7 Works

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: 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: A vision of Medicinal Chemistry for the future

Lewis Vidler & Jeremy G. Frey
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: Skills4Scientists - Poster & Careers Symposium - Poster Compilation

AndrĂ¡s 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: 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...

Registration Year

  • 2022
    2
  • 2021
    5

Resource Types

  • Audiovisual
    7

Affiliations

  • University of Southampton
    7
  • University of Nottingham
    2
  • University of Strathclyde
    1
  • MIT University
    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