61 Works

The Wales Immunology Teaching Toolkit

Nigel Francis, Tom Wilkinson & Dave Ruckley
The Wales Immunology Teaching Toolkit is a collaborative project between Cardiff and Swansea Universities. The open Canvas course hosts a range of immunology and general lab teaching resources that can be freely used and embedded either into websites or VLEs.
All resources can be accessed from: Wales Immunology Teaching Toolkit

AI3SD Video: Data-Driven Molecular Design in Computational Toxicology

Barbara Zdrazil
Timely drug discovery and toxicology approaches have seen a rise in strategies which use data as a basis for decisions at various stages. Such approaches include (automated) data integration and curation efforts, predictive machine learning approaches, as well as structure-based molecular design strategies that make use of the wealth of publicly available data sources and data types. In this talk, various computational workflows which have been developed in my lab for addressing research questions related...

AI3SD Video: One does not simply \"digitise scientific research\": The challenges and opportunities of technology in the 21st century

Samantha Kanza & Nicola Knight
We live in a technology driven era where emails, electronic systems and smart assistants are commonplace, and yet despite this there is an abnormally large amount of scientific research that is still recorded on paper. Additionally, even when data and research is captured electronically, it is of limited use unless it is adequately stored, labelled and made available in a machine-readable format. This talk explores some of the challenges and opportunities of digitising scientific research...

AI3SD Video: Organising your Networks & Projects

Samantha Kanza & Nicola Knight
This talk will cover tips and tricks for how to organise your networks and projects, including how to set up your communication methods, how to structure and organise all of the different types of data that you collect and best practices for project management.

AI3SD Video: Event detection in single-molecule data - how to find molecular signatures without (too many) prior assumptions

Tim Albrecht
Data from single-molecule experiments, such as from current-time or conductance-distance spectroscopy or sensors, are often "noisy" and characterised by complex molecular behaviour. In some cases, extracting the physically relevant information may be based on supervised approaches, i.e. where labelled data are available for training. In other cases, such data are either not available or it may simply be undesirable to make a priori assumptions about the molecular characteristics, for example to prevent loss of information...

AI3SD Video: Equality, Diversity & Inclusion in Networks: Developing your inclusive approach

Debra Fearnshaw & Jeremy G. Frey
This session will give delegates a framework in which to consider how they can develop an inclusive approach to their work, team and research. This talk will provide some examples of how to do this and inspire delegates to develop their own approaches.

AI3SD Video: Inference from Medical Images: Subspaces for Low Data Regimes

Mahesan Niranjan
Unlike in the field of visual scene recognition, where tremendous advances have taken place due to the availability of very large datasets to train deep neural networks, inference from medical images is often hampered by the fact that only small amounts of data may be available. When working with very small dataset problems, of the order of a few hundred items of data, the power of deep learning may still be exploited by using a...

AI3SD Video: Interpretable Machine Learning for Materials' Design and Characterisation

Keith Tobias Butler
"Where is the knowledge we have lost in information?" T.S. Eliot, The Rock
Machine learning (ML) and artificial intelligence (AI) are the subjects of wildly differing opinions on utility and potential impact. Depending who we talk to ML is the solution to almost every human challenge, from open boarders to pandemic control, or presents an existential crises for the species. In materials science the polarisation is perhaps less extreme, but nonetheless pervasive, while the numbers of...

AI3SD video: AI standardization to enable digital development

Emelie Bratt
Standardisation is often viewed hand in hand with legislation but there are significant differences in the purpose each serves. While both look to deliver a common level of safety and trust for industry as well as consumers standards are voluntary in nature. The role of standards is to respond to common problems identified across industry, through collaborative consensus base processes. It looks to produce guidance to bridge gaps in understanding and practices across sectors and...

AI3SD video: curated large inorganic datasets of reconnected InChI, InChI and IUPAC name

Thomas Allam
Speaking about my experience with the Skills4Scientists Seminar series on e-chemistry, networking and careers and the AI4SD internship itself.

AI4SD Video: Opportunities for ECRs in the Royal Society of Chemistry

Robert Bowles
Develop your career beyond your research by exploring your career options and how to get involved with the RSC.

AI3SD Video: The Variational Quantum Eigensolver - progress and near term applications for quantum chemistry

Jules Tilly
The Variational Quantum Eigensolver is among the most promising near term applications for quantum computing. It offers the possibility to model some wave functions accurately in polynomial time. Despite this, many hurdles and open questions remain. We will go through these questions, try discussing possible answers and the direction of research. After this we will discuss recent applications of the methods and integration to quantum chemistry methods such as CASSCF and experimentation on quantum computers.

AI3SD Video: Audacity of huge: Machine Learning for the discovery of transition metal catalysts and materials

Heather Kulik & Jeremy G. Frey
I will discuss our efforts to use machine learning (ML) to accelerate the computational tailoring and design of transition metal complexes and metal-organic framework (MOF) materials. One limitation in a challenging materials space such as open shell, 3d transition metal chemistry is that ML models and ML-accelerated high-throughput screening traditionally rely on density functional theory (DFT) for data generation, but DFT is both computationally demanding and prone to errors that limit its accuracy in predicting...

AI3SD Video: Quantum Machine Learning

Anatole von Lilienfeld
Many of the most relevant observables of matter depend explicitly on atomistic and electronic details, rendering a first principles approach to computational materials design mandatory. Alas, even when using high-performance computers, brute force high-throughput screening of material candidates is beyond any capacity for all but the simplest systems and properties due to the combinatorial nature of compound space, i.e. all the possible combinations of compositional and structural degrees of freedom. Consequently, efficient exploration algorithms exploit...

AI3SD Video: What a Medicinal Chemist Needs to Know about Explainable Artificial Intelligence

Alexander Dossetter
The latest developments in artificial intelligence (AI) have arrived into an existing state of creative tension between computational and medicinal chemists. At their most productive, medicinal and computational chemists have made significant progress in delivering new therapeutic agents into the clinic. However, the relationship between these communities has the prospect of being weakened by application of over-simplistic AI methods which, if they fail to deliver, will reinforce unproductive prejudices. AI systems are action orientated; they...

AI3SD Video: Hints and tips for optimising your researchfish data

Gavin Reddick
Gavin Reddick (Chief Analyst at Interfolio UK) will talk about practical things that researchers and universities can do to reduce the amount of time and effort needed to complete your annual reporting to funders via researchfish platform, as well as helping to ensure more accurate and useful data is collected. He will also touch on how you can get from researchfish and things you might want to use it for.

AI3SD Video: Capturing and Tracking your Outputs

Samantha Kanza & Nicola Knight
This talk will look at how to capture a wealth of different outputs. Gone are the days when journal papers were the only items to be considered outputs, there are so many different types of outputs that can be produced when working as part of a Network or large scale project. These can include videos, reports, presentations, posters, interviews and much more. This talk will look at creating templates for some of these items, how...

AI3SD Video: AI and multi-omics discovery science: A case study in understanding ageing at a systems level

Janna Hastings
Metabolism is central to all processes of life and the metabolome -- large-scale measurement of the quantities of small molecular entities in cells and tissues -- gives a readout of cellular functioning at a point in time. Harnessing metabolomic information together with transcriptomic information about gene expression allows for multi-level insights into genetic dysregulation and its cellular effects. I will describe a multi-omics approach based on genome-scale modelling that is able to integrate the two...

The Wales Immunology Teaching Toolkit

Nigel Francis, Tom Wilkinson & Dave Ruckley
The Wales Immunology Teaching Toolkit is a collaborative project between Cardiff and Swansea Universities. The open Canvas course hosts a range of immunology and general lab teaching resources that can be freely used and embedded either into websites or VLEs.
All resources can be accessed from: Wales Immunology Teaching Toolkit

AI3SD Video: Interpreting opacity: understanding gaps in our explanations of artificial neural networks

William Mcneill
We know everything that goes on within artificial neural networks. We tend to know of all the data such systems have been trained on. And designers will be aware of the various design decisions, training algorithms and techniques that went into their construction, too. At the same time, leading AI designers tell us that their systems are in some sense uninterpretable, inexplicable or opaque. That's puzzling. Drawing on discussions in the philosophy of neuroscience and...

AI3SD Video: AI insights from billions of dollars of ready-cleaned data

Will Bowers
Two of the greatest pain points in Artificial Intelligence (AI)-assisted research workflows are data quantity and data organisation. Estimates place 60-80% of time in data science workflows is simply cleaning and arranging the data, dependent on researcher skill and the type of data. As AI relies on pattern recognition, the larger the dataset, the more likely the algorithm is to recognise a useful pattern. Due to organised unput via the Studies ELN and the underlying...

AI3SD video: internship talk - making music with automated processes and AI for the AI3SD Network

Mubin Kazmi
Making the music for the AI3SD Network was an exciting and daunting project. In my talk I'll walk through the process I used to find and create ideas for the music, while talking about the sounds and technologies I used to make a successful musical package.

AI3SD video: the summer school, but not as we know it!

Martin Elliot
How to engage with a summer school in the COVID 19 world.

AI3SD video: internship talk-high-throughput generation of chemical isomers for the development of molecular models of biocrude oils

Francisco Martin-Martinez, Jeremy G. Frey & Mahesan Niranjan
The identification of chemical species in complex fluid materials like biocrude oils, is problem that can be largely solved by a computational optimisation of a molecular design space to expand the limited experimental data. This is specially useful due to the intrinsic difficulties to characterise this bitumen-like materials. We used available experimental data to generate molecular models of any biocrude oil from different biomass sources (e.g., chitin, coffee grounds, algae), and we expand the molecular...

AI3SD video: Bayesian optimisation in chemistry

Rubaiyat Khondaker
Recent work on the problem of optimising the yield of a chemical reaction has focused on Bayesian optimisation methods. We extend this work in several directions by: determining the effect on the performance of the optimiser of altering the acquisition function and batch size; testing the robustness of the optimiser by applying it to other existing reaction yield data sets; and applying the optimiser to the new problem domain of molecular power conversion efficiency in...

Registration Year

  • 2022

Resource Types

  • Audiovisual


  • University of Southampton
  • University of Nottingham
  • University of Cambridge
  • Royal Society of Chemistry
  • University College London
  • University of Kent
  • University Hospitals Birmingham NHS Foundation Trust
  • University of North Florida
  • University of Leeds
  • European Bioinformatics Institute