Needles in a Haystack: Big Data and Bigger Promises?
Needles in a Haystack: Big Data and Bigger Promises?

Abstract: 

We need to collect ever larger amounts of data! Why? Because we might find patterns of behaviour in our macro world –people, environment, upper atmosphere and deep oceans- and in our micro world – disease vectors, the heart of the matter (currently quarks) and so on. Once we have filled the big data silos, we will not only find patterns of (hidden) behaviour but we will be able to make machines learn the behaviour and mimic the operations performed by clever humans in the macro- and micro world. Then we have a disaster created, say, by greed, and all the systems that have discovered and learnt the behaviour of the ‘market’ failed to work costing trillions of dollars, yes and euros: We find that there was yet another pattern of behaviour we had failed to discover and learn – the market sentiment was what we had missed so the claim goes. Oh dear. A race is on to collect qualitative sentiment data -words, gestures, and voice intonation of the traders and bankers - on top of collecting terra bytes of quantitative high frequency trading data- and then trying to unravel and learn how the two data sets will be fused to make a decision. Data fusion will be the next challenge, after the statistical machine learning folks have cleared the deep learning stable. I
will talk about my experience of sentiment analysis and data fusion and will sprinkle my talk magical dust of artificial intelligence.

Bio: 

Khurshid is the Professor of Computer Science in the School of Statistics and Computer Science, Trinity College Dublin, University of Dublin, Ireland since 2005. He was formerly Professor of Artificial Intelligence at the University of Surrey, UK (1999-2005). He is currently working on spinning out his research in emergency management and decision making as a commercial venture: the product will be a social media monitor for use in emergencies including natural disasters like floods, and health pandemics. Khurshid's research areas include artificial intelligence, machine learning, social media and networks, fuzzy logic and behavioural finance. He was trained as a nuclear physicist and worked in high-performance computing covering areas such as forecasting, computer-assisted learning, engineering design, and information extraction from continuous information streams comprising texts, images and numbers. His work seeks to maximise the potential of computing systems by enabling these systems to deal with different modalities of human communications, language, vision, and numerical information exchange. Khurshid's current focus is on the automatic analysis facial expressions and hand gestures of politicians, civil protection officials, and market traders during emergencies. His collaborators have been diverse ranging from National Gallery of Ireland, UK and Irish Police Forces, Bundeskommnado Leipzig, Protezione Civile Veneto, Italy, Siemens AG, Mercedes Benz, AXA Insurance, international banks, and universities across the EU, the USA, and Australia. He has recently completed an EU Framework Programme 7 - Security Area on the use and abuse of social media in disaster emergency (Project Slandail). A book on Social Computing and the Law (Cambridge, 2018), focussing on emergency management, has just been published. In the past by the UK Research Councils (including EPSRC, ESRC, and AHRC) and EU Information Societies Programme have funded his projects. His work on commercialisation of his research on sentiment analysis and on social computing during disasters were funded by Atlantic Bridge Venture Finds and Enterprise Ireland respectively (2018019). He was the founding Head and Professor of Artificial Intelligence of the Department of Computing, University of Surrey, UK (1999-2005); Visiting Professor at the Copenhagen Business School (1998, 2013) and University of Surrey (2005-2008). He has extensive international contacts and has been invited to speak at major conferences across the world. He is currently working on an information system that can find trends in the reporting and blogging about infectious disease. He has published over 250 papers including 6 books; his most recent book is on the topic of Social Computing and the Law (Cambridge) and a five years before he published Affective Computing and Sentiment Analysis: Metaphor, Ontology and Terminology (Springer). He has supervised 45 PhD, 1 MPhil, and 21 MSc students successfully, and is currently supervising 2 PhD students and 6 MSc students. He is an elected Fellow of the British Computer Society and of Trinity College Dublin, and a Chartered Engineer of the UK Engineering Council.