Alexander Shklyarevsky

Alexander Shklyarevsky is a Director, Model Risk Management, in Enterprise Risk Management at State Street in New York. He specializes in quantitative pricing and risk models and other methodologies and processes for Capital, Collateral, Insurance Products, Derivative Products and their portfolios across asset classes. Prior to joining State Street, Alexander worked at AIG, Bank of America Merrill Lynch, Commerzbank, ING, Deutsche Bank where he specialized in quantitative pricing, trading and risk models for derivative securities and their portfolios, as well as Risk Management and Risk Analytics. Mr. Shklyarevsky has been published in financial magazines and has been a speaker at multiple industry and academic conferences. Prior to working in an Insurance Industry and a Financial Industry, he worked in Construction Research, Market Research and Academia where he conducted Mathematical Research and taught courses in Mathematics. Mr. Shklyarevsky holds a B.S. / M.S. Degree in Mathematics from Kiev State University (Department of Mathematics) and M.S. Degree with all PhD credits in Mathematics from New York University (Courant Institute of Mathematical Sciences, Department of Mathematics). He has 7 years of experience teaching Financial Mathematics courses at New York University and Rutgers University.

Andrei Golubentsev

For over 15 years, Dr. Goloubentsev has been working as desk quant and risk management quant at such leading financial institutions as Citigroup, Bank of America, CME Group, Credit Suisse, Bank of Montreal, Wachovia Securities, and CIBC, developing models to price, hedge, and risk manage various exotic derivatives. He is an expert in markets in various asset classes, particularly in interest rates, currencies and commodities. Currently, he is working on application of machine learning concepts to algorithmic trading. Andrei is a published author and has presented in numerous industry conferences.

Andrei has received his PhD in Physics and Mathematics from Moscow Institute of Physics and Technology. Upon completion of his postdoctoral studies in condensed matter physics at the University of Toronto, Canada, Andrei has become interested and gotten actively involved in all aspects of mathematical finance.

Alexander Leytman

Dr. Leytman has more than 30 years of experience leading technology and international commodity trade projects with annual budgets topping $25 million. He has successfully delivered projects and programs in finance, risk, regulatory compliance, and management consulting domains for such companies as Ernst & Young, Lehman Brothers, Nomura Securities, Citigroup, TD Bank, DTCC, and TIAA.

Furthermore, for the past 10 years Alex has been continuously teaching project management curriculum throughout North American academic institutions. He has earned his BA in Comparative Literature from New York University, MBA from Regis University, and Doctorate in Management Information Systems from University of Maryland University College.

Yves J. Hilpisch

Dr. Yves J. Hilpisch is founder and managing partner of The Python Quants (, a group focusing on the use of open source technologies for financial data science, artificial intelligence, algorithmic trading, and computational finance. He is also founder and CEO of The AI Machine (, a company focused on harnessing the power of artificial intelligence for algorithmic trading via a proprietary strategy execution platform. Yves has a Diploma in Business Administration (with honors) as well as a Ph.D. in mathematical finance (magna cum laude).

He is the author of four books:

  • Artificial Intelligence in Finance (O'Reilly, forthcoming)

  • Python for Finance (2nd ed., O'Reilly, 2018)

  • Listed Volatility and Variance Derivatives (Wiley, 2017)

  • Derivatives Analytics with Python (Wiley, 2015)

Yves is the director of the first online training program leading to a University Certificate in Python for Algorithmic Trading ( or for Computational Finance ( He also lectures on computational finance, machine learning and algorithmic trading at the CQF Program (

Yves wrote the financial analytics library DX Analytics ( and organizes meetups, conferences, and bootcamps about Python for quantitative finance and algorithmic trading in London (, Frankfurt, Berlin, Paris, and New York. He has given keynote speeches at technology conferences in the United States, Europe, and Asia.

Ed Hayes

Ed Hayes has worked in the financial services industry for over 20 years and in a variety of roles. He worked as a front office quant for AIG in FX options and energy principal investing before becoming senior risk analyst at RBS Sempra Commodities. He moved into management as Head of Market Risk at Société Générale Energy and Group Head of Quant Risk with the Noble Group. He recently worked at Citadel Investments as a quantitative developer in energy before moving to his current role at Natixis Bank as quantitative developer in the Latin American rates business. Before coming to finance, he taught Mathematics in both high school and college, and he has been teaching financial risk management at the UConn School of Business since 2014.

Ed holds an AB in Political Science from Columbia College of Columbia University and a PhD in Mathematics from the Courant Institute of Mathematical Sciences of New York University.

Fima Klebaner

Fima Klebaner is a Professor in Stochastic Processes, with over 30 years of experience in teaching and research in Stochastic Calculus and Financial mathematics. He has published “Introduction to Stochastic Calculus with Applications”, as well as over 90 research papers, with many important contributions in Financial Mathematics including stochastic volatility. He has also run professional courses for quants in banks and Treasury. Majority of his PhD’s are successful quants. In 2003 he was elected Fellow of the Institute of Mathematical Statistics.

Paul Bilokon

Dr Paul A. Bilokon is CEO and founder of Thalesians Ltd and an expert in algorithmic trading. He previously worked at Deutsche Bank, Citigroup, Nomura, Lehman Brothers, and Morgan Stanley. Paul graduated from Christ Church College, Oxford, with a distinction and best overall performance prize and twice from Imperial College. He has co-authored several books, including Machine Learning and Big Data with kdb+/q (with Jan Novotny, Aris Galiotos, and Frederic Deleze, published by Wiley) and Machine Learning in Finance: From Theory to Practice (with Matthew Dixon and Igor Halperin, published by Springer).

Pavel Chigansky

Dr. Chigansky is Associate Professor with the Department of Statistics and Data Science at the Hebrew University of Jerusalem. Broadly his research and teaching interests are in probability and stochastic processes. He published contributions to nonlinear filtering and stochastic control, dynamical systems with random perturbations and asymptotic statistics of random processes. Previously he held a position of research engineer with the Space Division of Israel Aircraft Industries.

Pavel holds Ph.D degree in Electrical Engineering from Tel Aviv University.

Irina Ursachi

Irina Ursachi is an independent Risk Management consultant. She has over eight years of experience in the banking industry, managing international projects in various European jurisdictions such as the UK, France, and Germany. Her expertise covers the design and specification of business processes as well as the implementation of regulatory requirements, trading systems, valuation models and valuation adjustments. Mrs. Ursachi is an active contributor to research projects and publications in the area of Risk Management. Prior to becoming an independent consultant, she has worked for the consulting companies d-fine and KPMG. She holds a Master’s degree in Mathematics from the University of Kaiserslautern.

Dr. Michael Coulon

Dr. Coulon is a quantitative risk consultant and an honorary Senior Lecturer in Finance at the University of Sussex Business School, with over 15 years of experience in quantitative finance, stochastic modelling and commodity markets. Michael’s academic background is in mathematics and finance with degrees from Imperial College London (BSc), Princeton University (MFin) and the University of Oxford (DPhil), complemented by industry experience at leading investment banks. He frequently collaborates with energy companies to apply mathematical techniques to practical risk management and valuation problems. He has developed many commodity price models and derivative pricing techniques, especially for electricity and environmental markets, often presents at leading conferences in this field, and has published in top international journals.

Anna Holten Møller

Anna Holten Møller is a senior risk analyst with 14 years experience from the financial sector within Sales, IT, Markets, Risk controlling and modelling. During the past 5 years Anna has worked on regulatory projects within market and counterparty credit risk covering both IT implementation, business impacts and mitigation aspects. Anna is currently leading Nykredit’s implementation of the Standardised Approach for Counterparty Credit Risk. Before joining Nykredit Anna worked with Nordea where she was leading the implantation of FRTB Standardised Approach. She is a recurring speaker at Risk Trainings FRTB courses.

Anna holds a MSc in Business Administration and Management Science (Mathematical Finance) from Copenhagen Business School.

Mikhail Soloveitchik, Dr. Habil

Dr. Mikhail Soloveitchik has about 20 years of experience in financial industry in Europe with 12 years as head of front office credit quantitative analytics at HSBC in London. He was also working in technology sector in Germany, including 2 years at IBM consultancy and spent 8 years as assistant professor of applied mathematics at university of Heidelberg. He has published several re- search papers in probability theory and mathematical physics.

He has PhD degree in mathematics from Moscow State University (supervised by Ya.G. Sinai) and Habilitation degree in applied mathematics from the university of Heidelberg in Germany.