Sylvain is CEO at TAC ECONOMICS. He deals with issues related to innovative and applied research in economy, finance, risk analysis and smart data. He researches on quantitative analysis and machine learning applied to economic analysis and decision making, country risk analysis and early warning systems using artificial intelligence, text mining (identification of ‘hot’ topics, storylines and sentiment), cost of capital in emerging markets, random forest and exchange rate forecasts, millennium development goals, etc.
Emanuele is Professor at the Department of Decision Sciences of Bocconi University and Director of the Bachelor in Economics, Management and Computer Science. He is also a fellow of Bocconi Institute for Data Science and Analytics. He holds a PhD in Probabilistic Risk Assessment from MIT. Among various senior roles, he is the president elect of the Decision Analysis Society of INFORMS, co-Editor in Chief of the European Journal of Operational Research, Editorial Board member of Risk Analysis, and a Scientific Advisor of the Springer International Series in Operations Research and Management Science. He has published more than 100 articles in journals of international excellence including several new sensitivity analysis methods, such as the Differential Importance Measure which is part of the “Probabilistic Risk Assessment Procedures Guide of NASA Managers and Practitioners”.
He led the funded project by Grandi Stazioni “Big Data Infrastructure and Machine Learning”. He has been involved in the four-year frontier research project on the interface between artificial intelligence and decision support with the purpose of using artificial intelligence for supporting decision-making in food crises (South Sudan). He is the recipient of the IBM faculty award for “Neural Networks and Global Sensitivity Analysis”. Currently, he is the instructor of the sponsored Siemens–Bocconi undergraduate course “Big Data for Business Analytics”.
Alan is a Data Scientist at Sabre Insurance Ltd. He has also been Director at Machine Learning Solutions Ltd (MLS). MLS provides training in ML techniques as well as delivery of technical projects in predictive analytics across various industries. Recent work includes provision of training in ML techniques to an actuarial team, Quality Assurance of GLM models and quality control on R code written to analyse patient responses to drugs. Alan holds Masters degrees in Machine Learning (UCL) and in Statistics (Sheffield University). He has held senior roles in the industry including Global Aerospace Actuary at AIG, Chief Actuary roles at Groupama and Allianz Marine and Aviation and Group Pricing Manager at RSA.
Frank is currently Professor of Computational Finance and Investment Analytics within Southampton Business School at the University of Southampton. Previously he worked for Barclays Global Investors, Meinl Capital Markets, State Street and UBS. His former roles included Economist, Fund Manager, Investment Strategist and Head of Research. Throughout his career, he has sought to bridge the gap between academia and practice. His research to date has been on the empirical market microstructure of electronic financial markets and his current research interests include, among others, network economics, neural networks, genetic algorithms, prediction markets, algorithmic trading, support vector machines, machine learning, etc.
Hans-Jörg von Mettenheim
Hans is tenured professor at IPAG, founder and Secretary-General of the Forecasting Financial Markets Association (FFMA). He directs the IPAG Quantitative Finance and Risk Management research chair that contributes to the analysis of algorithmic trading, the exploration of its opportunities, the assessment of its risks, aiming at encouraging knowledge-sharing between researchers and practitioners, and has a notable interest in the applications of big data techniques and data-based machine learning.
Jens Perch Nielsen
Jens is an actuary from Copenhagen and statistician from UC-Berkeley. Currently Professor of Actuarial Science at Cass, he previously worked as appointed actuary and led various product development departments. He became research director of RSA with responsibilities in life as well as non-life in 1999. From 2006 until 2012 he worked as an entrepreneur and he is still co-owner and board member of Copenhagen-based ScienceFirst, London-based Operational Science and Cyprus-based Emergent. He has written on topics relating to actuarial science, economics, econometrics and statistics. One of his main areas of research is forecasting benchmarks of long-term stock returns via machine learning.
Simone’s research combines network theory and sociological arguments to appreciate the organization and functioning of markets—especially, markets for cultural products and labour. Throughout his work he emphasizes the interrelationship of individuals, groups and social structures and tries to detail the causal mechanisms through which organizational and social facts are brought about.
Georgios is a Professor of Finance (Economics) at Adam Smith Business School, University of Glasgow. He has published, among others, research on neural networks in financial trading, neural network copula portfolio optimization for exchange traded funds, support vector regression for forecasting exchange traded funds, commodities, stock markets, exchange rates, inflation and unemployment.