12 Works

AI3SD Video: Skills4Scientists - Poster & Careers Symposium - Poster Compilation

András Vekassy, Aspen Fenzl, Erhan Gulsen, Hewan Zewdu, Jamie Longio, Maximilian Hoffman, Rhyan Barrett, Rubaiyat Khondaker, Anna Catton, Hongyang Dong, Kevin Calvache, Kaylee Patel, King Wong, Louis Greenhalgh, Rebecca Jane Clements, Thomas Allam, Sarah Scripps, Gavin Man, Samuel Munday, Michael Blakey, Graeme M. Day, Chris-Kriton Skylaris, Simon J. Coles, Stephen Gow & William Brocklesby
This video forms part of the Skills4Scientists Series which has been organised as a joint venture between the Artificial Intelligence for Scientific Discovery Network+ (AI3SD) and the Physical Sciences Data-Science Service (PSDS). This series ran over summer 2021 and aims to educate and improve scientists skills in a range of areas including research data management, python, version control, ethics, and career development. This series is primarily aimed at final year undergraduates / early stage PhD...

AI3SD Video: Producing Useful Code

Samuel Munday
This talk forms part of the Skills4Scientists Series which has been organised as a joint venture between the Artificial Intelligence for Scientific Discovery Network+ (AI3SD) and the Physical Sciences Data-Science Service (PSDS). This series ran over summer 2021 and aims to educate and improve scientists skills in a range of areas including research data management, python, version control, ethics, and career development. This series is primarily aimed at final year undergraduates / early stage PhD...

AI3SD Video: Explainable Machine Learning for Trustworthy AI

Fosca Giannotti
Black box AI systems for automated decision making, often based on machine learning over (big) data, map a userâs features into a class or a score without exposing the reasons why. This is problematic not only for the lack of transparency, but also for possible biases inherited by the algorithms from human prejudices and collection artifacts hidden in the training data, which may lead to unfair or wrong decisions. The future of AI lies in...

AI3SD Video: Accelerating design of organic materials with machine learning and AI

Olexandr Isayev
Deep learning is revolutionizing many areas of science and technology, particularly in natural language processing, speech recognition, and computer vision. In this talk, we will provide an overview of the latest developments of machine learning and AI methods and application to the problem of drug discovery and development at Isayevâ's Lab at CMU. We identify several areas where existing methods have the potential to accelerate materials research and disrupt more traditional approaches. First we will...

AI3SD Video: Towards Biological Plausibility Using Linked Open Data

Egon Willighagen
Behind risk assessment is experimental evidence. Behind biological knowledge is primary literature. However, because the amount of knowledge keeps growing, our experimental technologies are advancing and getting increasingly complex, even experts can no longer keep up with the progress in mechanistic understanding, outside their increasingly specialistic domain. At the same time, the number of biological questions with a simple answer keeps dropping and many modern questions have complex answers. Access to the right facts at...

AI3SD Video: Why you should take up PhD Opportunities in the Physical Sciences

Jeremy G. Frey
This talk forms part of the Skills4Scientists Series which has been organised as a joint venture between the Artificial Intelligence for Scientific Discovery Network+ (AI3SD) and the Physical Sciences Data-Science Service (PSDS). This series ran over summer 2021 and aims to educate and improve scientists skills in a range of areas including research data management, python, version control, ethics, and career development. This series is primarily aimed at final year undergraduates / early stage PhD...

AI3SD Video: Automated Chemical Ontology Expansion

Janna Hastings
Ontologies provide a shared vocabulary and semantic resource for a domain. Manual construction enables them to achieve high quality and capture subtle semantic nuances, essential for wide acceptance and applicability across a community. However, the manual curation process does not scale for large domains. I will present a methodology for automatic ontology extension based on deep learning using ontology annotations, and show how we apply this methodology to the ChEBI ontology, a prominent reference ontology...

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: 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...

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: How can Explainable AI help scientific exploration?

Carlos Zednik
Although models developed using machine learning are increasingly prevalent in scientific research, their opacity poses a threat to their utility. Explainable AI (XAI) aims to diminish this threat by rendering opaque models transparent. But, XAI is more than just the solution to a problem--it can also play an invaluable role in scientific exploration. In this talk, I will consider different techniques from Explainable AI to demonstrate their potential contribution to different kinds of exploratory activities....

AI3SD Video: Statistics Are a Girl's best Friend: Expanding the mechanistic Study Toolbox with Data Science

anat milo
The value of amassing and standardizing chemical data for improving the efficiency of chemical discovery is becoming increasingly clear. Machine learning analyses of these data are focused on finding correlations, trends and patterns to uncover needles of knowledge in the haystack of chemical reactions. However, in many cases, especially in academic settings, we do not have the means to produce large data sets, so by necessity we remain in the Small Data regime. In this...

Registration Year

  • 2021
    12

Resource Types

  • Audiovisual
    12

Affiliations

  • University of Southampton
    12
  • University of Nottingham
    2
  • University College London
    2
  • University of Strathclyde
    1
  • University of Cambridge
    1
  • University of Warwick
    1
  • University of Edinburgh
    1
  • University of Leeds
    1
  • Queen Mary University of London
    1
  • University of Manchester
    1