Paul Bilokon: CEO, Thalesians, Visiting Professor, Imperial College

Dr. Paul Bilokon is CEO and Founder of Thalesians Ltd and an expert in electronic and algorithmic trading across multiple asset classes, having helped build such businesses at Deutsche Bank and Citigroup. Before focussing on electronic trading, Paul worked on derivatives and has served in quantitative roles at Nomura, Lehman Brothers, and Morgan Stanley. Paul has been educated at Christ Church College, Oxford, and Imperial College. Apart from mathematical and computational finance, his academic interests include machine learning and mathematical logic.

Ivan Zhdankin: Associate, Quantitative Analyst, JP Morgan Chase & Co

Ivan Zhdankin is a quantitative researcher with experience in diverse areas of quantitative finance, including risk modelling, XVA, and electronic trading across asset classes, including commodity futures and G10 and emerging market currencies. Ivan was consulting various banks in quantitative modeling and has recently joined JP Morgan as a quantitative analyst. He has become one of the first researchers to generate convincing results in electronic alpha with neural nets. He has a solid mathematical background from New Economic School and Moscow State University, where he studied under the celebrated Albert Shiryaev, one of the developers of modern probability theory.

Francesca Lazzeri: Principal Manager, Cloud & AI & Machine Learning, Microsoft

Francesca Lazzeri is a machine learning scientist on the cloud advocacy team at Microsoft. An expert in big data technology innovations and the applications of machine learning-based solutions to real-world problems, she has worked with these issues in a wide range of industries, including energy, oil and gas, retail, aerospace, healthcare, and professional services. Previously, she was a research fellow in business economics at Harvard Business School, where she performed statistical and econometric analysis within the Technology and Operations Management Unit and worked on multiple patent data-driven projects to investigate and measure the impact of external knowledge networks on companies’ competitiveness and innovation. Francesca periodically teaches applied analytics and machine learning classes at universities in USA and Europe. and is a mentor for PhD and postdoc students at the Massachusetts Institute of Technology. She enjoys speaking at academic and industry conferences to share her knowledge and passion for AI, machine learning, and coding. Francesca holds a PhD in innovation management.

Alexander Sokol: Executive Chairman and Head of Quant Research, CompatibL

Alexander Sokol is the founder, Executive Chairman, and Head of Quant Research at CompatibL, a trading and risk technology company. He is also the co-founder of Numerix, where he served as CTO from 1996 to 2003, and the co-founder of Duality Group, where he served as CTO from 2017 to 2020.

Alexander won the Quant of the Year Award in 2018 together with Leif Andersen and Michael Pykhtin, for their joint work revealing the true scale of the settlement gap risk that remains even in the presence of initial margin. Alexander’s other notable research contributions include systemic wrong-way risk (with Michael Pykhtin, Risk Magazine), joint measure models, and the local price of risk (with John Hull and Alan White, Risk Magazine), and mean reversion skew (Risk Books, 2014).

Alexander earned his BA from the Moscow Institute of Physics and Technology at the age of 18, and a PhD from the L. D. Landau Institute for Theoretical Physics at the age of 22. He was the winner of the USSR Academy of Sciences Medal for Best Student Research of the Year in 1988.

Dr Antoine Jacquier: Reader in the Department of Mathematics at Imperial College London

His research interests are in Probability and Mathematical Finance. He is particularly interested in large deviations methods and asymptotic expansions for stochastic processes, and their applications to volatility modelling.

He also works on applications of Deep Learning and Quantum Computing in Mathematical Finance.

His personal webpage can be found at www2.imperial.ac.uk/~ajacquie/

Blanka Horvath: Associate Professor in Mathematical and Computational Finance, University of Oxford and Researcher, The Alan Turing Institute

Blanka research interests are in the area of Stochastic Analysis and Mathematical Finance.

Including asymptotic and numerical methods for option pricing, smile asymptotics for local- and stochastic volatility models (the SABR model and fractional volatility models in particular), Laplace methods on Wiener space and heat kernel expansions.

Blanka completed her PhD in Financial Mathematics at ETHZürich with Josef Teichmann and Johannes Muhle-Karbe. She holds a Diploma in Mathematics from the University of Bonn and an MSc in Economics from the University of Hong Kong.

Achintya Gopal: Machine Learning Quant Researcher, Bloomberg

Achintya Gopal is a Machine Learning Quant Researcher in the Quantitative Research group in the Office of the CTO at Bloomberg, where he works on applying machine learning within the financial domain. Prior to that, he worked on estimating carbon emissions using machine learning, developing new models in normalizing flows, and exploring new methods to evaluate statistical models with model uncertainty. More recently, he has been working on a variety of projects ranging from volatility modeling using neural networks, causal inference for investing, generative models in differential privacy, active learning for NLP, and the interpretability of large language models.

Peter leads the Institute of Wealth & Asset Management (IWA) at Zurich University of Applied Sciences (ZHAW). He is a member of the organizing committees of the Swiss CFA Pension Fund conference, the Networking Event Series – Sustainable Finance Technology powered by Innosuisse and the COST Conference on Artificial Intelligence in Industry and Finance.
The IWA is running the BRIDGE Discovery project “Spatial sustainable finance: Satellite-based ratings of company footprints in biodiversity and water” together with the Institute of Natural Resource Sciences at ZHAW and the Department of Geography at UZH.

Toby Weston: Quantitative Analyst, NatWest Markets

Saeed Amen: Turnleaf Analytics / Cuemacro / Visiting Lecturer at QMUL

Helyette GEMAN is a Professor of Mathematical Finance at Birkbeck – University of London and at Johns Hopkins University. She is a Graduate of Ecole Normale Supérieure in Mathematics, holds a Masters degree in Theoretical Physics, a PhD in Probability from the University Pierre et Marie Curie and a PhD in Finance from the University Pantheon Sorbonne.

She has been a scientific advisor to a number of major energy and mining companies for the last 20 years, covering the trading of crude oil, natural gas, electricity as well as metals in companies such as EDF Trading, Louis Dreyfus or BHP Billiton and was named in 2004 in the Hall of Fame of Energy Risk.

Prof Geman was previously the head of Research and Development at Caisse des Depots. She has published more than 140 papers in major finance journals including the Journal of Finance, Mathematical Finance, Journal of Financial Economics, Journal of Banking and Finance and Journal of Business. She has also written the book entitled Insurance and Weather Derivatives and is a Member of Honor of the French Society of Actuaries.

Her research includes exotic option pricing for which she got the first prize of the Merrill Lynch awards, asset price modeling through the introduction of transaction time (JOF, 2000); she is one of the authors of the CGMY pure jump Levy model (2002). Prof Geman had organized in 2000 at College de France the first meeting of the Bachelier Finance Society, with Paul Samuelson, Robert Merton and Henry McKean as keynote speakers.

Her book, ‘Commodities and Commodity Derivatives’ is the reference in the field. She was a Scientific Expert on Agriculture for the European Commission and is on the Board of the Bloomberg Commodity Index.
She counts among her numerous PhD students Nassim Taleb, author of the Black Swan