67 Works

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.

AI3SD Video: Finding Small Molecules in Big Data

Emma Schymanski
The environment and the chemicals to which we are exposed is incredibly complex, with over 111 million chemicals in the largest open chemical databases, 300,000 estimated in global inventories of high use, and over 70,000 in household use alone. Detectable molecules in environmental samples, metabolomics and exposomics can now be captured using high resolution mass spectrometry (HRMS), which provides a âsnapshotâ of all chemicals present in a sample and allows for retrospective data analysis through...

AI3SD Video: A vision of Medicinal Chemistry for the future

Lewis Vidler
Historically, medicinal chemistry and computational chemistry have been separate roles within a drug discovery organization requiring differing backgrounds and expertise. Increasingly in the modern world and going forwards these skillsets are coming closer and closer together, empowered by automation and increasingly advanced computational methods. Over time, there has been an increase in the amount of time a medicinal chemist spends at a computer compared with time in the lab which is expected to continue. For...

AI3SD Video: Using Scopus and SciVal to track your research impact and find collaborators

Christopher James
During this presentation, Chris James, a Senior Product Manager for Elsevier, will introduce Scopus and SciVal and demonstrate how the products can be used as part of your workflow to track your and others' research impact and identify peers for potential collaboration opportunities. Information gathered from these products can also be used to help support grant applications and identify relevant parallel areas of research. This session will be comprised of a short presentation, followed by...

AI3SD Video: Making sense of highly flexible molecular simulations: Where AI can help and where not

Christof Jäger
With simulating the dynamic behaviour of ever bigger molecular systems for longer simulation time we simultaneously achieve more realistic timescales and gain much better insights into the physiological relevant time dependent behaviour of molecular systems, but also generate significantly more data and thus pose new challenges for filtering noise and analysing the simulation data. In simulation analysis and data dimensionality reduction we often rely on linear dependencies and behaviour within the simulated timespan. This generally...

AI3SD Video: Discovery of synthesisable organic materials

Steven Bennett
The computational discovery of new materials with useful properties is currently hindered by the difficulty in transitioning from a computational prediction to synthetic realisation. Attempts at experimental validation are often time-consuming, expensive, and frequently, the key bottleneck of material discovery.[1] Porous organic cages (POCs) have been discovered as a possible alternative material for molecular separations, catalysis, and sensing applications.[2] For POCs, a priori property prediction is possible,[3] however, it can be time-consuming and computationally expensive...

AI3SD Video: RSC CICAG \"Who we are, what we do and what we are planning\"

Chris Swain & Jeremy G. Frey
The Royal Society of Chemistry Chemical Information and Computer Applications Group (CICAG) is one the the RSC's member led interest groups. The storage, retrieval, analysis and preservation of chemical information and data are of critical importance for research, development and education in the chemical sciences. CICAG works to support users of chemical information by providing training workshops, conferences highlighting the latest research in the area, and to promote wider recognition of the importance of chemical...

AI3SD Video: Introducing the Future Blood Testing Network

Weizi (Vicky) Li
The Future Blood Testing Network+ is a new Network funded by EPSRC. We are aiming to build a multi-disciplinary community to develop digital health technologies for remote, rapid, affordable and inclusive monitoring and personalised analytics. This presentation will introduce our Network, detailing our plans for the next three years, in particular highlighting the funding calls and opportunities that will be relevant to the AI4SD Community.

AI3SD Video: Sharing Data Science Solutions Across Domains via Patterns

Sarah Callaghan
We are generating more data than we ever have before and are developing new and exciting ways to derive new insights from them. Sharing our research is a fundamental part of expanding humanity's knowledge, as well as ensuring that researchers get credit for their work. In this talk I will introduce Patterns, the data science journal from Cell Press, along with wider discussions about the current state of AI and data science, and how to...

AI3SD Video: Translating innovations out of the lab and into the clinic: the importance of data curation, AI and ML?

Jennifer R. Hiscock & Thomas Allam
Our novel patented (European Patent Application No. 18743767.8, U.S. Patent Application No. 16/632,194), Supramolecular Self-associating Amphiphile (SSA) platform technology currently contains a library of ≈120 molecules (Figure 1), invented by J. Hiscock in 2016, has since been developed by an international, transdisciplinary team of ≈50 academic/industrial/governmental scientists, social scientists and clinicians. To date this molecular technology has been shown to:

1.act as broad-spectrum antimicrobials;1-6
2. increase the efficacy of other antibiotic/antiseptic agents and anticancer agents against bacteria7...

Humans of AI3SD: Dr Nicholas Watson

Michelle Pauli & nicholas watson
Dr Nicholas Watson is an associate professor of chemical engineering at the University of Nottingham and his research is focused on data-driven in-process sensing to deliver sustainable, safe and productive food manufacturing systems.

In this Humans of AI3SD interview he discusses the benefits of low-cost sensors for SMEs, why the real world is a lot more complicated than the controlled world of the lab, and the surprising value in getting your problems tackled by people who've...

AI3SD Video: Learning to Control Quantum Systems Robustly

Frank Langbein
Quantum control provides methods to steer the dynamics of quantum systems. The robustness of such controls, in addition to high fidelity, is important for practical applications due to the presence of uncertainties arising from limited knowledge about system and control Hamiltonians, initial state preparation errors, and interactions with the environment leading to decoherence. We introduce a novel robustness measure based on the Wasserstein distance, and discuss structured singular value analysis and log-sensitivity approaches from classical...

AI3SD Video: Hyperparameter Optimisation for Graph Neural Networks

YINGFANG YUAN
Traditional deep learning has made significant progress on various problems, from computer vision to natural language processing. For graph problems, there are still many challenges. Graph neural networks (GNNs) have been proposed for a wide range of learning tasks in the graph domain. In particular, in recent years, an increasing number of GNN models were applied to model molecular graphs and predict the properties of the corresponding molecules. However, a direct impediment to achieve good...

AI3SD Video: Combining robotics and Machine Learning for accelerated drug discovery

Thomas Fleming
Artificial intelligence has an increasing impact on drug discovery and development, offering opportunities to identify novel targets, hit, and lead-like compounds in accelerated timeframes. However, the success of any AI/ ML model depends on the quality of the input data, and the speed with which in silico predictions can be validated in vitro.

The talk will cover laboratory automation and robotics and the benefits they offer in terms of quality and speed of data generation...

AI3SD Video: Machine Learning and AI for Drug Design

Ola Engkvist
Artificial Intelligence has become impactful during the last few years in chemistry and the life sciences, pushing the scientific boundaries forward as exemplified by the recent success of AlphaFold2.

In this presentation I will provide an overview of how AI have impacted drug design in the last few years, where we are now and what progress we can reasonably expect in the coming years. The presentation will have a focus on deep learning based molecular...

AI3SD Video: Reinforcement Learning Methods

Stephen Gow
Reinforcement learning is a machine learning paradigm in which an agent learns to make decisions to achieve a long-term goal. In the past five years, the previously somewhat niche method has seen substantially increased interest from within the chemistry community, driven by the need for a machine learning approach to problems of planning and sequential decision making and recent developments in harnessing the power of neural networks to make reinforcement learning achievable for large problems....

AI3SD Video: AI and optimisation in Computational Chemistry

Grant Hill
Numerical methods of optimisation are vital in chemistry, ranging from finding the lowest energy of a molecule through to reactor design. This talk will discuss two examples of how we are using optimisation techniques to work towards automating the discovery of new materials and developing computational chemistry methodology. The first of these is an AI3SD funded project where we set out to develop new membranes for water desalination using artificial intelligence techniques. In the second,...

AI3SD video: harnessing advanced algorithms to enable the automated optimisation of telescoped chemical reactions; performance directed self-optimisation of bimetallic nanoparticle catalysts

Thomas Chamberlain
The catalytic performance of nanoparticles is dependent on an extensive number of properties, reactions conditions and combinations thereof; however, very few methods employing multivariate closed-loop optimisation of nanoparticle catalysts have been reported to date. Here we demonstrate a machine learning-driven reactor platform for the performance directed synthesis of nanoparticle catalysts. Our experimental strategy uses an automated two-stage continuous flow reactor with decoupled residence times, allowing the precise synthesis of gold-silver nanoparticles (AuAgNP) with variable metal...

AI3SD video: physical sciences data infrastructure: shaping the physical sciences roadmap

Simon J. Coles
Digital technologies and computational resources are being utilised in scientific research and an increasing rate, however, the vast potential of these resources has yet to be realised. The physical sciences data infrastructure (PSDI) project aims to accelerate research in the physical sciences by providing a data infrastructure that brings together and builds upon the various data systems researchers currently use. This project is currently funded through the EPSRC digital research infrastructure funding to undertake a...

Registration Year

  • 2022
    55
  • 2021
    12

Resource Types

  • Audiovisual
    67

Affiliations

  • University of Southampton
    67
  • University of Nottingham
    5
  • University of Cambridge
    4
  • University College London
    4
  • University of Leeds
    2
  • University of Oxford
    2
  • Swansea University
    2
  • University of Sheffield
    2
  • University of Strathclyde
    1
  • University of Kent
    1