Quant Summit USA

Luca Capriotti is a Managing Director at Credit Suisse, based in London, where he works in Quantitative Strategies and he is responsible for Credit Products in Europe, and globally for Corporate Bank and Treasury. Previous to this role, he was US head of Quantitative Strategies Global Credit Products, he has worked in Credit and Commodities Exotics in New York and London and in the cross-asset modeling R&D group of GMAG in the London office.
Luca is also visiting professor at the Department of Mathematics at University College London. His current research interests are in the fields of Machine Learning, Algorithmic Trading, Credit Models and Computational Finance, with a focus on applications of Adjoint Algorithmic Differentiation (AAD) for which he holds a US Patent.

Luca gives regularly gives seminars and courses worldwide. He has served as supervisor and external examiner for Master and PhD programs and as referee for several scientific publications .

Prior to working in Finance, Luca was a researcher at the Kavli Institute for Theoretical Physics, Santa Barbara, California, working in the field of High Temperature Superconductivity and Quantum Monte Carlo methods for Condensed Matter systems.

Luca holds a M.S. cum laude in General Physics from University of Florence (1996), and an M.Phil. and Ph.D. cum laude in Condensed Matter Theory, from the International School for Advanced Studies, Trieste (2000).

Peter Carr, Chair of the Finance and Risk Engineering Department, NYU TANDON SCHOOL OF ENGINEERING

Professor Peter Carr is the Chair of the Finance and Risk Engineering Department at NYU's Tandon School He has headed various quant groups in the nancial 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 nancial industry, Dr. Carr was a finance professor for 8 years at Cornell University, after obtaining his PhD 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 nance. 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 inuential people in financial technology.

Mauro Cesa, Quantitative Finance Editor, RISK.NET

Mauro Cesa is quantitative finance editor for Risk.net, based in London. He leads the team responsible for the publication of quantitative research across all brands of the division. The section of Risk.net he manages, Cutting Edge, publishes peer-reviewed papers on derivatives, asset and risk management, and commodities.

Mauro holds a degree in economics from the university of Trieste and a masters in quant finance from the University of Brescia.

Jim Gatheral is Presidential Professor of Mathematics at Baruch College, CUNY teaching mostly courses in the Masters of Financial Engineering (MFE) program. Prior to joining the faculty of Baruch College, Jim was involved in all of the major derivative product areas as bookrunner, risk manager, and quantitative analyst in London, Tokyo and New York, in a career in the financial industry that spanned over 27 years. Jim has served as a Managing Editor of the International Journal of Theoretical and Applied Finance and as Associate Editor of the SIAM Journal on Financial Mathematics; he currently serves as Joint Editor-in-Chief of Quantitative Finance with Michael Dempster. His current research focus is on volatility modeling and modeling equity market microstructure for algorithmic trading. Jim is also a frequent speaker at both practitioner and academic conferences around the world. His best-selling book, The Volatility Surface: A Practitioner's Guide (Wiley 2006) is one of the standard references on the subject of volatility modeling. He received his Ph.D. in theoretical physics from Cambridge University.

Igor Halperin is currently an Adjunct Professor of Financial Machine Learning at the NYU Tandon School of Engineering. Prior to that, he was an Executive Director of Quantitative Research at JPMorgan Chase where we focused on the research and development of predictive and statistical models and machine learning methods for modeling risk of financial portfolios. He has authored a number of publications on quantitative finance, and is a frequent speaker at financial conferences. Dr. Halperin has a Ph.D. in theoretical physics from Tel Aviv University, and M.Sc. in nuclear physics from St. Petersburg State Technical 

Dr. Marcos López de Prado is the chief executive officer of True Positive Technologies. He founded Guggenheim Partners’ Quantitative Investment Strategies (QIS) business, where he applied cutting-edge machine learning (ML) to the development of high-capacity strategies that delivered superior risk-adjusted returns. After managing up to $13 billion in assets, Marcos acquired QIS and successfully spun-out that business from Guggenheim in 2018.

Since 2010, Marcos has been a research fellow at Lawrence Berkeley National Laboratory (U.S. Department of Energy, Office of Science). One of the top-10 most read authors in finance (SSRN's rankings), he has published dozens of scientific articles on ML and supercomputing in the leading academic journals, and he holds multiple international patent applications on algorithmic trading.

Marcos earned a PhD in Financial Economics (2003), a second PhD in Mathematical Finance (2011) from Universidad Complutense de Madrid, and is a recipient of Spain's National Award for Academic Excellence (1999). He completed his post-doctoral research at Harvard University and Cornell University, where he teaches a Financial ML course at the School of Engineering. Marcos has an Erdős #2 and an Einstein #4 according to the American Mathematical Society.

Dr. Marcos López de Prado is the chief executive officer of True Positive Technologies. He founded Guggenheim Partners’ Quantitative Investment Strategies (QIS) business, where he applied cutting-edge machine learning (ML) to the development of high-capacity strategies that delivered superior risk-adjusted returns. After managing up to $13 billion in assets, Marcos acquired QIS and successfully spun-out that business from Guggenheim in 2018.

Since 2010, Marcos has been a research fellow at Lawrence Berkeley National Laboratory (U.S. Department of Energy, Office of Science). One of the top-10 most read authors in finance (SSRN's rankings), he has published dozens of scientific articles on ML and supercomputing in the leading academic journals, and he holds multiple international patent applications on algorithmic trading.

Marcos earned a PhD in Financial Economics (2003), a second PhD in Mathematical Finance (2011) from Universidad Complutense de Madrid, and is a recipient of Spain's National Award for Academic Excellence (1999). He completed his post-doctoral research at Harvard University and Cornell University, where he teaches a Financial ML course at the School of Engineering. Marcos has an Erdős #2 and an Einstein #4 according to the American Mathematical Society.

Dilip Madan, ‎Professor at Robert H. Smith School of Business, UNIVERSITY OF MARYLAND

Dilip Madan is Professor of Finance at the Robert H. Smith School of Business. He specializes in Mathematical Finance. Currently he serves as a consultant to Morgan Stanley, Meru Capital and Caspian Capital. He has also consulted with Citigroup, Bloomberg, the FDIC and Wachovia Securities. He is a founding member and Past President of the Bachelier Finance Society. He received the 2006 von Humboldt award in applied mathematics, was the 2007 Risk Magazine Quant of the year, received the 2008 Medal for Science from the University of Bologna and held the 2010 Eurandom Chair. He is Man- aging Editor of Mathematical Finance, Co-editor of the Review of Derivatives Research, Associate Editor of the Journal of Credit Risk and Quantitative Finance. His work is dedicated to improving the quality of financial valuation models, enhancing the performance of investment strategies, and advancing the efficiency of risk allocation in modern economies. Recent major contributions have appeared inMathematical Finance, Finance and Stochastics, Quantitative Finance, the Journal of Computational Finance, The International Journal of Theoretical and Applied Finance, The Journal of Risk, The Journal of Credit Risk among other journals.

Stefano Pasquali, Managing Director, Head of Liquidity Research, BLACKROCK

Stefano Pasquali Managing Director, is the Head of Liquidity Research Group at BlackRock Solutions. As Head of Liquidity Research, Mr. Pasquali is responsible for market liquidity modelling both at the security and portfolio level, as well as estimating portfolio liquidity risk profiles. His responsibilities include defining cross asset class models, leveraging available trade data and developing innovative machine learning based approaches to better estimate market liquidity. Mr. Pasquali is heavily involved in developing methodologies to estimate funding liquidity and better estimate funds flows. These models include: the cost of position or portfolio liquidation, time to liquidation, redemption estimation, and investor behavior modelling utilizing a big data approach. Stefano is a member of the Government Relations Steering Committee within BlackRock.

Previous to Blackrock, Mr. Pasquali oversaw product development and research for Bloomberg's liquidity solution, introducing a big data approach to their financial analytics. His team designed and implemented models to estimate liquidity and risk across different asset classes with a particular focus on OTC markets. Before this he lead business development and research for fixed income evaluated pricing.
Mr. Pasquali has more than 15 years of experience examining and implementing innovative approaches to calculating risk and market impact. He regularly speaks at industry events about the complexity and challenges of liquidity evaluation ̶ particularly in the OTC marketplace. His approach to risk and liquidity evaluation is strongly influenced by over 20 years of experience working with big data, data mining, machine learning and data base management.

Prior to moving to New York in 2010, Mr. Pasquali held senior positions at several European banks and asset management firms where he oversaw risk management, portfolio risk analysis, model development and risk management committees. These accomplishments include the construction of a risk management process for a global asset management firm with over 100 Billion AUM. This involved driving projects from data acquisition and normalization to model development and portfolio management support.

Mr. Pasquali, a strong believer in academic contribution to the industry, has engaged in various conversations and collaborations with universities from the US, UK, and Italy. He also participates as a supervisor in the Experiential Learning Program and Masters of Quantitative Finance Program based at Rutgers University, along with tutoring students in research activities.

Before his career in finance, Mr. Pasquali was a researcher in Theoretical and Computational Physics (in particular Monte Carlo Simulation, Solid State physics, Environment Science, Acoustic Optimization). Originally from Carrara (Tuscany, Italy), he grew up in Parma. Mr. Pasquali is a graduate of Parma University and holds a master's degree in Theoretical Physics, as well as research fellowships in Computational Physics at Parma University and Reading University (UK).

Peter Carr, Chair of the Finance and Risk Engineering Department, NYU TANDON SCHOOL OF ENGINEERING

Professor Peter Carr is the Chair of the Finance and Risk Engineering Department at NYU's Tandon School He has headed various quant groups in the nancial 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 nancial industry, Dr. Carr was a finance professor for 8 years at Cornell University, after obtaining his PhD 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 nance. 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 inuential people in financial technology.

Luca Capriotti is a Managing Director at Credit Suisse, based in London, where he works in Quantitative Strategies and he is responsible for Credit Products in Europe, and globally for Corporate Bank and Treasury. Previous to this role, he was US head of Quantitative Strategies Global Credit Products, he has worked in Credit and Commodities Exotics in New York and London and in the cross-asset modeling R&D group of GMAG in the London office.
Luca is also visiting professor at the Department of Mathematics at University College London. His current research interests are in the fields of Machine Learning, Algorithmic Trading, Credit Models and Computational Finance, with a focus on applications of Adjoint Algorithmic Differentiation (AAD) for which he holds a US Patent.

Luca gives regularly gives seminars and courses worldwide. He has served as supervisor and external examiner for Master and PhD programs and as referee for several scientific publications .

Prior to working in Finance, Luca was a researcher at the Kavli Institute for Theoretical Physics, Santa Barbara, California, working in the field of High Temperature Superconductivity and Quantum Monte Carlo methods for Condensed Matter systems.

Luca holds a M.S. cum laude in General Physics from University of Florence (1996), and an M.Phil. and Ph.D. cum laude in Condensed Matter Theory, from the International School for Advanced Studies, Trieste (2000).

Dr. Vasil S. Denchev is the Chief Quantum Software Architect of the Quantum Artificial Intelligence Lab at Google. He received his PhD in Computer Science from Purdue University. Vasil's PhD research gave impetus to the founding in 2013 of the Quantum Artificial Intelligence Lab by pioneering important techniques allowing for the successful application of quantum annealing to statistical machine learning and computer vision problems. Currently Vasil is studying the computational effects of quantum tunneling and many-body delocalization via experimentation with existing quantum processors as well as distributed large-scale numerical simulations of various quantum and classical computational models. Most recently, in recognition of his overall contributions to the computing sciences, Vasil received the prestigious John Atanasoff Award from the President of Bulgaria.

Suresh Baral is a Managing Director in Protiviti’s Model Risk practice within the Data Management and Advanced Analytics solution. He has 20 years of experience in leading model development and model validation; economic capital modeling, stress testing, loss forecasting, managing credit risk of consumer loan portfolios, and improving portfolio performance through use of analytical data driven approaches.

Jonathan Briggs joined CPPIB in early 2010 as the head of Implementation Research for Global Tactical Asset Allocation.  In 2012 he switched roles to head Quantitative Alpha Research for the Quantitative Equity team. The equity team currently manages a large, market neutral, global equity portfolio and has recently been instrumental in the exploration and use of alternative data and machine learning techniques for forecasting. Prior to CPPIB Jonathan was a Research Officer at Barclays Global Investors with both the global macro and active equity research teams. He has a Ph.D. from the University of Pennsylvania in Control Theory, a M.S. in Engineering from Dartmouth and undergraduate degrees from California Institute of Technology and Bowdoin College.

 

Vern Brownell, Chief Executive Officer, D-WAVE SYSTEMS

Vern Brownell joined D-Wave as CEO in 2009, leading the company through its transition from research into the leader in the development and delivery of quantum computing systems and software. During his tenure D-Wave secured its first customers including Lockheed Martin, Google and NASA, Los Alamos National Laboratory, and raised over $100 million in venture funding. Mr. Brownell joined D-Wave from Egenera, a pioneer of infrastructure virtualization, a company he founded and at which he held executive roles including CEO. Prior to Egenera, Mr. Brownell served as the Chief Technology Officer at Goldman Sachs where he and his staff of 1,300 were responsible for worldwide technology infrastructure. He holds an MBA degree from Anna Maria College and a BEng. degree in Electrical Engineering from Stevens Institute of Technology.

Mauricio Bustos joined Rosenberg Equities in 1999 as a research analyst and currently serves as Data Architect in the Investment Platform Technology group. He has a BS in Mechanical/Aerospace Engineering from the University of Michigan at Ann Arbor and an MBA from the Haas School of Business at the University of California, Berkeley. He is a CFA charterholder

Over the past 15 years, Dr. Ben Dor oversaw large scale research projects in rates, credit, equities, and hedge funds used by the largest institutional investors globally, including central banks, Sovereign wealth funds, asset managers, insurance companies, pensions and hedge funds. His research focused on asset allocation, smart beta, alpha generation, portfolio optimization, risk management, cost of investment constraints and hedging.

He published two books on quantitative investing in credit securities and over a dozen articles in leading industry journals such as the Journal of Portfolio Management, Journal of Fixed Income, Journal of Investment Management, and Journal of Alternative Investments.

He co-authored the influential articles on ‘DTS (Duration Times Spread)', a new approach to measuring the spread risk of corporate bonds and credit default swaps. It changed industry practices and was widely adopted by credit investors globally. One of his articles received the Martello award for the 2007 best practitioner paper, and his research on ‘cloning' hedge funds was the basis for several products and was awarded a U.S. patent.

His recent work on exploring the cross-asset relation between stocks and bonds was the basis for constructing systematic equity strategies such as momentum and ‘value' based on credit signals, and the usage of equity derivatives for hedging high-yield bonds. His systematic strategies were adopted by some of the largest global asset managers and were presented in leading industry conferences.

Prior to his current role, Dr. Ben Dor worked at Lehman Brothers and Morgan Stanley. He holds a PhD in Finance from the Kellogg Business School at Northwestern University, and completed his B.A. and M.A. in Economics from Tel Aviv University, Cum Laude.

Lucia is a professional with 10 years of experience in quantitative finance, both in pricing and risk modelling. Her areas of specialization are: Counterparty Risk and Collateral Modelling. Lucia holds an MSC in Mathematics from the Courant Institute at NYU.

Prof. Rama Cont holds the Chair of Mathematical Finance at Imperial College London and is director of the CFM-Imperial Institute of Quantitative Finance since 2012, after previous appointments at Ecole Polytechnique (France), Columbia University (New York) and Sorbonne (Paris).

His research in finance has focused on modeling of extreme market risks: market discontinuities and breakdowns, liquidity risk, endogenous risk and systemic risk. His 2006 paper on ‘model risk', an early reference on the topic, was the first to propose a quantitative approach to model risk.

Cont has served as a consultant to the BIS, the European Central Bank, the New York Federal Reserve, Norges Bank, the US Commodity Futures Commission (CFTC), the US Office of Financial Research, the IMF and a dozen major CCPs in Europe, Asia, the US and Latin America.

He was awarded the Louis Bachelier Prize by the French Academy of Sciences in 2010 and the Royal Society Award for Excellence in Interdisciplinary Research in 2017 for his research on mathematical modeling in finance.

Indrani De, CFA, PRM, is Managing Director of Macro & Country Risk, in Enterprise Risk Management at TIAA. Her responsibilities include macroeconomic and financial markets analysis, economic forecasting, key risk indicators and asset class outlook, stress testing and sensitivity analysis, and identification and evaluation of emerging risks. Prior to TIAA, she was Senior Director of Quantitative Research at institutional buy-side investment firm New Amsterdam Partners. Earlier in her career, she worked as an investment analyst for GE Capital and 20th Century Venture Capital. She has been published in the Journal of Investing, Journal of Investment Consulting and NYSSA Financial Professionals' Post. Indrani is a past president and on the Board of Directors of the Society of Quantitative Analysts (SQA). She has been a frequent speaker at leading industry conferences and been quoted in major media outlets like Reuters, Forbes and Financial Planning. Indrani received an undergraduate degree in Economics (Honors) from University of Delhi, and an MBA from the Indian Institute of Management (Bangalore). She completed the coursework for a PhD (Business-Major in Finance) at the City University of New York with a full merit scholarship, and holds the Chartered Financial Analyst and Professional Risk Manager designations. Indrani lives in Livingston, New Jersey and enjoys reading on a wide range of subjects and travelling the world. She has travelled to more than forty countries.

Andrew Dickinson is a senior quantitative analyst at Bank of America focussing on the modelling of central counterparties (CCPs). Prior to his current role he was responsible for FVA modelling at JP Morgan preceded by a number of years working on the pricing of exotic interest rate derivatives at Bank of America Merrill Lynch and JP Morgan.

He holds a doctorate in probability theory from the University of Oxford.

Peg DiOrio is the head of quantitative equity at Voya Investment Management and serves as a portfolio manager for the Voya Natural Resources Equity Income and Infrastructure, Industrials and Materials funds. Prior to joining the firm, she was a quantitative analyst with Alliance Bernstein/Sanford C. Bernstein for sixteen years where she was responsible for multivariate and time series analysis for low volatility strategies, global equities, REITs and options. Previously she was a senior investment planning analyst with Sanford C. Bernstein. Peg received an MS in Applied Mathematics, Statistics and Operations Research from the Courant Institute of Mathematical Sciences, NYU and a BS from SUNY Stony Brook. She holds the Chartered Financial Analyst® designation and is a Past President and current board member of the Society of Quantitative Analysts.

Dan Furstenberg is a Managing Director and has worked at Jefferies for over ten years, managing New York Equity Sales, creating the Jefferies Global Data Strategy and serving as a member of its Equity Committee.  Dan has advised over seventy investment managers’ data science teams on their build-out efforts and evaluated over one hundred data vendors.  Dan recently co-authored two pieces of data-centric content including a whitepaper on Data Science and the Buy Side and another proprietary data survey. Dan began his career in investment banking, focusing on leveraged finance at Merrill Lynch before joining the tech banking team at Credit Suisse First Boston.   

Education: 

Ph.D. in Theoretical Physics, Brown University. 

Experience:

Wells Fargo Securities, Quantitative Analyst (Director) New York City, November 2010 - present

Morgan Stanley, Quantitative analyst (Executive Director), New York City, Aug. 2003-Nov. 2010

Jim Gatheral is Presidential Professor of Mathematics at Baruch College, CUNY teaching mostly courses in the Masters of Financial Engineering (MFE) program. Prior to joining the faculty of Baruch College, Jim was involved in all of the major derivative product areas as bookrunner, risk manager, and quantitative analyst in London, Tokyo and New York, in a career in the financial industry that spanned over 27 years. Jim has served as a Managing Editor of the International Journal of Theoretical and Applied Finance and as Associate Editor of the SIAM Journal on Financial Mathematics; he currently serves as Joint Editor-in-Chief of Quantitative Finance with Michael Dempster. His current research focus is on volatility modeling and modeling equity market microstructure for algorithmic trading. Jim is also a frequent speaker at both practitioner and academic conferences around the world. His best-selling book, The Volatility Surface: A Practitioner's Guide (Wiley 2006) is one of the standard references on the subject of volatility modeling. He received his Ph.D. in theoretical physics from Cambridge University.

Julien is a senior quantitative analyst in the Quantitative Research group at Bloomberg L.P., New York. He is also an adjunct professor in the Department of Mathematics at Columbia University and at the Courant Institute of Mathematical Sciences, NYU. Before joining Bloomberg, Julien worked in the Global Markets Quantitative Research team at Societe Generale in Paris for six years (2006-2012), and was an adjunct professor at Universite Paris 7 and Ecole des ponts. He co-authored the book Nonlinear Option Pricing (Chapman & Hall, CRC Financial Mathematics Series, 2014) with Pierre Henry-Labordere. His main research interests include nonlinear option pricing, volatility and correlation modeling, and numerical probabilistic methods. Julien holds a Ph.D. in Probability Theory and Statistics from Ecole des ponts. He graduated from Ecole Polytechnique (Paris), Universite Paris 6, and Ecole des ponts. A big football fan, Julien has also developed a strong interest in sports analytics, and has published several articles on the FIFA World Cup, the UEFA Champions League, and the UEFA Euro in top-tier newspapers such as The New York Times, Le Monde, and El Pais, including a new, fairer draw method for the FIFA World Cup.

Igor Halperin is currently an Adjunct Professor of Financial Machine Learning at the NYU Tandon School of Engineering. Prior to that, he was an Executive Director of Quantitative Research at JPMorgan Chase where we focused on the research and development of predictive and statistical models and machine learning methods for modeling risk of financial portfolios. He has authored a number of publications on quantitative finance, and is a frequent speaker at financial conferences. Dr. Halperin has a Ph.D. in theoretical physics from Tel Aviv University, and M.Sc. in nuclear physics from St. Petersburg State Technical 

Bernhard Hientzsch, Director, Head of Model, Library, and Tools Development for Corporate Model Risk, WELLS FARGO

Bernhard Hientzsch is the Head of Model, Library, and Tool Development in the Corporate Model Risk Management Group at Wells Fargo. His group is responsible for the implementation of models, libraries, components, and tools for the validation, benchmarking, and oversight of models at Wells Fargo. Prior to joining Wells Fargo, he was a postdoctoral scientist at New York University in several DoE supported projects and consulting on mathematical, financial, and computer modelling in the USA and Germany. Bernhard received his PhD in applied mathematics from the Courant Institute at New York University.

Andrey Itkin, Director, Senior Quant Research Associate, BANK OF AMERICA

Dr. Andrey Itkin is an Adjunct Professor at NYU, Department of Risk and Financial Engineering and Director, Senior Research Associate at Bank of America. He received his PhD in physics of liquids, gases and plasma, and degree of Doctor of Science in computational physics. During his academic carrier he published few books and multiple papers on chemical and theoretical physics and astrophysics, and later on computational and mathematical finance. Andrey occupied various research and managerial positions in financial industry and also is a member of multiple professional associations in finance and physics.

Amit is the head of quantitative research and PM at Blockseed Investments, New York. His fund invests in digital assets and cryptocurrencies using quantitative and systematic strategies. 

Amit is an investment professional with over twelve years of Wall Street Sell Side and Buy Side experience. He is a successful quantitative researcher with extensive experience in modeling and development of Interest Rate Structured Products, Commodities Exotics, and Cross Currency Correlation Options. His experience includes quantitative strategist/researcher/analyst roles with the structured products trading desk at the Bank of America, commodities and rates exotics derivatives at the Barclays, and commodities and FX at the Millennium Management.

Amit received an MS focussed on quantitative research in Business from the Penn State and an MS and BS in Engineering from IIT Bombay. He holds the Chartered Financial Analyst® and the Certificate in Quantitative Finance® designations.

Petter Kolm, Director of the Mathematics in Finance Masters Program and Clinical Professor, Courant Institute of Mathematical Sciences, NEW YORK UNIVERSITY

Petter Kolm is the Director of the Mathematics in Finance Masters Program and Clinical Associate Professor at the Courant Institute of Mathematical Sciences, New York University and the Principal of the Heimdall Group, LLC. 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 coauthored the 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 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 the board of directors of the International Association for Quantitative Finance (IAQF). As a consultant and expert witness, he has provided his services in areas such as algorithmic and quantitative trading strategies, econometrics, forecasting models, portfolio construction methodologies incorporating transaction costs, and risk management procedures.

Christos is the founder and CIO at Atlas Ridge Capital, a quantitative multi strategy hedge fund in the new data and machine learning space. Prior to Atlas Ridge, Christos was a Portfolio Manager at the Multi-Asset Solutions business at AllianceBernstein, and a Senior Investment Manager at State Street Global Advisors where he managed long-only and long-short active equity strategies. Prior to that, Christos was the Deputy Head of Quant Research at Old Mutual Asset Managers in London, leading research on existing products, proprietary strategies and new products. He concentrated on Equity Market Neutral strategies, as well GTAA, Currency, Volatility Arbitrage and other products.

Christos received a BA (Hons) in Economics from the University of Cambridge, UK, an MSc in Mathematical Finance from Brunel University, UK, and is currently working towards a part-time PhD in Financial Economics at Birkbeck College, UK.

He is on the board of directors of the Society of Quantitative Analysts (SQA) and served on the board of directors of the Institute of Quantitative Investment Research (Inquire UK), from 2005 – 2016.

Donny Lee is a Quantitative Trader in BNP Paribas working on HFT strategies that trade G10 FX on multiple exchanges. Prior to BNP Paribas, Mr. Lee worked at Ortus Capital Management in Hong Kong where he traded FX based on price moves in the futures market. Mr. Lee began his career at Rhicon Currency Management in Singapore. He holds a B.S. in Mathematics and Computer Science from Duke University.

George Lentzas, Manager & Chief Data Scientist and Adjunct Associate Professor, SPRINGFIELD CAPITAL MANAGEMENT, COLUMBIA BUSINESS SCHOOL & NEW YORK UNIVERSITY

Dr. George A. Lentzas (Springfield Capital Management, Columbia Business School and NYU) is a statistics expert with a decade of experience in applying quantitative models in the real world. He has worked in various capacities at a number of leading financial institutions, including Morgan Stanley, BNP Paribas, Citigroup and Hutchin Hill Capital. He has also held faculty positions at both Columbia University and New York University, where he has taught courses in Machine Learning and Applied Statistics & Econometrics. His professional expertise includes the application of statistics, machine learning and artificial intelligence to finance and economics. He is currently the Chief Data Scientist and Manager of Springfield Capital Management, a NY based start-up quantitative hedge fund, as well as an Adjunct Associate Professor of Business at Columbia Business School and of Economics at New York University. He holds a PhD, MPhil and BA from Oxford University, an MPhil from Cambridge University and has been a Visiting Fellow at the Department of Economics, Harvard University.

Yadong Li is currently the head of Portfolio Central modeling team in Quantitative Analytics of Barclays. Previously he held leadership roles in various areas of quantitative modeling in Lehman and Barclays, including Credit Correlation, Emerging Market Credit, Basel 2.5 Market Risk and Basel 3 Counterparty Exposure Risk etc. His current research interests are in XVA and regulatory capital modeling, including stress testing, CCAR, FRTB, back-testing, risk capital allocation and optimization etc. Yadong held a Ph.D. in Physics and a MS in Computer Sciences from Wisconsin-Madison, and a Master in Financial Engineering degree from UC-Berkeley.

Alexander Lipton is Founder and CEO of Stronghold Labs, Co-Founder of Distilled Analytics, Co-Founder of Sila, Partner at Numeraire Financial, Connection Science Fellow at MIT, and Visiting Professor of Financial Engineering at EPFL. He sits on the Board of Directors of Zilliqa (Singapore) and on Advisory Boards of several FinTech Companies, including Clearmatics (London), Endor (Tel Aviv), Metaco (Geneva), Zilliqa (Singapore), and a few more.

In 2016 he left Bank of America Merrill Lynch, where he served for ten years in various senior managerial roles including Quantitative Solutions Executive and Co-Head of the Global Quantitative Group. Earlier, he held senior managerial positions at Citadel Investment Group, Credit Suisse, Deutsche Bank, and Bankers Trust.
In parallel, Alex held several prestigious academic appointments at NYU, Oxford University, Imperial College, and the University of Illinois. Before switching to finance, Alex was a Full Professor of Mathematics at the University of Illinois and a Consultant at Los Alamos National Laboratory.

In 2000 Alex was awarded the first ever Quant of the Year Award by Risk Magazine. Alex published eight books and more than a hundred scientific papers. His book “Financial Engineering - Selected Works of Alexander Lipton” has been published in May of 2018.

Julia Litvinova is the Head of Model Validation and Analytics at State Street. In this role Julia is responsible for supervising validation of a broad range of models for credit, market, ALM, liquidity risks and asset management at State Street as well as quantifying and managing model risk at the firm-wide level.

Prior to joining State Street Julia worked at the Brattle Group, the economic litigation consulting company. She received her Ph.D. in Economics from Duke University, M.A. in Economics from New Economics School and M.S. in Mathematics from Moscow State University.

Dr. Marcos López de Prado is the chief executive officer of True Positive Technologies. He founded Guggenheim Partners’ Quantitative Investment Strategies (QIS) business, where he applied cutting-edge machine learning (ML) to the development of high-capacity strategies that delivered superior risk-adjusted returns. After managing up to $13 billion in assets, Marcos acquired QIS and successfully spun-out that business from Guggenheim in 2018.

Since 2010, Marcos has been a research fellow at Lawrence Berkeley National Laboratory (U.S. Department of Energy, Office of Science). One of the top-10 most read authors in finance (SSRN's rankings), he has published dozens of scientific articles on ML and supercomputing in the leading academic journals, and he holds multiple international patent applications on algorithmic trading.

Marcos earned a PhD in Financial Economics (2003), a second PhD in Mathematical Finance (2011) from Universidad Complutense de Madrid, and is a recipient of Spain's National Award for Academic Excellence (1999). He completed his post-doctoral research at Harvard University and Cornell University, where he teaches a Financial ML course at the School of Engineering. Marcos has an Erdős #2 and an Einstein #4 according to the American Mathematical Society.

Dr. Marcos López de Prado is the chief executive officer of True Positive Technologies. He founded Guggenheim Partners’ Quantitative Investment Strategies (QIS) business, where he applied cutting-edge machine learning (ML) to the development of high-capacity strategies that delivered superior risk-adjusted returns. After managing up to $13 billion in assets, Marcos acquired QIS and successfully spun-out that business from Guggenheim in 2018.

Since 2010, Marcos has been a research fellow at Lawrence Berkeley National Laboratory (U.S. Department of Energy, Office of Science). One of the top-10 most read authors in finance (SSRN's rankings), he has published dozens of scientific articles on ML and supercomputing in the leading academic journals, and he holds multiple international patent applications on algorithmic trading.

Marcos earned a PhD in Financial Economics (2003), a second PhD in Mathematical Finance (2011) from Universidad Complutense de Madrid, and is a recipient of Spain's National Award for Academic Excellence (1999). He completed his post-doctoral research at Harvard University and Cornell University, where he teaches a Financial ML course at the School of Engineering. Marcos has an Erdős #2 and an Einstein #4 according to the American Mathematical Society.

Dilip Madan, ‎Professor at Robert H. Smith School of Business, UNIVERSITY OF MARYLAND

Dilip Madan is Professor of Finance at the Robert H. Smith School of Business. He specializes in Mathematical Finance. Currently he serves as a consultant to Morgan Stanley, Meru Capital and Caspian Capital. He has also consulted with Citigroup, Bloomberg, the FDIC and Wachovia Securities. He is a founding member and Past President of the Bachelier Finance Society. He received the 2006 von Humboldt award in applied mathematics, was the 2007 Risk Magazine Quant of the year, received the 2008 Medal for Science from the University of Bologna and held the 2010 Eurandom Chair. He is Man- aging Editor of Mathematical Finance, Co-editor of the Review of Derivatives Research, Associate Editor of the Journal of Credit Risk and Quantitative Finance. His work is dedicated to improving the quality of financial valuation models, enhancing the performance of investment strategies, and advancing the efficiency of risk allocation in modern economies. Recent major contributions have appeared inMathematical Finance, Finance and Stochastics, Quantitative Finance, the Journal of Computational Finance, The International Journal of Theoretical and Applied Finance, The Journal of Risk, The Journal of Credit Risk among other journals.

Fabio is global head of Quantitative Analytics at Bloomberg LP, New York. His team is responsible for the research on and implementation of cross-asset analytics for derivatives pricing, XVA valuations and credit and market risk. Fabio is also adjunct professor at NYU, and a former CME risk committee member. He has jointly authored the book 'Interest rate models: theory and practice' and published extensively in books and international journals, including 16 cutting-edge articles in Risk Magazine. Fabio holds a BSc in Applied Mathematics from the University of Padua, Italy, and a PhD in Mathematical Finance from the Erasmus University of Rotterdam, The Netherlands

Miquel Noguer i Alonso, Chief Development Officer, GLOBAL AI

Miquel Noguer i Alonso is a financial markets practitioner with more than 20 years of experience in asset management.

He is currently Chief Development Officer for Global AI a a Big Data Company that uses State-of-the-Art Statistical and Artificial Intelligence models to produce actionable insights, signals and alternative data for institutional clients, including Investors, Governments and Corporations.
He worked for UBS AG (Switzerland) 10 years as Executive Director. He acted a member of European Investment Committee. He worked as a Chief Investment Office and CIO for Andbank from 2000 to 2006. He started his career at KPMG.

He is Adjunct Professor at Columbia University teaching Asset Allocation, Big Data in Finance and Fintech. He is also Professor at ESADE teaching Hedge Fund, Big Data in Finance and Fintech. He taught the first Fintech and Big Data course at the London Business School in 2017.

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 completed a Postdoc in Columbia Business School in 2012. He collaborated with the Mathematics department of Fribourg during his PhD. He also holds the Certified European Financial Analyst (CEFA) 2000.

His research interests range from asset allocation, big data, machine learning 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 giving presentations in Indiana University, ESADE and CAIA and several industry seminars like the Quant Summit USA 2017 and 2010.

Stefano Pasquali, Managing Director, Head of Liquidity Research, BLACKROCK

Stefano Pasquali Managing Director, is the Head of Liquidity Research Group at BlackRock Solutions. As Head of Liquidity Research, Mr. Pasquali is responsible for market liquidity modelling both at the security and portfolio level, as well as estimating portfolio liquidity risk profiles. His responsibilities include defining cross asset class models, leveraging available trade data and developing innovative machine learning based approaches to better estimate market liquidity. Mr. Pasquali is heavily involved in developing methodologies to estimate funding liquidity and better estimate funds flows. These models include: the cost of position or portfolio liquidation, time to liquidation, redemption estimation, and investor behavior modelling utilizing a big data approach. Stefano is a member of the Government Relations Steering Committee within BlackRock.

Previous to Blackrock, Mr. Pasquali oversaw product development and research for Bloomberg's liquidity solution, introducing a big data approach to their financial analytics. His team designed and implemented models to estimate liquidity and risk across different asset classes with a particular focus on OTC markets. Before this he lead business development and research for fixed income evaluated pricing.
Mr. Pasquali has more than 15 years of experience examining and implementing innovative approaches to calculating risk and market impact. He regularly speaks at industry events about the complexity and challenges of liquidity evaluation ̶ particularly in the OTC marketplace. His approach to risk and liquidity evaluation is strongly influenced by over 20 years of experience working with big data, data mining, machine learning and data base management.

Prior to moving to New York in 2010, Mr. Pasquali held senior positions at several European banks and asset management firms where he oversaw risk management, portfolio risk analysis, model development and risk management committees. These accomplishments include the construction of a risk management process for a global asset management firm with over 100 Billion AUM. This involved driving projects from data acquisition and normalization to model development and portfolio management support.

Mr. Pasquali, a strong believer in academic contribution to the industry, has engaged in various conversations and collaborations with universities from the US, UK, and Italy. He also participates as a supervisor in the Experiential Learning Program and Masters of Quantitative Finance Program based at Rutgers University, along with tutoring students in research activities.

Before his career in finance, Mr. Pasquali was a researcher in Theoretical and Computational Physics (in particular Monte Carlo Simulation, Solid State physics, Environment Science, Acoustic Optimization). Originally from Carrara (Tuscany, Italy), he grew up in Parma. Mr. Pasquali is a graduate of Parma University and holds a master's degree in Theoretical Physics, as well as research fellowships in Computational Physics at Parma University and Reading University (UK).

Gregory Pelts, Quant, BLACKROCK

Dr. Gregory Pelts has been working in the financial industry for over a decade. He completed his training in mathematics and physics at the St Petersburg State University and the Steklov Mathematical Institute in Russia. He received his second Ph.D. in Theoretical Physics from the Rockefeller University in New York. Gregory has authored a number of publications and given presentations in theoretical physics and quantitative finance. Gregory is currently employed by BlackRock. Prior to that, he worked for Goldman Sachs, Bear Stearns and Dresdner-Kleinwort-Benson. Gregory focuses on applications of group theoretical methods to problems in quantitative finance, in particular, stochastic interest rates, stochastic volatility, and credit risk.

Ken created the Risk Management department at Och Ziff and served as Chief Risk Officer for over 13 years. He led the Firm through a five-fold increase in AUM and headcount, the transition from private to public company, and managed major and minor financial/business crises and the introduction of new strategies and products.
He pioneered the use of quantitative techniques for portfolio construction and analysis at a fundamentally oriented firm, anticipating the “quantamental” revolution. Most recent activities have focused on how Artificial Intelligence may adapted to Finance.

Michael Pykhtin, Manager, Quantitative Risk, FEDERAL RESERVE BOARD

Michael Pykhtin is a manager in the Quantitative Risk section at the U.S. Federal Reserve Board. Prior to joining the Board in 2009 as a senior economist, he had a successful nine-year career as a quantitative researcher at Bank of America and KeyCorp. Michael has edited “Counterparty Risk Management” (Risk Books, 2014) and “Counterparty Credit Risk Modelling” (Risk Books, 2005); he is also a contributing author to several recent edited collections. Michael has published extensively in the leading industry journals; he has been an Associate Editor of the Journal of Credit Risk since 2007. Michael is a two-time recipient of Risk Magazine's Quant of the Year award (for 2014 and 2018). Michael holds a Ph.D. degree in Physics from the University of Pennsylvania and an M.S. degree in Physics and Applied Mathematics from Moscow Institute of Physics and Technology.

Gordon Ritter completed his PhD in mathematical physics at Harvard University in 2007, where his published work ranged across the fields of quantum computation, quantum field theory, differential geometry, and abstract algebra.

Gordon is currently a senior portfolio manager at GSA Capital, and leader of a team trading a range of high-Sharpe absolute return strategies across geographies and asset classes.

Prior to joining GSA, Gordon was a Vice President of Highbridge Capital and a core member of the firm's statistical arbitrage group, which although less than 20 people, was one of the most successful quantitative trading groups
in history, responsible for billions in profit and trillions of dollars of trades across equities, futures and options.

Concurrently with his positions in industry, Gordon teaches courses ranging from portfolio management to econometrics at Rutgers University, and also at Baruch College (CUNY) and New York University. He has also published several articles on modern portfolio theory in top practitioner journals.

Riti Samanta is a managing director and part of the Senior Leadership Team (SLT) at State Street Global Advisors. She is responsible for the development of smart beta fixed income, currency, and active rates investment strategies for SSGA. Previously, she headed the Asset Allocation and Currency research teams developing investible strategies in these areas using quantitative models for return forecasting, risk measurement, and portfolio construction. She is part of the Fixed Income, Cash and Currency (FICC) SLT and a member of the Technical Committee that evaluates all quantitative research in the firm. She is a senior portfolio manager in FICC.

Before joining SSGA, Riti was a senior research associate at State Street Associates using institutional flows, holdings and market returns to forecast investor behavior in equity and currency markets. She has published research on Extreme Value Theory, studying the effect of incorporating non-normalities and time-sensitive correlation structures in various aspects of quantitative modeling. Her research has been published in the Journal of Performance Measurement and presented at the Society for Nonlinear Dynamics and Econometrics.

Riti holds a PhD in international finance and economics from Brandeis University, a MS in finance from Brandeis, and a BA in economics (minor in mathematics) from Reed College, where she held the Walter Mintz scholarship in economics.

Dr. Ronnie Shah joined Deutsche Bank in March 2017 as a Director and Head of US Quantitative Research and Quantitative Investment Solutions. Prior to Deutsche Bank, he led quantitative research efforts in various roles as Senior Director of Research for Gerstein Fisher Funds, Senior Researcher at Dimensional Fund Advisors and as a Portfolio Manager for the Scientific Active Equity team at BlackRock. His research has been published in various academic and practitioner financial journals including the Journal of Portfolio Management, Journal of Index Investing and Journal of Investment Management. Dr. Shah graduated summa cum laude with a BS in economics from the Wharton School and BAS in Systems Engineering from the University of Pennsylvania, an MSc in Finance and Economics from the London School of Economics, and an MA and PhD, both in Finance, from the University of Texas McCombs School of Business. He currently serves as an adjunct professor of Finance at the University of Texas McCombs School of Business.

Hersh Shefrin, Mario L. Belotti Professor of Finance, Leavey School of Business, SANTA CLARA UNIVERSITY 

Hersh Shefrin is the Mario L. Belotti Professor of Finance at Santa Clara University. He is one of the pioneers in the behavioral approach to economics and finance. Together with Richard Thaler, he developed an economic theory of self-control, which the Nobel committee emphasized in awarding the 2017 Economics Nobel to Thaler. The January 2001 issue of CFO magazine lists him among the academic stars of finance. A 2003 article in the American Economic Review listed him as one of the top fifteen economic theorists to have influenced empirical work. He is the author of seven books and numerous articles about how behavioral ideas impact real world decisions. In 2009, his book Beyond Greed and Fear was recognized by J.P. Morgan Chase as one of the top ten books published since 2000. He received his Ph.D. from the London School of Economics in 1974. He also holds an honorary doctorate from the University of Oulu, Finland. He is frequently interviewed by the press and his work was profiled by BBC-TV in February 2014. He writes a monthly blog post for Forbes, and has intermittently written for The Wall Street Journal and The Huffington Post. 

Mr. Sangha is Head of Risk in the Mobile Analytics division at State Street and leads a risk and investment strategy team for an artificial intelligence platform that integrates machine learning, natural language processing, portfolio and risk management, and human experiences to explore connections and extract relevant insights between market-moving events and multi-asset class portfolios.

Mr. Sangha is an accomplished global macro portfolio manager, strategist, and risk manager, with over 20 years’ experience. He has advised firms on developing quantamental approaches to trading --- strategies at the intersection of structural, statistical, and fundamental trading, utilizing data science, machine learning on both structured and unstructured data, and behavioral analytics.  Further, he has led several investment strategy and risk management teams and held a number of senior positions, including Chief Investment Strategist at a $6 billion global macro volatility hedge fund, and Senior Global Macro Trader at a $400 million hedge fund.

Mr. Sangha began his career at Goldman, Sachs & Co.,in the Global Investment Research Division.  He received honors at the International Mathematics Olympiad, served on the Canadian Mathematics Olympic Team, and is a Magna Cum Laude graduate of Brown University.

Michael Sotiropoulos, Managing Director, Global Markets, DEUTSCHE BANK

Michael Sotiropoulos is the global head of quant research for equities trading at Deutsche Bank. Prior to his current role, Michael was a Managing Director at Bank of America Merrill Lynch, where he headed the algorithmic trading quant group.

He has also worked for nine years in equity structured products and derivatives pricing at Bank of America and at Bear Stearns.
Michael has a Ph.D. in theoretical physics from Stony Brook University. Before joining the finance industry he taught and worked in quantum field theory and particle physics at the University of Southampton, England and at the University of Michigan.

Ben Steiner, Head of Quantitative Strategies, CIT GROUP

Ben Steiner is the Head of Quantitative Strategies at CIT Group. His experience covers quantitative modelling, portfolio management and business development for alternative investments. Now focusing on the less liquid asset class of private debt, his previous experience covered the more liquid strategies of Non-traditional Bond; Managed Futures; Global Macro & Equity Long/Short.

At CIT, Ben is now responsible for model development, research and analysis of credit and default risk. This includes probability of default, loss severity & stress testing (CCAR, DFAST). Ben joined CIT in 2015 and is based in New Jersey.

Before joining CIT, he was an Absolute Return Portfolio Manager and Senior Quantitative Researcher at FFTW (a subsidiary of BNP Paribas). Prior to that, he was with Aspect Capital as the Research Manager for financial engineering. Ben started his career at Deutsche Bank as a member of the quantitative research and portfolio construction team. He has 16 years of alternative investment experience.

Ben has a BA in Economics (with honors) from The University of Manchester and an MSc in Mathematical Finance from Imperial College London. He serves as a Director of the Society of Quantitative Analysts (SQA) - which celebrated its 50th anniversary last year - and sits on the Big Data Advisory Board at Rutgers.

Vasily Strela is a Managing Director and Global Head of FICC Quantitative Strategies at RBC Capital Markets. He and his group are responsible for development of risk neutral and statistical models and techniques for pricing and risk of all parts of Fixed Income and Commodities business.
Prior to joining RBC, Vasily was a Managing Director and Global Head of Market Modeling Group at Morgan Stanley. Vasily first joined Morgan Stanley in June 2001 and served in a variety of quant roles in Fixed Income Division. In 2007-2009 Vasily worked in FAST group at Bear Stearns and in interest rates QR group at JP Morgan. At Morgan Stanley Vasily was responsible for coordination of campus recruitment for Fixed Income Starts and Modeling group.

Vasily is affiliated with MIT Mathematics Department where he organized, developed and is co-teaching a class on Topics in Mathematics with Applications in Finance

Vasily holds a Ph.D. degree in Mathematics from MIT and an M.S. degree in Applied Mathematics and Physics from Moscow Institute of Physics and Technology.

Pietro Toscano, PhD, is Senior Risk Manager of OppenheimerFunds' Risk Management Group. In this capacity, he leads the investment risk management and fiduciary risk oversight for the Multi-Asset and Alternatives business. Dr. Toscano is the Founder and Chairman of the OppenheimerFunds Investment and Risk Institute.

Previously, he worked at BlackRock (legacy BGI), where he was Director and Lead Risk Manager for the America's Quantitative Fixed Income business (AUM ~ $37B, including the $7B flagship systematic Fixed Income Global Alpha hedge fund FIGA, and the Capital Structure Investment hedge fund CSI) as well as for the America's Fixed Income ETF and Index Investments business (AUM ~ $500B). At BlackRock, he served as a member of the BlackRock Applied Research Award Committee - a selected group of 20 top quants across the firm - and as the Global Head of Talent Management for the Risk Beta Strategies team. His expertise includes knowledge of the BlackRock's proprietary pricing and risk analytics, and risk methodologies across asset classes.

Dr. Toscano earned a BS in Electrical Engineering and a PhD in Information Engineering from University of Pisa, Italy, as well as a Master's in Financial Engineering from University of California, Berkeley. He published white papers on portfolio construction, risk methodologies, and derivatives pricing techniques in the Journal of Derivatives, in the International Journal of Theoretical and Applied Finance, and in the European Journal of Operational Research. Dr. Toscano is a Financial Risk Manager, Certified by the Global Association of Risk Professionals.

Leon Xin is the Head of Risk and Portfolio Construction and Hedge Fund Strategist for the CIO team of the Endowments and Foundations Group at JP Morgan. Mr. Xin conducts risk analysis and quantitative research to construct portfolios and improve portfolio efficiency. He is also responsible for research and selection of hedge fund managers. Mr. Xin joined J.P. Morgan in 2016 and has 11 years of investment industry experience.

Prior to J.P. Morgan, Mr. Xin worked for over 10 years as the Head of Alternative Investment Risk team at UBS Asset Management, where he covered UBS O'Connor, an internal multi-strategy hedge fund. As the Head of Risk team, Mr. Xin was responsible for risk analysis and quantitative research on multi-strategy hedge fund investing in equity, credit, risk arb, convertible arb, macro and volatility strategies. Prior to UBS, Mr. Xin worked as an associate in Ping An Insurance of China for two years on strategic planning projects.

Mr. Xin receives a M.S. degree on Applied Math from the University of Illinois at Chicago and is a CFA charter holder.