Dr. Paul A. Bilokon

Dr. Paul A. Bilokon

CEO and Founder of Thalesians Ltd. Previously served as Director and Head of global credit and core e-trading quants at Deutsche Bank, the teams that he helped set up with Jason Batt and Martin Zinkin. Having also worked at Morgan Stanley, Lehman Brothers, and Nomura, Paul pioneered electronic trading in credit with Rob Smith and William Osborn.

Paul has graduated from Christ Church, University of Oxford, with a distinction and Best Overall Performance prize. He has also graduated twice from Imperial College London.

Paul’s lectures at Imperial College London in machine learning for MSc students in mathematics and finance and his course consistently achieve top rankings among the students.

Paul has made contributions to mathematical logic, domain theory, and stochastic filtering theory, and, with Abbas Edalat, has published a prestigious LICS paper. Paul’s books are being published by Wiley and Springer.

Dr. Bilokon is a Member of British Computer Society, Institution of Engineering and Technology, and European Complex Systems Society.

Paul is a frequent speaker at premier conferences such as Global Derivatives/QuantMinds, WBS QuanTech, AI, and Quantitative Finance conferences, alphascope, LICS, and Domains.

Prof. Matthew Dixon

Assistant Professor in the Applied Math Department at the Illionois Institute of Technology. His research in computational methods for finance is funded by Intel.

Matthew began his career in structured credit trading at Lehman Brothers in London before pursuing academics and consulting for financial institutions in quantitative trading and risk modelling.

He holds a PhD in Applied Mathematics from Imperial College (2007) and has held postdoctoral and visiting professor appointments at Stanford University and UC Davis respectively.

He has published over 20 peer reviewed publications on machine learning and financial modelling, and has been cited in Bloomberg Markets and the Financial Times as an AI in fintech expert.

Together we can achieve incredible things. Like, for example, having a much more transparent financial system, the cornerstone of a healthy, functioning democracy. It’s all about sharing ideas in the spirit of innovation, the spirit of helping others.

Prof. Matthew Dixon, Deepmind and the Future of the Finance Industry, TEDx talk

Dr. Brian Healy

Prof. Brian Healy

Brian has a PhD in Quantitative Finance and is an Adjunct Professor in Financial and Risk Engineering at New York University as well as being an Adjunct Professor of Mathematical Finance at Imperial College London.

He is an expert in solving complex problems using advanced mathematics and technology with a particular passion for the identification, analysis, pricing and management of risk.

He has held credit risk modelling positions for banks and asset managers, been Chief Scientific Officer for a number of enterprises with a focus on machine learning and artificial intelligence and was a mathematical modelling and exotic options trader for a number of tier 1 banks.

Alexandra Mostovoy

Alexandra Mostovoy

Alex recently graduated from the University of Edinburgh, where she studied Astrophysics. Since then, she’s worked for a Scottish tech start-up, imparted a wealth of mathematical knowledge and technique onto young minds by way of tutoring, and is currently a Data Scientist for Thalesians.

Alex speaks six languages (human) to varying degrees of fluency, and is gaining proficiency in communicating with machines in Java. She thrives on solving mathematical problems and delights in using vector calculus and matrix algebra.

Dr. Jan Novotny

Dr. Jan Novotny

A front office quant in the eFX markets working on predictive analytics and alpha signals.

Jan has built up a quantitative offering at HSBC. Prior to joining HSBC, he was working in the Centre for Econometric Analysis on the high-frequency time series econometric models and was visiting lecturer at Cass Business Group, Warwick Business School and Politecnico di Milano.

He co-authored a number of papers in peer-reviewed journals in Finance and Physics, contributed to several books, and presented at numerous conferences and workshops all over the world. During his PhD studies, he co-founded Quantum Finance CZ.

Ed Silantyev

Ed Silantyev

Hands-on data scientist with a wealth of expertise in machine learning libraries, such as Keras and TensorFlow.

Ed has also been a cryptocurrency trader for the last three years. During this time, he has developed a software system that trades cryptocurrencies on several exchanges algorithmically.

Ed’s interests in quantitative modelling include alpha generation in cryptocurrencies.

He is also an accomplished developer and system architect in Java and Python, and holds advanced certifications from Oracle.

Ed has presented his work at top industry conferences, including WBS QuanTech and at Thalesian seminars.

Dr. Nick Firoozye

Dr. Nick Firoozye

Dr. Nick Firoozye is a mathematician and statistician with over 20 years of experience in the finance industry, in both buy and sell-side firms, largely in  research.

Dr. Firoozye started his career in Lehman Brothers doing MBS/ABS modelling, heading teams in portfolio strategy and EM quant research, later taking a variety of senior roles at Goldman Sachs, and Deutsche Bank, as well as at the asset managers, Sanford Bernstein, and Citadel, in areas ranging from quantitative strategy, relative value strategy and trading, to fixed income asset allocation.

He was an MD and Head of Global Derivative Strategy, part of the Quantitative Investment Strategy Group, at Nomura from 2009-2017 and more recently Head of Quantitative Strategy at Symmetry Investments. He is currently an Honorary Senior Lecturer in Computer Science at University College London, focusing on Robust Machine Learning in finance.

Dr. Nick Firoozye co-authored a book, entitled Managing Uncertainty, Mitigating Risk, about the role of uncertainty and imprecise probability in finance, in light of the many recent financial crises, and he is writing a book on Algorithmic Trading Strategies based on his PhD and MSc courses on the same topic offered at UCL.