MD, Head of Quantitative Analytics and Quantitative Development, NatWest Markets
Vladimir Piterbarg: MD, Head of Quantitative Analytics and Quantitative Development at NatWest Markets
Professor and Dept. Chair of FRE Tandon, New York University
Peter Carr: Professor and Dept. Chair of FRE Tandon, New York University
Dr. Peter Carr is the Chair of the Finance and Risk Engineering Department at NYU Tandon School of Engineering. He has headed various quant groups in the financial industry for the last twenty years. He also presently serves as a trustee for the National Museum of Mathematics and WorldQuant University. Prior to joining the financial industry, Dr. Carr was a finance professor for 8 years at Cornell University, after obtaining his Ph.D. from UCLA in 1989. He has over 85 publications in academic and industry-oriented journals and serves as an associate editor for 8 journals related to mathematical finance. He was selected as Quant of the Year by Risk Magazine in 2003 and Financial Engineer of the Year by IAQF/Sungard in 2010. From 2011 to 2014, Dr. Carr was included in Institutional Investor’s Tech 50, an annual listing of the 50 most influential people in financial technology.
In the 2 years Dr. Carr been FRE dept. chair, applications increased from 1,300 per year to 1,900 per year. The number of FRE Masters students in residence was the highest in any 2-year period. For the incoming 2018 class, current verbal GRE is 169/170 and GPA is 3.82. FRE moved up in Quantnet rankings both years. An online summer course was initiated last summer and an on-campus bootcamp will be initiated this summer. Six electives on machine learning in finance were introduced. The distance learning room will become operational this summer.
Reader, Financial Mathematics, Cass Business School
Laura Ballotta: Reader, Financial Mathematics, Cass Business School
Dr Ballotta works in the areas of quantitative finance and risk management. She has written on topics including stochastic modelling for financial valuation and risk management, numerical methods aimed at supporting financial applications, and the interplay between finance and insurance.
Recent major contributions have appeared in Journal of Financial and Quantitative Analysis, European Journal of Operational Research and Quantitative Finance among others.
She serves as associate editor and referee for a number of international journals in the field.
Laura Ballotta obtained her PhD in Mathematical and Computational Methods for Economics and Finance from the Università degli Studi di Bergamo (Italy), following her BSc in Economics from Università Cattolica del Sacro Cuore, Piacenza (Italy), and MSc in Financial Mathematics from the University of Edinburgh – jointly awarded with Heriot-Watt University (UK). Laura has previously held positions at Università Cattolica del Sacro Cuore, Piacenza (Italy), and Department of Actuarial Science and Statistics, City University London (UK).
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.
Associate Director, Quantum Computing, USRA
Davide Venturelli: Associate Director, Quantum Computing, USRA
Davide Venturelli works in the NASA Intelligent System Division (TI) as a research scientist under the NASA Academic Mission Service contract. He is currently Quantum Computing team lead and Science Operations Manager of the Research Institute of Advanced Computer Science (RIACS) at USRA. Venturelli is currently invested in research projects dealing with quantum optimization applications and their near-term implementation in real hardware.
Chair in Mathematical Finance and Stochastic Analysis, Imperial College London, Dept. of Mathematics
Damiano Brigo: Chair in Mathematical Finance and Stochastic Analysis, Imperial College London, Dept. of Mathematics
Professor Damiano Brigo is Chair of Mathematical Finance & co-Head of group at Imperial College, London, consistently ranked among the top 10 Universities in the world. Damiano is also part of the Stochastic Analysis Group at Imperial and serves in several advisory and consulting roles in the financial industry.
Damiano’s previous roles include Gilbart Professor and Head of Group at King’s College London, Managing Director & Global Head of Quantitative Innovation in Fitch Ratings, Head of Credit Models in Banca IMI, Fixed Income Professor at Bocconi University in Milan, Quantitative Analyst at Banca Intesa and Head of the Capco Institute.
Damiano published 100+ works in top journals for Mathematical Finance, Systems Theory, Probability and Statistics, and books for Springer and Wiley that became field references in stochastic interest rate and credit modeling, with H-index 38 and 7000+ citations on Scholar. Damiano is Editor of the International Journal of Theoretical & Applied Finance and of Mathematics of Control, Signals & Systems, and has been listed as the most cited author in Risk Magazine in 1998-2017.
Damiano’s past work and current interests include valuation across asset classes, credit derivatives, interest rate, equity and FX derivatives, univariate and multivariate volatility smile modeling, hedging, risk measurement, funding costs, counterparty credit risk, valuation adjustments, stochastic models for commodities and inflation, dependence dynamics, liquidity risk, optimal execution, information geometry and stochastic analysis, nonlinear stochastic filtering, stochastic processes consistent with mixtures of distributions, and stochastic differential geometry.
Damiano obtained a Ph.D. in stochastic filtering with differential geometry in 1996 from the Free University of Amsterdam, following a BSc in Mathematics with honours from the University of Padua.
Head of Quantitative Portfolio Solutions, Alphadyne Asset Management
Ioana Boier: Head of Quantitative Portfolio Solutions, Alphadyne Asset Management
Ioana is the Head of Quantitative Portfolio Solutions, Alphadyne Asset Management.
I have a Ph.D. in Computer Science from Purdue University. In addition, I have completed graduate coursework in Financial Mathematics at NYU and Big Data at Harvard University. Prior to joining Citadel, I was a Director in the Global Markets Division at BNP Paribas where I managed the Interest Rate Options & Inflation quantitative research team. Before transitioning into Finance, I was a research staff member at the IBM T. J. Watson Research Center.
Executive Chairman and Head of Quant Research, CompatibL
Alexander Sokol: Executive Chairman and Head of Quant Research, CompatibL
Alexander Sokol is the founder, Executive Chairman, and Head of Quant Research at CompatibL, a trading and risk technology company. He is also the co-founder of Numerix, where he served as CTO from 1996 to 2003, and the co-founder of Duality Group, where he served as CTO from 2017 to 2020.
Alexander won the Quant of the Year Award in 2018 together with Leif Andersen and Michael Pykhtin, for their joint work revealing the true scale of the settlement gap risk that remains even in the presence of initial margin. Alexander’s other notable research contributions include systemic wrong-way risk (with Michael Pykhtin, Risk Magazine), joint measure models, and the local price of risk (with John Hull and Alan White, Risk Magazine), and mean reversion skew (Risk Books, 2014).
Alexander earned his BA from the Moscow Institute of Physics and Technology at the age of 18, and a PhD from the L. D. Landau Institute for Theoretical Physics at the age of 22. He was the winner of the USSR Academy of Sciences Medal for Best Student Research of the Year in 1988.
AI Research Associate, Fidelity Investments
Igor Halperin: AI Research Associate, Fidelity Investments
Igor Halperin is an AI Research Associate at Fidelity Investments. His research focuses on using methods of reinforcement learning, information theory, neuroscience and physics for financial problems such as portfolio optimization, dynamic risk management, and inference of sequential decision-making processes of financial agents. Igor has an extensive industrial and academic experience in statistical and financial modeling, in particular in the areas of option pricing, credit portfolio risk modeling, portfolio optimization, and operational risk modeling. Prior to joining Fidelity, Igor worked as a Research Professor of Financial Machine Learning at NYU Tandon School of Engineering. Before that, Igor was an Executive Director of Quantitative Research at JPMorgan, and a quantitative researcher at Bloomberg LP. Igor has published numerous articles in finance and physics journals, and is a frequent speaker at financial conferences. He has co-authored the books “Machine Learning in Finance: From Theory to Practice” (Springer 2020) and “Credit Risk Frontiers” (Bloomberg LP, 2012). Igor has a Ph.D. in theoretical high energy physics from Tel Aviv University, and a M.Sc. in nuclear physics from St. Petersburg State Technical University.
Stuart School of Business, Illinois Institute of Technology
Matthew Dixon: Stuart School of Business, Illinois Institute of Technology
Matthew Dixon, Ph.D, FRM, began his career as a quant in structured credit trading at Lehman Brothers. He has consulted for numerous investment management, trading and financial technology firms in machine learning and risk analytics. He is the author of the 2020 textbook “Machine Learning in Finance: From Theory to Practice” and has written over 20 peer reviewed papers on machine learning and computational finance, including SIAM J. Financial Mathematics and the Journal of Computational Finance. He is the recipient of an Illinois Tech innovation award, and his research has been funded by Intel and the NSF. Matthew has recently contributed to the CFA syllabus on machine learning and he currently serves on the CFA advisory committee for quantitative trading. He has been invited internationally to give talks at prestigious seminars organized by investment banks and universities in addition to being quoted in the Financial Times and Bloomberg Markets. He holds a Ph.D. in Applied Math from Imperial College, has held visiting academic appointments at Stanford and UC Davis, and is a tenure-track Assistant Professor at Illinois Tech.
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.
Lecturer in Financial Mathematics, Queen Mary University of London
Kathrin Glau: Lecturer in Financial Mathematics, Queen Mary University of London
Kathrin Glau currently is a Lecturer in Financial Mathematics at Queen Mary University of London & FELLOW co-founded by Marie Skłodowska Curie at École Polytechnique Fédérale de Lausanne. Between 2011 and 2017 she was Junior Professor at the Technical University of Munich. Prior to this she worked as a postdoctoral university assistant at the chair of Prof. Walter Schachermayer at the University of Vienna. In September 2010 she completed her Ph.D. on the topic of Feynman-Kac representations for option pricing in Lévy models at the chair of Ernst Eberlein.
Her research is driven by the interdisciplinary nature of computational finance and reaches across the borders of finance, stochastic analysis and numerical analysis. At the core of her current research is the design and implementation of complexity reduction techniques for finance. Key to her approach is the decomposition of algorithms in an offline phase, which is a learning step, and a fast and accurate online phase. The methods range from model order reduction of parametric partial differential equations to learning algorithms and are designed to facilitate such diverse tasks as uncertainty quantification and calibration, real-time pricing, real-time risk monitoring, and intra-day stress testing.
Professor, Courant Institute of Mathematical Sciences, NYU
Petter Kolm: Director of the Mathematics in Finance Master’s Program and Clinical Professor, Courant Institute of Mathematical Sciences, New York University
Petter Kolm is a Clinical Professor and the Director of the Mathematics in Finance Master’s Program at Courant Institute of Mathematical Sciences, NYU. Previously, Petter worked in the Quantitative Strategies Group at Goldman Sachs Asset Management where his responsibilities included researching and developing new quantitative investment strategies for the group’s hedge fund. Petter has coauthored numerous academic articles and four books: Financial Modeling of the Equity Market: From CAPM to Cointegration (Wiley, 2006), Trends in Quantitative Finance (CFA Research Institute, 2006), Robust Portfolio Management and Optimization (Wiley, 2007), and Quantitative Equity Investing: Techniques and Strategies (Wiley, 2010). He holds a Ph.D. in Mathematics from Yale, an M.Phil. in Applied Mathematics from the Royal Institute of Technology, and an M.S. in Mathematics from ETH Zurich.
Petter is a member of the editorial boards of the International Journal of Portfolio Analysis and Management (IJPAM), Journal of Investment Strategies (JoIS), Journal of Portfolio Management (JPM) and Journal of Financial Data Science (JFDS). He is an Advisory Board Member of Betterment (one of the largest robo-advisors) and the Alternative Data Group (ADG). Petter is also on the Board of Directors of the International Association for Quantitative Finance (IAQF) and the Yale Graduate School Alumni Association (GSAA).
Petter’s teaching, work and research interests include alternative data, data science, econometrics, forecasting models, high frequency trading, machine learning, portfolio optimization w/ transaction costs and taxes, quantitative and systematic trading, risk management, robo-advisory and investing, smart beta strategies, transaction costs, and tax-aware investing.
Founder & CEO, Riskfuel
Ryan Ferguson: Founder & CEO, Riskfuel
Ryan is Founder and CEO at Riskfuel, a capital markets focused startup that is developing ultra-fast AI-based valuation technologies.Previously, Ryan was Managing Director and Head of Securitization, Credit Derivatives and XVA at Scotiabank. Prior roles have included credit correlation trading and managing the equity derivatives trading desk. Ryan began his career with positions in risk management and financial engineering. Ryan has a PhD in Physics from Imperial College, and a BASc and MASc in Electrical Engineering from the University of Waterloo.
Head of Structured Credit QA, Barclays Investment Bank
Andrey Chirikhin: Head of Structured Credit QA, Barclays Investment Bank
Andrey was formerly Head of Modelling and Quantitative Analytics for L1 Treasury, part of a USD 25bn privately held investment vehicle LetterOne. Prior to LetterOne, Andrey was MD and Head of CVA and CCR quantitative Analytics at RBS. There he has created and run the front office cross asset CVA quant team. He also restructured and led the risk-side quant team charged with delivering a new Basel III compliant internal CCR methodology. The system utilizing the newly delivered methodology has won the 2013 Internal System of the year Risk award. In his 20 year career in investment banking, Andrey held several leadership and senior quant positions at Goldman Sachs, HSBC and Dresdner Kleinwort. Andrey Chirikhin holds PhD in Theoretical Statistics from Warwick University (UK), MBA from INSDEAD and MSc in Applied Mathematics from Moscow Institute for Physics and Technology (Phystech).
Since 2018 Andrey runs his own company, Quantitative Recipes, that advises on wide rage of XVA, long-term market modelling for risk and quant infrastructure.
Senior Director, Head of Methodology and Analytics, Capital Markets Risk Management, CIBC
Hany Farag: Senior Director, Head of Methodology and Analytics, Capital Markets Risk Management, CIBC
Hany Farag is Senior Director and Head of Risk Methodology and Analytics at CIBC. Prior to his current position he was a partner at Eastmoor Capital Partners, LLP; Managing Director and Head of FX Statistical Arbitrage at CIBC; and Head of Quantitative Research at OANDA Corporation. Prior to his industry positions he was a Postdoctoral Fellow at Caltech and at Rice University. He holds a PhD in Mathematical Analysis from Yale, a MS in Theoretical Physics from Yale, and a BSC in Electronics and Communication Engineering from Ain Shams.
Zineb El Filali Ech-Chafiq:
Quantitative Analyst, Natixis
Zineb El Filali Ech-Chafiq: Quantitative Analyst, Natixis
Professor of Quantum Technologies, University of Sussex
Prof. Winfried Hensinger: Professor of Quantum Technologies, University of Sussex
Prof Winfried Hensinger heads the Sussex Ion Quantum Technology Group and he is the director of the Sussex Centre for Quantum Technologies. Hensinger’s group works on developing and constructing practical trapped-ion quantum computers as well quantum sensors. Hensinger produced the first ion trap microchip in the world and more recently, his group developed a new generation of quantum microchips featuring world record specifications. In 2016, Hensinger and his group invented a new approach to quantum computing with trapped ions where voltages applied to a quantum computer microchip can replace billions of laser beams which would have been required in previous proposals on how to build a quantum computer. In 2017, Hensinger announced the first practical blueprint for building a quantum computer in a paper published in Science Advances (http://advances.sciencemag.org/content/3/2/e1601540.full) giving rise to the assertion that is now possible to construct a large scale quantum computer. Hensinger recently founded, Universal Quantum, a full stack quantum computing company where he serves as Chief Scientist and Chairman.
Chief Analyst, Danske Bank
Alexandre Antonov: Chief Analyst, Danske Bank
Alexandre Antonov received his PhD degree from the Landau Institute for Theoretical Physics in 1997. He worked for Numerix during 1998-2017 and recently he has joined Danske Bank as the Chief Analyst in Copenhagen.
His activity is concentrated on modeling and numerical methods for interest rates, cross currency, hybrid, credit and CVA/FVA/MVA. AA is a published author for multiple publications in mathematical finance and a frequent speaker at financial conferences.
He has received a Quant of Year Award of Risk magazine in 2016.
Head of Research, Quantica Capital AG
Artur Sepp: Head of Research, Quantica Capital AG
Artur Sepp is Director of Research at Quantica Capital AG in Zurich focusing on development of systematic data-driven trend-following and asset allocation strategies. Prior, Artur worked at Julius Baer in Zurich as Senior Quant Strategist developing algorithmic solutions and investment strategies for the trading and portfolio advisory. Before, Artur has worked in leading roles 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 since 2006. Artur holds a PhD in Mathematical Statistics from University of Tartu, an MSc in Industrial Engineering and Management Sciences from Northwestern University, and a BA in Mathematical Economics with distinction from Tallinn University of Technology. Artur’s research and expertise are on econometric data analysis, statistical machine learning and computational methods along with designing of research and trading infrastructure and technology with applications for quantitative trading, asset allocation and wealth management. He is the author and co-author of several research articles on quantitative finance published in key journals. Artur is known for his contributions to stochastic volatility and credit risk modelling with an H-index of 15. He is a member of the editorial board of the Journal of Computational Finance.
PhD Student in Quantum Computing, UCL
Nedeen Alsharif: PhD Student in Quantum Computing, UCL
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.
XVA and Capital Quantitative Analyst, UBS
Gordon Lee: XVA and Capital Quantitative Analyst, UBS
Associate Director, Quantitative Analyst, Model Validation, Banco Santander
Ángel Rodríguez-Rozas: Associate Director, Quantitative Analyst, Model Validation, Banco Santander
Ángel Rodríguez Rozas holds a Ph.D. in Computational and Applied Mathematics from the University of Lisbon and an M.Sc. in Artificial Intelligence from the Universitat Rovira i Virgili (URV) and the Polytechnic University of Catalonia (UPC). He has authored more than 20 research articles in international peer-reviewed journals in many different areas, including artificial intelligence, numerical methods for PDEs, high-performance computing, plasma physics, the finite element method, seismic wave propagation, and oil&gas simulation and inversion of petrophysical measurements.
Ángel joined Banco Santander in 2018 where he is working as a Quant Analyst in the Internal Validation team, within the Risk Department. As part of his role, Ángel is responsible for leading the design and development of a numerical library for the internal validation of pricing models, including interest rates, FX, credit, commodities, equity, inflation, and xVA. His research efforts are currently focusing on the finance industry, investigating efficient numerical methods (Quasi- and Monte Carlo methods, Finite Elements) and quantum computing algorithms (digital and analog) for the pricing of financial derivatives.
Professor of Mathematics Université de Paris, Laboratoire de Probabilités, Statistique et Modélisation
Stéphane Crépey: Professor of Mathematics at the Université de Paris, Laboratoire de Probabilités, Statistique et Modélisation (LPSM)
Stéphane Crépey is the Professor of Mathematics at the Université de Paris, Laboratoire de Probabilités, Statistique et Modélisation (LPSM). Formerly professor at the Mathematics Department of University of Evry (France), head of Probability and Mathematical Finance and head of the Engineering and Finance branch (M2IF) of the Paris-Saclay Master Program in Financial Mathematics. His research interests are financial modeling, counterparty and credit risk, numerical finance, as well as related mathematical topics in the fields of backward stochastic differential equations and partial differential equations. He is the author of numerous research papers and two books: “Financial Modeling: A Backward Stochastic Differential Equations Perspective” (S. Crépey, Springer Finance Textbook Series, 2013) and “Counterparty Risk and Funding, a Tale of Two Puzzles” (S. Crépey, T. Bielecki and D. Brigo, Chapman & Hall/CRC Financial Mathematics Series, 2014).
He is an associate editor of SIAM Journal on Financial Mathematics, International Journal of Theoretical and Applied Finance, and a member of the scientific council of the French financial markets authority (AMF). Stéphane Crépey graduated from ENSAE and he holds a PhD in applied mathematics from Ecole Polytechnique and INRIA Sophia Antipolis.
Systematic Trading, JPMorgan Chase & Co
Ivan Zhdankin: Systematic Trading, 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.
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.
Head of Research and Development: MoCaX Intelligence
Mariano Zeron: Head of Research and Development: MoCaX Intelligence
Mariano leads our Research & Development work. He has vast experience in Chebyshev Spectral Decomposition, machine-learning and related disciplines, and their application to quantitative problems in the financial markets. Mariano holds a Ph.D. in Mathematics from Cambridge University.
Head of Fair Value Policy, Intesa Sanpaolo
Marco Bianchetti: Head of Fair Value Policy, Intesa Sanpaolo
Marco Bianchetti joined the Market Risk Management area of Intesa Marco joined the Financial and Market Risk Management area of Intesa Sanpaolo in 2008. His work covers pricing and risk management of financial instruments across all asset classes, with a focus on new products development, model validation, model risk management, interest rate modelling, funding and counterparty risk, fair and prudent valuation, applications of Quasi Monte Carlo in finance. He is in charge of the global Fair Value Policy of Intesa Sanpaolo group since Nov. 2015. Previously he worked for 8 years in the front office Financial Engineering area of Banca Caboto (now Banca IMI), developing pricing models and applications for interest rate and inflation trading desks. He is adjunct professor of Interest Rate Models at University of Bologna since 2015, and a frequent speaker at international conferences and trainings in quantitative finance. He holds a M.Sc. in theoretical nuclear physics and a Ph.D. in theoretical condensed matter physics.
Financial Analyst, Prometeia S.p.a
Pietro Rossi: Financial Analyst, Prometeia S.p.a
Pietro Rossi holds a degree in physics from the University of Parma and a Ph.D. from New York University. He has been actively doing research in the field of high energy physics in the early stage of his career and moved later on to high performance computing. In the last ten years he has been involved with mathematical finance. Currently his research activity splits between the use of Fourier transform Methods in finance and machine learning techniques applied to financial risk management.
Since 2018 he has a teaching appointment with the University of Bologna.
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.
David Jessop: Head of Investment Risk at Columbia Threadneedle Investments EMEA APAC
David is the Head of Investment Risk at Columbia Threadneedle Investments EMEA APAC. Previously the Global Head of Equities Quantitative Research at UBS. His areas of research include portfolio analysis and construction, style analysis and risk modelling. He also helps clients understand, use and implement the quantitative tools available from UBS. David joined UBS in 2002. Prior to this, he spent seven years at Citigroup as Head of Global Quantitative Marketing. Before moving to the sell side he spent six years at Morgan Grenfell Asset Management, where he managed index funds, asset allocation funds and also an option overwriting fund.
David graduated from Trinity College, Cambridge with an MA in Mathematics.
XVA and Credit Derivative Quant, Daiwa Capital Markets
Assad Bouayoun: XVA and Credit Derivative Quant, Daiwa Capital Markets
Assad Bouayoun is a senior XVA Quantitative Analyst with more than 15 years’ experience in leading banks. He has designed industry standard hedging and pricing systems, first in equity derivative at Commerzbank, then in credit derivatives at Credit Agricole, in XVA at Lloyds in Model Validation at RBS in Model Development. Assad has an extensive experience in developing enterprise wide analytics to improve the financial management of derivative portfolios, in particular large scale hybrid Monte-Carlo and Exposure computation. Assad is currently building the prototype of a new XVA platform integrating cutting-edge technologies (GPU, Cloud computing) and numerical methods (AAD) to enable fast and accurate XVA and sensitivities computation. He holds a MSc in Mathematical Trading and Finance from CASS business school and a Master in Applied Mathematics and Computer Science from Université de Technologie de Compiegne (France).
Quantitative Analyst, Deutsche Bank
Colin Turfus: Quantitative Analyst, Deutsche Bank
Colin Turfus has worked for the last twelve years as a financial engineer, mainly analysing model risk for credit derivatives and hybrids. More recently his interest has been in the application of perturbation methods to risk management, finding efficient analytic methods for computing, e.g., CVA, VaR and model risk. He is currently working in Global Model Validation and Governance at Deutsche Bank. He also taught evening courses on C++ and Financial Engineering at City University for seven years. Prior to that Colin worked as a developer consultant in the mobile phone industry after an extended period in academia, teaching applied maths and researching in fluid dynamics and turbulent dispersion.
Postdoctoral Research Assistant: Queen Mary University of London
Linus Wunderlich: Postdoctoral Research Assistant: Queen Mary University of London