Dr Georgina Cosma

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Senior lecturer at the Department of Computer Science, Loughborough University, UK

Areas of research: Intelligent & Neural Information Retrieval, Computational Intelligence & Machine Learning, Continual Lifelong Learning, Temporal Information Modelling, Bias Management & Mitigation, and AI Reasoning.

Qualifications: Graduated from the University of Warwick with a PhD degree in Computer Science in 2008. My thesis was on Intelligent Information Retrieval. BSc Hons (First Class) & PhD Computer Science, PGCHE (Distinction), HEA Fellow. More information can be found here.

Current role: I am Senior Lecturer (Associate Professor) in AI & Data Science at the Department of Computer Science, Loughborough University, U.K. I teach the Natural Language Processing (NLP) module that is a compulsory module of MSc in Artificial Intelligence; and I am programme director of the MSc in Data Science programme (FT and PT).

Research group: I am leading the Neural Information Processing, Retrieval & Modellingresearch group and supervising a team of talented PhD students and Research Fellows working on neural information retrieval and other AI projects. If you are interested in joining the group as a self-funded (or sponsored) student, please see the Neural Information Retrieval page for sample projects and ideas.

Responsible AI: AI can be a powerful tool but must be used responsibly in society and not to cause any harm. For this reason it is vital that those designing, developing, and deploying AI have a good understanding on how to use AI responsibly. For more information on “The importance of ethical AI and a new training programme I delivered via the Royal Statistical Society” please visit this page.

Grant capture and research activity: Currently hold a number of grants funded by the NIHR, THF, KTP, MoD, RAF and industry-funded grants. For more information on please see my page on Funded Projects.

Past experiences: In the past, I have held several grants as Principal Investigator (PI) and Co-Investigator (Co-I). Most noteworthy, was the 3-year Leverhulme project grant entitled “Novel Approaches for Constructing Optimised Multimodal Data Spaces” I held as PI (Oct 2016-Oct 2019). The outputs of the project focus on the development of new Deep Learning algorithms for classifying data (images, video, text, etc.). I enjoy working on NLP and cross-modal Information Retrieval, and have plenty of experience working on large-scale NLP projects. In the past, I have delivered a research/consultancy project for the Government Equality Office (GEO), where I led a work-package on the design and development of advanced Natural Language Processing (NLP) algorithms for analysing large and noisy textual data collected from a large-scale national survey. That also included the development of NLP algorithms for identifying and modelling topics (and subtopics) in the survey data; and for identifying similar and identical responses. For more information on please see my page on Funded Projects.

Memberships: Fellow of the Royal Statistical Society, member of IEEE Computer Society, IEEE Computational Intelligence Society, and several IEEE communities including the Big Data Community, Cloud Computing Community, and Internet of Things Community; and member of the BCS-IRSG (Information Retrieval Specialist Group), and ACM-SIGIR (Special Interest Group in Information Retrieval). I am an active council panel member for EPSRC, and an active reviewer for EPSRC, ESRC, BBSRC, MRC, CRUK, The Leverhulme Trust, and STFC.

Editorial: A very active Associate Editor of Elsevier Pattern Recognition journal. Senior Editorial Board of Nature Scientific Reports. Special Issue Editor of MDPI  Journal of Imaging, Special Issue “Advances and Challenges in Multimodal Machine Learning”.

A proud owner of a beautiful cat, called Tami. She keeps me company when working from home, and likes to relax behind the laptop.