Focus on:  Hide Contributions
Login

IDAS Launch Event

30 September 2019
Ogden Centre West
Europe/London timezone

IDAS management board

Contribution List

35 out of 35 displayed
Export to PDF
  1. 26. The data movement challenge and a communication-avoiding mindset
    Tobias Weinzierl (Computer Science / IDAS)
    30/09/2019, 10:00
  2. 27. Extracting Governing Equations from Data
    Rui Carvalho (Engineering / DEI / IDAS)
    30/09/2019, 10:10

    Over the centuries, scientists have sought to describe natural phenomena with mechanistic models. In the last century, we have also made tremendous progress in building powerful non-mechanistic models, from linear regression to random forests and neural networks. However, although data are nowadays abundant in many areas of science and engineering, models often remain elusive. I will introduce...

    Go to contribution page
  3. 28. New insights into magnetic relaxation from HPC
    Anthony Yeates (Mathematical Sciences - Magnetohydrodynamics / IDAS)
    30/09/2019, 10:20
  4. 29. Escape From Model Land
    Leonard A. Smith (LSE / Oxford / Visiting Prof at Durham (Astronomy))
    30/09/2019, 10:30
  5. 12. Condor: a cheap HPC
    Bernard Piette (Mathematical Sciences / CPT)
    30/09/2019, 10:40
  6. 32. Multi-parameter estimation with P&G
    Miguel De-Icaza-Lizaola (Physics / CDT)
    30/09/2019, 10:50
  7. 30. Statistics, Data, and Science
    Jonathan Cumming (Mathematical Sciences - Statistics, SMCU / IDAS)
    30/09/2019, 11:00
  8. 31. Emulation of computer models when multi-fidelity data are available
    Georgios Karagiannis (Mathematical Sciences - Statistics / IDAS)
    30/09/2019, 11:10
  9. 11. Quantum computing research in Durham QLM
    Nicholas Chancellor (Physics - Quantum Light and Matter)
    30/09/2019, 11:20
  10. 9. Music and Big Data (1)
    Tuomas Eerola (Music)
    30/09/2019, 12:00
  11. 10. The Sound of MusAIc
    Nick Collins (Music)
    30/09/2019, 12:10
  12. 13. Doctoral theses and digital scholarship: working with the EThOS collection of the British Library
    Catherine Montgomery (Education)
    30/09/2019, 12:20
  13. 14. Predigital Data
    Matthew Eddy (Philosophy)
    30/09/2019, 12:30
  14. 15. Online competition: how dominant platforms use data
    Anca Chirita (Law School)
    30/09/2019, 12:40
  15. 16. Using evolutionary models to study cultural change and diversity
    Jeremy Kendal (DCERC/Dept. Anthropology)
    30/09/2019, 12:50
  16. 17. The theory-ladenness of observation in big data science
    Peter Vickers (Philosophy)
    30/09/2019, 13:00
  17. 18. Intelligent Tutoring Systems and Learning Analytics
    Lei Shi (Computer Science)
    30/09/2019, 13:10
  18. 19. Virtual Bodies: Ethics of Digital Data in Physical Anthropology
    Trudi Buck (Anthropology)
    30/09/2019, 13:20
  19. 1. IDAS overview
    Frank Krauss (IDAS & physics)
    30/09/2019, 14:30
  20. 20. Forests and climate change - what do images tell us?
    Danny Donoghue (Geography)
    30/09/2019, 14:35
  21. 21. Statistical Shape Modelling and Applications
    Ian Jermyn (Mathematical Sciences)
    30/09/2019, 14:45
  22. 22. Classification of Airborne Laser Scanner Data using Deep Learning
    Nan Wang
    30/09/2019, 14:55
  23. 23. Quite big, very messy: Data science and the Archaeology of the Ancient near East
    Dan Lawrence
    30/09/2019, 15:05
  24. 24. Climate change and the dry tropical forests of Southern Central Africa
    Ruusa David
    30/09/2019, 15:15
  25. 25. Spectral analysis of coffee in Thailand
    Anthony Brown
    30/09/2019, 15:25
  26. 33. CNN-supervised classification of airborne riverscape imagery
    Patrice Carbonneau
    30/09/2019, 15:35
  27. 2. Data Mining and Classical Manuscripts
    Peter Heslin (IDAS and Classics)
    30/09/2019, 16:30
  28. 3. Rescribe: OCR for historic texts and manuscripts
    Nick White (Rescribe (Durham spin-out))
    30/09/2019, 16:40
  29. 4. Interactive text mining and visualization in the humanities
    Donald Sturgeon (Computer Science)
    30/09/2019, 16:50
  30. 5. Digital Theology
    Pete Phillips (Theology)
    30/09/2019, 17:00
  31. 6. Machine Learning and Patterns in Dialogue
    Chris Brown (Education)
    30/09/2019, 17:10
  32. 7. Deep Learning for Museum Collections
    Matthew Roberts (Archaeology)
    30/09/2019, 17:20

    Working with image data provided by the Durham University Oriental Museum, we sought to test how well a data set created from a museum's digital archives could be used for broad artefact type classification using a CNN implemented in PyTorch, as well as considering potential ways in which computer vision and object recognition could be used to support efforts in heritage protection.

    Go to contribution page
  33. 8. Statistical Methods in Archaeology
    Andrew Millard (Archaeology)
    30/09/2019, 17:30
  34. 34. AI and Ethical Investing
    Robert Song
    30/09/2019, 17:40
  35. 35. Mapping Risks in Generated Text
    Joe Bullock
    30/09/2019, 17:50

    This talk is based on research conducted in collaboration with the United Nations and demonstrates the ability with which AI can be used to generate text easily, and at a low cost. The implications of this to societal peace and stability will be explored, and recommendations for potential steps towards the mitigation of negative consequences given.

    Go to contribution page

Back to the event