Dr Nina Dethlefs

Dr Nina Dethlefs

Senior Lecturer

Faculty and Department

  • Faculty of Science and Engineering
  • School of Computer Science

Summary

My research interests lie at the intersection of machine learning and natural language processing (NLP), particularly in the areas of data-to-text and natural language generation (NLG), interactive systems, assistive technologies, and domain transfer and adaptability for data analytics in a wider AI context. I have spent the last few years working with neural networks as a primary algorithm family but have previously worked with graphical models, clustering and reinforcement learning. Most recently I have become interested in applying AI and NLP in "useful" contexts such as mental health, operations and maintenance in an engineering context, and in a natural world context such as prediction of water flow and quality.

For projects, detailed publications and my team, please see: https://bda-hull.github.io/

Data Analysis and Visualisation

Applied AI

Understanding AI

Recent outputs

View more outputs

Journal Article

Real-time social media sentiment analysis for rapid impact assessment of floods

Bryan-Smith, L., Godsall, J., George, F., Egode, K., Dethlefs, N., & Parsons, D. (2023). Real-time social media sentiment analysis for rapid impact assessment of floods. Computers & geosciences, 178, Article 105405. https://doi.org/10.1016/j.cageo.2023.105405

Domain-invariant icing detection on wind turbine rotor blades with generative artificial intelligence for deep transfer learning

Chatterjee, J., Alvela Nieto, M. T., Gelbhardt, H., Dethlefs, N., Ohlendorf, J., Greulich, A., & Thoben, K. (2023). Domain-invariant icing detection on wind turbine rotor blades with generative artificial intelligence for deep transfer learning. Environmental Data Science, 2, 1-15. https://doi.org/10.1017/eds.2023.9

This new conversational AI model can be your friend, philosopher, and guide ... and even your worst enemy

Chatterjee, J., & Dethlefs, N. (2023). This new conversational AI model can be your friend, philosopher, and guide ... and even your worst enemy. Patterns, 4(1), Article 100676. https://doi.org/10.1016/j.patter.2022.100676

Automated Question-Answering for Interactive Decision Support in Operations & Maintenance of Wind Turbines

Chatterjee, J., & Dethlefs, N. (2022). Automated Question-Answering for Interactive Decision Support in Operations & Maintenance of Wind Turbines. IEEE Access, 10, 84710-84737. https://doi.org/10.1109/ACCESS.2022.3197167

Facilitating a smoother transition to renewable energy with AI

Chatterjee, J., & Dethlefs, N. (2022). Facilitating a smoother transition to renewable energy with AI. Patterns, 3(6), Article 100528. https://doi.org/10.1016/j.patter.2022.100528

Research interests

Artificial Intelligence, Natural language processing, Interactive Systems, Environmental modelling / Sustainable AI, Offshore wind

Lead investigator

Project

Funder

Grant

Started

Status

Project

ChatOSW - - A feasibility pilot for natural language-based decision support in offshore wind

Funder

EPSRC Engineering & Physical Sciences Research Council

Grant

£49,651.00

Started

1 December 2023

Status

Ongoing

Project

Deep Text Generation from a Knowledge Graph

Funder

Diffbot

Grant

£21,119.00

Started

1 October 2017

Status

Complete

Project

FF2021 -1049 - Physics -informed machine learning for rapid fatigue assessments in offshore wind farms

Funder

EPSRC Engineering & Physical Sciences Research Council

Grant

£96,941.00

Started

1 June 2021

Status

Complete

Co-investigator

Project

Funder

Grant

Started

Status

Project

The EPSRC Centre for Doctoral Training on Offshore Wind Energy and the Environment

Funder

EPSRC Engineering & Physical Sciences Research Council

Grant

£3,840,952.00

Started

1 April 2019

Status

Ongoing

Project

Secure and Safe Multi-Robot Systems

Funder

EC European Commission

Grant

£482,634.00

Started

1 January 2021

Status

Complete

Postgraduate supervision

Natural language processing, interactive systems, AI, environmental data analytics

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