaxoSmithKline
Email: benjamin.d.huckle@gsk.com
Research Interests: We operate a high throughput natural product screening laboratory. The screen assesses thousands of experiments a week and requires a balance of numbers against variation of controls. We are looking for an AI& approach that replaces some of the repetitive tasks we use trained scientists to undertake such as variation monitoring, root cause identification and rectification. There is scope to also look at novel variation control and some of the decision making around progression criteria that could be suitable for AI.
Collaboration Interests: Academic.
Dr Nick Lynch - Director, Curlew Research
Email: nick.lynch@curlewresearch.com
Research Interests: AI /ML use in Drug Discovery, data, FAIR & developing value from AI/ML projects.
Collaboration Interests: Academic.
Dr. Mohammad Majid al-Rifaie - Lecturer in Data Science and Artificial Intelligence, University of Greenwich
Email: M.AIrifaie@gre.ac.uk
Blurb:Mohammad is a lecturer in computing at the School of Computing & Mathematical Sciences, University of Greenwich, as well as a visiting lecturer at Goldsmiths, University of London and a senior research fellow at the Faculty of Life Sciences & Medicine, King’s College London. He holds a PhD in computational swarm intelligence from Goldsmiths, University of London, and since 2011, he has published extensively in the field, covering both the theoretical grounds as well as the applications of Computational Swarm Intelligence (CSI) and Evolutionary Computation (EC). His work in the area has featured multiple times in the media including the BBC channel. Over the past 10 years, he has developed a unique interdisciplinary research profile with nearly 70 peer-reviewed publications including, journal papers, book chapters and conference papers on CSI and EC as well as their applications in medical imaging, data science and machine learning. Mohammad’s work has received more than 330 citations since 2011 with h-index 10 and i10-index 10.
Research Interests: Artificial Intelligence (AI), Machine Learnin (ML), Evolutionary Computation (EC), Optimisation and Tomographic Reconstruction.
Collaboration Interests: Academics: 1) Colleagues from non-AI background with a relevant problem to solve using AI, 2) Colleagues dealing with optimisation problem in a noisy environment. Companies: 1) Companies with relevant data to analyse using AI/ML and EC methods, 2) companies interested in optimising a "fitness function" with noisy search space.
Mr Chris Morris - Senior Data Analyst, Biorelate
Email: chris.morris@biorelate.com
Research Interests: Drug discovery; natural language processing; machine learning.
Collaboration Interests: Public-private partnerships.
Mr Marco Quaglio - Final year PhD candidate, Department of Chemical Engineering UCL
Email: m.quaglio@ucl.ac.uk
Research Interests: I am interested in the development of intelligent modelling methodologies to support the scientist in the mechanistic description of kinetic processes.
Collaboration Interests: Together with my advisor, Dr Federico Galvanin, we are seeking industrial partners to further validate our approaches on case studies of industrial relevance.
Mr Mani Sarkar - Independent / Freelancer (Self-employed) Software Developer / Data Engineer
Email: sadhak001@gmail.com
Blurb: Passionate software developer with 16+ years of software development experience, recent developer-turned-data scientist/ML/Data engineer with DevOps/Infra skills. Involved with a number of developer communities and F/OSS projects. Strong interests in data, analytics and visualisations. Speaker and has authored a number of blog posts. For more details see https://neomatrix369.wordpress.com/about/.
Research Interests: Artificial Intelligence, Machine Learning, Deep Learning, AI/ML/DL interpretation and explanability, Software development, data analysis and visualisation.
Collaboration Interests: Mostly industrial collaborators but happy to also work with academic collaborators.
Dr. Pinelopi Troullinou - Research Analyst, Trilateral Research
Email: pinelopi.troullinou@trilateralresearch.com
Blurb: I am a Research Analyst on the Applied Research and Innovation (ARI) team at Trilateral Research, an interdisciplinary consulting and technology development SME based in London and Ireland. Our team consists of social scientists, ethical and legal experts and data scientists that focus on transforming research into sustainable impact. We have a strong experience of leading and participating in European and nationally funded research projects and we also collaborate on tenders with public and private agencies. With a PhD in Surveillance Studies, I contribute to Trilateral’s work related to the intersection of technology and society including undertaking privacy, social and ethical impact assessments of digital technologies. This involves engaging with stakeholders throughout the process to ensure an ethics and privacy-by-design approach.
Research Interests: Privacy, ethics, impact assessments, co-design, user-requirements, technology and data science.
Collaboration Interests: A mix.
Professor Ivan Tyukin - Professor of Applied Mathematics, University of Leicester
Email: I.Tyukin@le.ac.uk
Research Interests: Correction of AI errors, quantification of decisions in AI systems, reduction of false positives, and general machine learning problems for large and high-dimensional data/applications, computer vision. In addition, I am interested in mathematical modelling, dynamical systems, adaptive systems, and inverse problems with non-convex and nonlinear parameterization.
Collaboration Interests: Open and keen to both, academic or industrial collaborations.

Institutional Collaborators
The Cambridge Crystallographic Data Centre
Main Point of Contact: Jason Cole - cole@ccdc.cam.ac.uk
Blurb:  The Cambridge Crystallographic Data Centre (CCDC) develops and maintains The Cambridge Structural Database (CSD) along with knowledge-based software used by structural chemists in academia and industry worldwide. The CSD is the world’s most comprehensive database of experimentally-determined 3D crystal structures and will soon be able to boast more than 1 million entries. Entries in the CSD are enriched with bibliographic, chemical and physical property information, vital for meaningful interpretation and reuse. Machine access to the data and knowledge in the CSD is possible through the CSD Python API.  The CCDC is open to the discussion of collaborations that combine the data in the CSD with AI technologies in the pursuit of new discoveries and insights relevant to the design of chemicals and materials.
Research Interests: Structural chemistry; Structure-based drug design; Prediction of solid form properties; Design of functional materials.
Collaboration Interests: Academic and/or Industrial.

Institutional Collaborators
Sosei Heptares
Blurb:  Sosei Heptares is an international biopharmaceutical group focused on the design and development of new medicines originating from its proprietary GPCR-targeted StaR® technology and Structure-Based Drug Design platform capabilities.
Main Point of Contact: Chris de Graaf - chris.degraaf@soseiheptares.com
Research Interests: Computer-Assisted Drug Design (CADD), GPCR Structure-Based Drug Design (SBDD), Structural Cheminformatics, Artificial Intelligence (AI) driven Drug Discovery.
Collaboration Interests: A mix.