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.
Associate, Quantitative Analyst, JPMorgan Chase & Co
Ivan Zhdankin: Associate, Quantitative Analyst, JPMorgan Chase & Co
Ivan Zhdankin is a quantitative researcher with experience in diverse areas of quantitative finance, including risk modelling, XVA, and electronic trading across asset classes, including commodity futures and G10 and emerging market currencies. Ivan was consulting various banks in quantitative modeling and has recently joined JP Morgan as a quantitative analyst. He has become one of the first researchers to generate convincing results in electronic alpha with neural nets. He has a solid mathematical background from New Economic School and Moscow State University, where he studied under the celebrated Albert Shiryaev, one of the developers of modern probability theory.
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 the 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.
AI Wealth Technologies Founder & Visiting Research Fellow, Oxford Mathematical Institute
Katia Babbar: AI Wealth Technologies Founder & Visiting Research Fellow, Oxford Mathematical Institute
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 and Chief Science Officer, Artificial Intelligence Finance Institute – AIFI
Miquel Noguer Alonso: Co – Founder and Chief Science Officer, Artificial Intelligence Finance Institute – AIFI
Miquel Noguer is a financial markets practitioner with more than 20 years of experience in asset management, he is currently Head of Development at Global AI ( Big Data Artificial Intelligence in Finance company ) and Head on Innovation and Technology at IEF.
He worked for UBS AG (Switzerland) as Executive Director.for the last 10 years. He worked as a Chief Investment Office and CIO for Andbank from 2000 to 2006.
He is professor of Big Data in Finace at ESADE and Adjunct Professor at Columbia University teaching Asset Allocation, Big Data in Finance and Fintech. 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).
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.
Honorary Lecturer, Department of Mathematics, Imperial College London
Blanka Horvath: Honorary Lecturer, Department of Mathematics, Imperial College London
Blanka is a Honorary Lecturer in the Department of Mathematics at Imperial College London and a Lecturer at King’s College London. Her research interests are in the area of Stochastic Analysis and Mathematical Finance.
Her interests include asymptotic and numerical methods for option pricing, smile asymptotics for local- and stochastic volatility models (the SABR model and fractional volatility models in particular), Laplace methods on Wiener space and heat kernel expansions.
Blanka completed her PhD in Financial Mathematics at ETHZürich with Josef Teichmann and Johannes Muhle-Karbe. She holds a Diploma in Mathematics from the University of Bonn and an MSc in Economics from the University of Hong Kong.
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.
Co-founder and CEO, Yields.io
Jos Gheerardyn: Co-founder and CEO of Yields.io
Jos is the co-founder and CEO of Yields.io. Prior to his current role he has been active in quantitative finance both as a manager and as an analyst. Over the past 15 years he has been working with leading international investment banks as well as with award winning start-up companies. He is the author of multiple patents applying quantitative risk management techniques on imbalance markets. Jos holds a PhD in superstring theory from the University of Leuven.
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.
Product Manager BQUANT/BQL, Bloomberg LP
Sandrine Foldvari: Product Manager BQUANT/BQL, Bloomberg LP
Dr Sandrine Foldvari joined Bloomberg as a BQL/BQUANT Product manager in 2009.
Prior to this, Sandrine earned her PhD from London School of Economics in portfolio allocation. She has 15+ years experience as a quantitative trader / researcher in proprietary trading desks at major investment banks (Goldman Sachs and Credit Suisse) as well as in Hedge Funds (AHL- Man Group and Taranis-BlueQuant). She has joined Bloomberg to develop their Equity Back-testing tool leveraging on Bloomberg data integration (through the in house query language BQL) to provide analytics tools through the BQUANT platform.
Technical Consultant, NAG
Edvin Hopkins: Technical Consultant, NAG
Edvin first worked with NAG between 2010 and 2013, as part of a Knowledge Transfer Partnership with the University of Manchester. Long-time NAG collaborator Professor Nick Higham and his team had developed many new algorithms to compute matrix functions. Edvin’s role was to convert these algorithms into code for the NAG Library.
After the successful collaboration, Edvin worked with Professor Higham as a post-doctoral research associate, before finally joining NAG in 2015. He is based in our Manchester Office.
Edvin gained a PhD in Numerical Relativity from the University of Cambridge in 2009. His supervisor was Dr John Stewart. This followed a first class honours degree in Mathematics and a “Certificate of Advanced Study in Mathematics” from the same institution.
Head of Model Internal Audit, Group Crédit Agricole
Gilles Artaud: Market and Counterparty Risk, Credit Agricole-CIB
Gilles Artaud has been working in investment banking for the last 20 years, where he held various positions within Quant, Front Office and Risk Department, working all along on many underlying types, pricing, validation, regulatory and economic capital, market risk and counterparty credit risk topics.
After setting in place the methodology and library for CCR and CVA, he lead XVA, initial margins on non-cleared transactions, and many regulatory topics.
His current “hot” topics are XVAs (CVA DVA FVA AVA MVA…) and impact of new regulatory requirements on derivatives, among which SA-CCR, NSFR, FRTB and FRTB-CVA and Artificial Intelligence technologies in Risk Management.
Principal Researcher Quantitative Analysis, QxBranch
David Garvin: Principal Researcher Quantitative Analysis, QxBranch
David focusses on researching, developing and implementing financial industry applications of quantum computing. QxBranch delivers predictive analytics, illuminated by Explainable Data Science, leveraging the emerging potential of Quantum Computing.
David has over 20 years experience as a Front-Office Quant in the Finance Industry. Previously, he has been the Global Head of Quantitative Analysis at the Commonwealth Bank of Australia. Prior to that, he was a Director at Deutsche Bank and a Quant Analyst at Morgan Grenfell. He has covered all asset classes and been involved in management, modelling, risk and analytics, derivatives and structured products, machine learning and electronic trading.
David holds a PhD in Artificial Intelligence from Cambridge University and an MBA (Exec) from the Australian Graduate School of Management. He has authored articles in finance, computing, physics and engineering.