Financial Engineer of the Year:

Bruno Dupire

And IAQF Innovation Award Recipient:

Antoine Savine

Award Dinner Information

Tuesday, May 19, 2026

The Yale Club

New York City

6:30pm Cocktails 7:30pm Dinner

Corporate sponsorships including tables of ten are available

Individual seats are available for $600

For more information please contact the

IAQF office at 646-736-0705 or info@iaqf.org

About the Winner: 

Bruno Dupire is head of Quantitative Research at Bloomberg L.P., which he joined in 2004. Prior to this assignment in New York, he has headed the Derivatives Research teams at Société Générale, Paribas Capital Markets and Nikko Financial Products where he was a Managing Director. He is best known for having pioneered the widely used Local Volatility model (simplest extension of the Black-Scholes-Merton model to fit all option prices) in 1993 and the Functional Itô Calculus (framework for path dependency) in 2009. After a Master's degree in Artificial Intelligence in 1982 and a PhD in Numerical Analysis in 1985 he has conducted in 1987-88 a study to apply Neural Nets to time series forecasting for Caisse des Dépôts et Consignations. 

At Bloomberg he has initiated the BQuant project, a quant platform that combines easy access to the data with the expressivity of Python. He runs the BBQ (Bloomberg Quant) seminar, the largest monthly quant seminar worldwide. He is a Fellow and Adjunct Professor at NYU and he is in the Risk magazine “Hall of Fame”. He is the recipient of the 2006 “Cutting edge research” award of Wilmott Magazine, of the Risk Magazine “Lifetime Achievement” award for 2008 and of the 2025 Financial Engineer of the Year Award of IAQF. 

About the Innovation Award Winner:

Antoine Savine is a Managing Director and the Global Head of Rates Quants at Barclays Investment Bank. In the previous years, he led Macro Analytics at Hudson River Trading. In the previous decades, he built the Fixed Income Quant group at BNP, and served as chief quantitative analyst at Danske Bank's Superfly Analytics and adjunct professor of mathematical finance at Copenhagen University. He wrote the book on adjoint differentiation (AAD) with Wiley (Modern Computational Finance, 2018), created differential machine learning with Brian Huge, and delivered multiple influential publications and conference talks. He holds a PhD in mathematical finance from Copenhagen University and a Masters (DEA) of mathematical finance from University of Paris, City.

Wednesday May 20th, 2026

6:30 PM Seminar Begins

8:00 PM Reception

Hybrid Event

Fordham University

McNally Amphitheater

140 West 62nd Street

New York, NY 10023

Free Registration!

For Virtual Attendees: Please select virtual instead of member type upon registration.

Abstract:

We derive the optimal long-term growth rate for an agent investing in a market composed of a numéraire asset, a risky asset subject to transaction costs, and a liquidity pool within an Automated Market Maker (AMM). We first establish the necessary conditions to ensure a no-arbitrage environment within this market structure. Under these conditions, we determine the asymptotically optimal trading strategy for liquidity providers. Finally, we provide economic intuition for the strategy’s sensitivity to various market parameters, supported by numerical illustrations of our theoretical results.

Bio:

Maxim Bichuch holds a M.S. from NYU and a Ph.D. from Carnegie Mellon University both in Financial Mathematics. He was a Postdoctoral Research Associate & Lecturer in the ORFE department in Princeton, and an Assistant Professor at Worcester Polytechnic Institute and Johns Hopkins University, before joining the department of Mathematics at The University at Buffalo. Prior to obtaining his Ph.D. He has also gained corporate experience working for Citigroup and Bear Stearns. His research interests include optimal investment, optimal control, stochastic volatility, credit, funding and counterparty risks, and most recently electricity markets, machine learning and AI, decentralized finance and fintech.

AI/ML in Finance: Advancing the Future of Financial Markets

Presented IAQF and LSE DSI

23rd June, 2026 | London

The International Association of Quantitative Finance (IAQF), in collaboration with the Data Science Institute at the London School of Economics (LSE DSI), is pleased to co-host this exclusive event. We invite you to an evening of compelling presentations and lively discussions exploring how artificial intelligence (AI) and machine learning (ML) are reshaping financial markets.

Sponsored by:

Event description

Artificial intelligence (AI) and machine learning (ML) are becoming foundational technologies for modern finance. They are reshaping how institutions generate insights from data, manage risk, execute transactions, and serve clients—while also influencing market structure and financial stability.

This event brings together academic and industry leaders for short talks and a panel discussion on how AI/ML is advancing the future of financial markets. The conversation will highlight practical applications, emerging capabilities, and the key challenges that will shape adoption over the next several years.

Open to academics, practitioners, students, and the public, the event provides a forum to learn, ask questions, and connect with a community working at the forefront of AI/ML and finance.

We look forward to welcoming you to an inspiring evening in London!

Why attend? 

• Engage with thought leaders and experts in AI/ML and finance.
• Network with industry practitioners, academics, and enthusiasts.
• Gain insights into emerging trends shaping the future of financial markets.

Confirmed speakers and panelists (alphabetically listed)

• Álvaro Cartea, Professor of Mathematical Finance and Director, Oxford-Man Institute of Quantitative Finance, University of Oxford (UK)
  
• Peter Hafez, Chief Data Scientist, RavenPack | BigData.com (Spain)
• James Hamp, Head of Data Strategy & Analytics for Foreign Exchange, Citi (UK)
• Petter Kolm, Professor, Courant Institute of Mathematical Sciences, New York University (USA)
• Luitgard Veraart, Professor, Department of Mathematics, LSE (UK)

Chair

Johannes Ruf, Professor, Department of Mathematics, and Deputy Director, Data Science Institute, LSE (UK)

Moderator

Hilary Till, Principal, Premia Research LLC (USA)

Registration

This is a free, in-person event, and registration is required. Walk-ins and onsite registration will not be possible. We request that attendees arrive on time to be assured of a seat.

Location

LSE Shaw Library

6^th Floor of the Old Building

London School of Economics and Political Science

Houghton Street

London WC2A 2AE

United Kingdom

Event program

• 17:45 Doors open
• 18:00 - 18:05 Welcome & introduction
• 18:05 - 19:20 Presentations and panel discussion
• 19:20 - 20:00 Reception

Map of the LSE Campus (Including the Old Building) available at this link.