EXPERTS SEARCH

Arnaud de Servigny is the CEO and founder of Queensfield AI Technologies (QFAI), a firm which creates market-neutral strategies for one of the 3 largest global Multi-Strat Hedge Funds. In addition, QFAI creates long-only strategies looking to outperform passive benchmarks. With more than 10 years of experience in the AI space, he is a pioneer in this field of AI applied to money-management.

Until 2015, Arnaud was the global Head of the Multi-Asset Group (MAG) and Wealth Management Chief Investment Officer (CIO) at Deutsche Asset & Wealth Management. He chaired the MAG's Global Investment Committee (GIC) which supports Deutsche Asset and Wealth Management's dynamic asset allocation process. Arnaud has been central to the development of this process, incorporating cutting-edge developments in asset allocation and giving research and strategy a cornerstone role. MAG manages 125 billion euros of assets globally.

Until mid-2010, Arnaud was a Managing Director at Barclays Wealth, where he was in charge of Economic and Behavioural Research, Investment Strategy and Asset Allocation. He also chaired the bank's investment committee.

From 2001 to 2006 Arnaud was the Global Head of Quantitative Analytics at Standard and Poor's. He was responsible for developing and implementing advanced technology within the firm's Credit Market Services department. This was centred around the creation of portfolio solutions, early warning indicators and stress testing tools.

Prior to joining Standard and Poor's, Arnaud worked in the Group Risk Management Department of BNP-Paribas, focusing on credit risk-related portfolio management and control.

Arnaud is also an Adjunct Professor of Finance at Imperial College Business School in London, where he co-launched their Master of Financial Engineering and Risk Management programme in 2005.

Arnaud holds a PhD in Financial Economics from the Sorbonne University, an MSc in quantitative finance (DEA) from Dauphine University, and a Civil Engineering MSc from the Ecole Nationale des Ponts & Chaussees in Paris.

Publications include many papers and articles as well as five books: the first on monetary policy and fixed income, the second and third on credit risk management, the fourth on structuring and the last on asset management.

Arnaud has received three awards for his work.

Hi, I’m Prashant Garg, an economist working on science, innovation, production, and media using machine learning, causal inference, and network science. 

I am a Research Associate at University of Cambridge and an Associate Fellow at INET Oxford. I recently completed my PhD in Economics at Imperial College London. I will join Bocconi University as a Postdoctoral Researcher in September 2026.

Personal Webpage: https://www.prashantgarg.org/

Sofia Gueorgieva is a Visiting Lecturer in Finance at the Imperial College Business School. Sofia has taught Corporate Finance, Advanced Corporate Finance, Banking, Mergers and Acquisitions and other financial courses for various programmes such as MSc Risk Management and Financial Engineering, MSc Finance, MSc Finance and Accounting, MSc Management. Previously, Sofia taught Corporate Finance at Baruch College, City Univeristy of New York.


Sofia holds a BA degree in Applied Economics from the American University in Bulgaria (AUBG), as well as MSc and PhD in Management witih concentration in Finance from INSEAD, France.

Her research focuses on the evolving dynamics of digital platforms and the creator economy. She combines machine learning and causal inference with large-scale data from major user-generated content platforms to uncover patterns in the digital world, with a focus to advance equity and transparency in digital ecosystems and help emerging creators to grow.

Sila Ordu is a doctoral student in Finance, currently completing her MRes. Previously, she was a pre-doctoral teaching and research assistant in Finance at Imperial.

Sila holds a BSc in Management Engineering from Istanbul Technical University and an MSc in Data Science and Economics from University College London.