Miquel Noguer Alonso:
Co – Founder and Chief Science Officer, Artificial Intelligence Finance Institute – AIFI
Miquel Noguer Alonso: Co – Founder and Chief Science Officer, Artificial Intelligence Finance Institute – AIFI
Miquel Noguer is a financial markets practitioner with more than 20 years of experience in asset management, he is currently Head of Development at Global AI ( Big Data Artificial Intelligence in Finance company ) and Head on Innovation and Technology at IEF.
He worked for UBS AG (Switzerland) as Executive Director.for the last 10 years. He worked as a Chief Investment Office and CIO for Andbank from 2000 to 2006.
He is professor of Big Data in Finace at ESADE and Adjunct Professor at Columbia University teaching Asset Allocation, Big Data in Finance and Fintech. He received an MBA and a Degree in business administration and economics in ESADE in 1993. In 2010 he earned a PhD in quantitative finance with a Summa Cum Laude distinction (UNED – Madrid Spain).
Prof. Marcos López de Prado:
Global Head – Quantitative Research & Development, ABU DHABI INVESTMENT AUTHORITY (ADIA)
Prof. Marcos López de Prado: Global Head – Quantitative Research & Development, ABU DHABI INVESTMENT AUTHORITY (ADIA)
Prof. Marcos López de Prado is the Global Head – Quantitative Research & Development, ABU DHABI INVESTMENT AUTHORITY (ADIA), and professor of practice at Cornell University’s School of Engineering. He has over 20 years of experience developing investment strategies with the help of machine learning algorithms and supercomputers. He launched TPT after he sold some of his patents to AQR Capital Management, where he was a principal and AQR’s first head of machine learning. Marcos also founded and led Guggenheim Partners’ Quantitative Investment Strategies business, where he managed up to $13 billion in assets, and delivered an audited risk-adjusted return (information ratio) of 2.3.
William J. Kelly:
CEO, CAIA Association
William J. Kelly: CEO, CAIA Association
William (Bill) J. Kelly is the CEO of the CAIA Association. Bill has been a frequent industry speaker, writer, and commentator on alternative investment topics around the world since taking the leadership role at the CAIA Association in January, 2014. Previously, Bill was the CEO of Boston Partners and one of seven founding partners of the predecessor firm, Boston Partners Asset Management which, prior to a majority interest being sold to Robeco Group in Rotterdam in 2002, was an employee-owned
Founder, CIO, Ritter Alpha, LP
Gordon Ritter: Founder, CIO, Ritter Alpha, LP
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.
Prior to Harvard he earned his Bachelor’s degree with honours in Mathematics from the University of Chicago. 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. GSA Capital has won the Equity Market Neutral & Quantitative Strategies category at the Eurohedge awards four times, with numerous other awards including in the long-term performance category.
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 pro_t 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, continuous-time finance, and market microstructure in the Department of Statistics at Rutgers University, and also in the MFE programs at Baruch College (CUNY) and New York University (both ranked in the top 5 MFE programs).
He has published several articles on modern portfolio theory in top practitioner journals including Risk, and academic journals including European Journal of Operational Research.
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.
Clinical Full Professor and Director, Courant Institute of Mathematical Sciences, NYU
Petter Kolm: Clinical Full Professor and Director of the M.S. in Mathematics in Finance Program, Courant Institute of Mathematical Sciences, New York University & Partner, CorePoint-Partners.com
Petter Kolm is Clinical Full Professor and Director of the M.S. in Mathematics in Finance Program at the Courant Institute of Mathematical Sciences, New York University, since 2007. He is also Partner at CorePoint-Partners.com. Previously, Petter worked in the Quantitative Strategies group at Goldman Sachs Asset Management, developing proprietary investment strategies, portfolio and risk analytics in equities, fixed income and commodities.
Petter is the co-author of numerous academic journal articles and several well-known finance books including, 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).
Petter is a frequent speaker, panelist and moderator at academic and industry conferences and events. He is a member of the editorial boards of the International Journal of Portfolio Analysis and Management (IJPAM), Journal of Financial Data Science (JFDS), Journal of Investment Strategies (JoIS), and Journal of Portfolio Management (JPM). Petter is an Advisory Board Member of Alternative Data Group (ADG), AISignals and Operations in Trading (Aisot), Betterment (one of the largest robo-advisors) and Volatility and Risk Institute at NYU Stern. He is also on the Board of Directors of the International Association for Quantitative Finance (IAQF) and Scientific Advisory Board Member of the Artificial Intelligence Finance Institute (AIFI).
As an advisory board member, consultant, and expert witness, Petter has provided services in areas including alternative data, data science, econometrics, forecasting models, high frequency trading, machine learning, portfolio optimization with transaction costs, quantitative and systematic trading, risk management, robo-advisory, smart beta strategies, trading strategies, transaction costs, and tax-aware investing.
He holds a Ph.D. in Mathematics from Yale University; an M.Phil. in Applied Mathematics from the Royal Institute of Technology, Stockholm, Sweden; and an M.S. in Mathematics from ETH Zurich, Switzerland
Associate Professor, Cold Spring Harbor Laboratory
Mickey Atwal: Associate Professor, Cold Spring Harbor Laboratory
Mickey Atwal is an associate professor at Cold Spring Harbor Laboratory where he
undertakes machine learning research and builds tools to analyze vast datasets in
cancer genomics and immunology. He was awarded the Winship Herr Award for
Excellence in Teaching a record three times, developing courses at the interface of
machine learning, molecular biology, and neuroscience. He has trained in theoretical
physics from the University of Cambridge, Cornell University, and Princeton University
Professor, MIT Computer Science and Artificial Intelligence Laboratory
Larry Rudolph: Professor, MIT Computer Science and Artificial Intelligence Laboratory
Larry Rudolph is a researcher at the MIT Computer Science and Artificial Intelligence
Laboratory. Larry received his PhD also in Computer Science in 1981 from the Courant
Institute at NYU. He was on the faculty at University of Toronto, Carnegie-Mellon
University, and The Hebrew University, before joining MIT as a principal research
scientist, in 1995.
Way back in 1978, he helped start the Ultracomputer, a high performance parallel
computer architecture, many ideas of which can be found in current multi-core
computer chips. VP (Member of Labs) at Two Sigma Investments