Dr Mandie Quartly:
Global Tech Lead, IBM POWER Ecosystem Development
Dr Mandie Quartly, Global Tech Lead, IBM POWER Ecosystem Development
Focused on the creation and growth of strategic relationships with key software organisations. In particular those using AI capabilities and looking to enable end users to gain timely insights from their data. Mandie’s background is Linux, Power Systems and High Performance Computing focused, specialising in the design and implementation of high performance Linux-based systems. Mandie has an MBA and a Ph.D. in Astrophysics.
Trading Strategist, Bank of America Merrill Lynch
Georgios Papaioannou: Trading Strategist, Bank of America Merrill Lynch
George Papaioannou, is a VP Trading Strategist within the Scientific Implementation Group of Bank of America Merrill Lynch. A Global quantitative team employing systematic, quantitative and scientifically informed methodologies around execution, portfolio management, and risk management, with emphasis on development of client solutions. George joined BAML in May 2018, following 12 years in energy major Shell, where he worked on a variety of functions. His latest role was in a team of computational science specialists, advising on machine learning, data, cloud, and high performance computing projects. He has previously worked in production operations, oil and gas forecasting, production optimization, reservoir management, development and project execution, for offshore fields in Brunei. The first 5 years of his industry career he worked in R&D as a scientific software developer focusing on scalable solvers and high performance computing. George holds a PhD in Computational Fluid Mechanics from the Massachusetts Institute of Technology, where he also completed two MSc degrees and worked as a post-doctoral associate for a year. He has authored academic articles and acted as referee for several scientific journals.
Alison B. Lowndes:
Artificial Intelligence DevRel | EMEA, NVIDIA
Alison B. Lowndes: Artificial Intelligence DevRel | EMEA, NVIDIA
Joining in 2015, Alison spent her first 18 months with NVIDIA as a Deep Learning Solutions Architect and is now responsible for NVIDIA’s Artificial Intelligence Developer Relations in the EMEA region (Europe, Middle East, Africa). She is a mature graduate in Artificial Intelligence combining technical and theoretical computer science with a physics background & over 20 years of experience in international project management, entrepreneurial activities and the internet. She consults on a wide range of AI applications, including planetary defence with NASA, ESA & the SETI Institute and continues to manage the community of AI & Machine Learning researchers around the world, remaining knowledgeable in state of the art across all areas of research. She also travels, advises on & teaches NVIDIA’s GPU Computing platform, around the globe.
Vice President, Morgan Stanley
Harsh Prasad: Vice President, Morgan Stanley
Harsh started his career as a programmer working on various search and pattern recognition algorithms including AI techniques, across radio astrophysics, bioinformatics and speech recognition. He then transitioned to financial risk domain and for the last decade has worked in many regulatory jurisdictions with banks and finance companies as well as consulting firms focussed on quant modelling. In this period he has applied Machine Learning techniques to behavioural modelling for ALM, mortgage risk modelling, derivatives pricing, time series outlier detection and risk data management. He has been a guest faculty with B schools and is currently authoring a book titled ‘Machine Learning for Finance’.
Head of Research, Quantica Capital AG
Artur Sepp: Head of Research, Quantica Capital AG
Artur Sepp is Head of Research at Quantica Capital AG in Zurich focusing on systematic data-driven trading strategies. Artur has extensive experience working as a Quantitative Strategist in leading roles since 2006. Prior to joining Quantica, Artur worked at Julius Baer in Zurich developing algorithmic solutions and strategies for the wealth management and portfolio advisory. Before, Artur worked as a front office quant strategist for equity and credit derivatives trading at Bank of America Merrill Lynch in London and Merrill Lynch in New York. Artur has a PhD in Statistics, an MSc in Industrial Engineering from Northwestern University, and a BA in Mathematical Economics. Artur’s research area and expertise are on econometric data analysis, machine learning, and computational methods with their applications for quantitative trading strategies and asset allocation. He is the author and co-author of several research articles on quantitative finance published in leading journals and he is known for his contributions to stochastic volatility and credit risk modelling. Artur is a member of the editorial board of the Journal of Computational Finance.
Managing Director, Head of Data Analytics, Standard Chartered Bank
Alexei Kondratyev: Managing Director, Head of Data Analytics, Standard Chartered Bank
In his role as Managing Director and Head of Data Analytics at Standard Chartered Bank, Alexei is responsible for providing data analytics services to Financial Markets sales and trading.
He joined Standard Chartered Bank in 2010 from Barclays Capital where he managed a model development team within Credit Risk Analytics. Prior to joining Barclays Capital in 2004, he was a senior quantitative analyst at Dresdner Bank in Frankfurt.
Alexei holds MSc in Theoretical Nuclear Physics from the University of Kiev and PhD in Mathematical Physics from the Institute for Mathematics, National Academy of Sciences of Ukraine.
William A. McGhee:
Global Head of Quantitative Analytics, NatWest Markets
William A. McGhee: Global Head of Quantitative Analytics, NatWest Markets
William started his quant career in 1994 with J.P. Morgan in the Currency Options business. In 1998 he joined Deutsche Bank where he became Global Head of FX Quantitative Analytics. He worked between 2003 and 2009 at Citi in a number of roles encompassing structuring, exotics trading and heading up the FX Quantitative Strategy Group.
He joined RBS in 2009 to run the multi-asset Hybrid Quantitative Analytics team. In his current position as Global Head of Quantitative Analytics he is responsible for all modelling within the investment bank – from electronic trading to vanilla and complex derivatives.
William holds a PhD in Mathematical Physics, is a Fellow of the Institute of Mathematics and It’s Applications and serves on the UK Parliamentary and Scientific Committee.
Managing Director, Head of Credit Derivatives, CITI
Youssef Elouerkhaoui, Managing Director, Head of Credit Derivatives, CITI
Youssed Elouerkhaoui is the global Head of Credit Quantitive Analysis at Citi. His group supports all aspects of modelling and product development across desks, thais includes: Flow Credit Trading, Correlation Trading, CDOs, Exotics and Emering Markets.
He also supports CVA, Funding and Regulatory Capital for Credit Markets. Prior to this, he was a Director in the Fixed Income Derivatives Quantitative Research Group at UBS, where he was in charge of developing and implementing models for the Structured Credit Desk. Before joining UBS, Youssef was a Quantitative Research Analyst at Credit Lyonnais supporting the Interest Rates Exotics business. He has also worked as a Senior Consultant in the Risk Analytics and Research Group at Ernst & Young. He is a graduate of Ecole Centrale Paris and he holds a PhD in Mathematics from Paris-Dauphine University.
Founder, CEO, Thalesians & Senior Quantitative Consultant, BNP Paribas
Paul Bilokon: Founder, CEO, Thalesians & Senior Quantitative Consultant, BNP Paribas
Dr. Paul Bilokon is CEO and Founder of Thalesians Ltd and an expert in electronic and algorithmic trading across multiple asset classes, having helped build such businesses at Deutsche Bank and Citigroup. Before focussing on electronic trading, Paul worked on derivatives and has served in quantitative roles at Nomura, Lehman Brothers, and Morgan Stanley. Paul has been educated at Christ Church College, Oxford, and Imperial College. Apart from mathematical and computational finance, his academic interests include machine learning and mathematical logic.
Miquel Noguer Alonso:
Co-Founder at Artificial Intelligence Finance Institute – AIFI
Miquel Noguer Alonso: Co-Founder at Artificial Intelligence Finance Institute – AIFI
Miquel Noguer i Alonso is a financial markets practitioner with more than 20 years of experience in asset management, he is currently working for UBS AG (Switzerland). He worked as a CFO and CIO for a European bank from 2000 to 2006. He started his career at KPMG.
He is Adjunct Assistant Professor at Columbia University teaching Asset Allocation, Big Data in Finance, Fintech and Hedge Fund Professor at ESADE. He received an MBA and a Degree in business administration and economics in ESADE in 1993. In 2010 he earned a PhD in quantitative finance with a Summa Cum Laude distinction (UNED – Madrid Spain). He also holds the Certified European Financial Analyst diploma ( 2000 ).
His research interests range from asset allocation, big data to algorithmic trading and fintech. His academic collaborations include a visiting scholarship in Columbia University in 2013 in the Finance and Economics Department, in Fribourg University in 2010 in the mathematics department, and presentations in Indiana University, ESADE, London Business School, CAIA Association, AFI and several industry seminars.
Professor of Complexity Science, University College London
Tomaso Aste: Professor of Complexity Science, University College London
Tomaso Aste is Professor of Complexity Science at UCL Computer Science Department. A trained Physicist, he has substantially contributed to research in complex structures analysis, financial systems modelling and machine learning. He is passionate in the exploration of the interface between technologies on society and currently he focuses on the application of Blockchain Technologies to domains beyond digital currencies.
He is Scientific Director and Founder of the UCL Centre for Blockchain Technologies, Head and Founder of the Financial Computing and Analytics Group at UCL, Programme Director of the MSc in Financial Risk Management, Vice- Director of the Centre for doctoral training in Financial Computing & Analytics, and Member of the Board of the ESRC LSE-UCL Systemic Risk Centre.
Prior to UCL he held positions in UK and Australia. He is advising and consulting for financial institutions, banks and digital-economy companies and startups.
Claudi Ruiz Camps:
Machine Learning Specialist, ABN AMRO Clearing Bank
Claudi Ruiz Camps: Machine Learning Specialist, ABN AMRO Clearing Bank
Claudi has studied Physics at Autonomous University of Barcelona and a master’s degree in Automatic Control and Robotics at Polytechnic University of Catalonia. He has been doing research in Machine Learning for the industry since 2015 and currently he is working at ABN AMRO Clearing Bank as a Machine Learning Specialist. His domain of expertise is unsupervised learning and he is currently tackling problems such as unsupervised anomaly detection, information compression, clustering and time series forecast by using approaches within the framework of variational autoencoders, recurrent neural networks and generative adversarial networks among others.
Vice President, CitiBank
Inder Singh: Vice President, CitiBank
Inder has more than 15 years of experience in finance technologies and has created numerous low latency and high frequency trading and risk management application. He enjoys learning about new technologies and platforms and prefers staying hands-on. He is currently involved in building risk platform for commodities business and pursuing independently on building applications to leverage sentiment analysis in different markets. His experience ranges from various Microsoft technologies to Java, Python etc.
Founder & CEO, MoCaX Intelligence
Ignacio Ruiz: Founder & CEO, MoCaX Intelligence
Ignacio Ruiz has been the head strategist for Counterparty Credit Risk, exposure measurement, for Credit Suisse, as well as the Head of Risk Methodology, equities, for BNP Paribas. In 2010, Ignacio set up iRuiz Consulting as an independent advisory business in this field. In 2014, Ignacio founded iRuiz Technologies to develop and commercialise MoCaX Intelligence.
He holds a PhD in nano-physics from Cambridge University.
Saeed Amen: Founder: Cuemacro
Saeed has a decade of experience creating and successfully running systematic trading models at Lehman Brothers and Nomura. He is the founder of Cuemacro, Cuemacro is a company focused on understanding macro markets from a quantitative perspective. He is the author of ‘Trading Thalesians – What the ancient world can teach us about trading today’ (Palgrave Macmillan), and graduated with a first class honours master’s degree from Imperial College in Mathematics& Computer Science.
Front Office Quant
Jan is a former front office quant at HSBC in the eFX markets working on predictive analytics and alpha signals. Prior to joining HSBC team, he was working in the Centre for Econometric Analysis on the high-frequency time series econometric models and was visiting lecturer at Cass Business Group, Warwick Business School and Politecnico di Milano. He co-authored number of papers in peer-reviewed journals in Finance and Physics, contributed to several books, and presented at numerous conferences and workshops all over the world. During his PhD studies, he co-founded Quantum Finance CZ.
Co-founder of Irithmics
Grant Fuller: Co-founder of Irithmics
Grant Fuller is co-founder of Fintech applying artificial intelligence to gain greater insight and analysis of hedge funds. Grant was previously part of the hedge fund risk practice of Ernst & Young in London, and prior to that he helped start and develop Bloomberg’s successful hedge fund trading and analytics AIM platform, leading the firm’s European and Asian business. Before joining Bloomberg, he was part of RiskMetrics where we was responsible for helping build the European asset management technologies and consulting capabilites. Grant Fuller holds a BSc in Chemistry from the University of St Andrews. He remained at St Andrews to undertake a PhD applying neural networks within carbohydrate chemistry, after which he joined academic research at Cambridge University.
Quantitative Research Solutions, Bloomberg, LP
Arun Verma: Quantitative Research Solutions, Bloomberg, LP
Dr. Arun Verma joined the Bloomberg Quantitative Research group in 2003. Prior to that, he earned his Ph.D from Cornell University in the areas of computer science & applied mathematics. At Bloomberg, Mr. Verma’s work initially focused on Stochastic Volatility Models for Derivatives & Exotics pricing and hedging. More recently, he has enjoyed working at the intersection of diverse areas such as data science (for structured & unstructured data), innovative quantitative & machine learning methods and finally interactive visualizations to help reveal embedded signals in financial data.