Research Team
and Graduate Supervision

Working Group

Raeid, Saqur, Postdoctoral Researcher PDRA Datasig II, UKRI.

Wen Su,  PhD Student (2023-)  Sponsored by JP Morgan Chase
Internships: JP Morgan Chase

Jonathan Plenk, PhD Student ongoing (2023-)
Internships: Citadel

Adam Jones, PhD Student (2022-)  Sponsored by JP Morgan Chase
Internships: JP Morgan Chase

PhD Students Past and Present 

Wen Su,  PhD Thesis, ongoing (2023-)  Sponsored by JP Morgan Chase
Internships: JP Morgan Chase

Jonathan Plenk, PhD Thesis, ongoing (2023-)
Internships: Citadel

Adam Jones,  PhD Thesis, ongoing (2022-)  Sponsored by JP Morgan Chase
Internships: JP Morgan Chase

Yannick Limmer, PhD Thesis, Oxford University (2022-2025)
Internships: DWR
First Job: DWR

Andrew Alden, PhD Thesis, jointly with Prof. Carmine Ventre, King's College London (2021-) & Oxford Man Institute (2022-2025)
Internships: Man  Group
First Job: Man  Group

Owen Futter, PhD Thesis, Sponsored by Atlantic House Group
King's College London (2021) and  jointly with Prof. Johannes Muhle-Karbe (2022-2025)
Internships: Atlantic House Group, Jump Trading
First Job: Jump Trading

Zacharia Issa , PhD Thesis, King's College London (2020-2023)
Internships: Quantitative Analyst at Kaiju, Bank of New York Mellon
First Job: Bank of New York Mellon, Citadel

Aitor Muguruza Gonzalez  ‘Developments on Rough Volatility’, PhD Thesis , jointly with Dr A. Jacquier,
Imperial College London (2016-2020)
First Job: Quantitative Analyst at Natixis
Now: Global Head of Quantitative Modelling at Kaiju.

Member of PhD Examination Committees for:

Felix PRENZEL: Statistcal Modelling and Simulation of Limit Order Markets.
Doctoral thesis at Oxford University partially completed at JP Morgan Chase, 2023.

Faycal DRISSI: Models of Market Liquidity, Applications to Traditional Markets and Automated Market Makers.
These de Doctorat, Universite' Paris 1 Pantheon-Sorbonne, 2023.

Bouazza SAADEDDINE: Learning From Simulated Data in Finance: XVAs, Risk Measures and Calibration.
Thèse de doctorat de l'université Paris-Saclay, 2022.

Michael ALLOUCHE:  Contributions to Generative Modeling and Dictionary Learning: Theory and Application.
These de doctorat de l’Institut Polytechnique de Paris, preparee a l’Ecole Polytechnique 2022.

Sheng WANG:  Neural-SDE market models
Doctoral thesis at Oxford University, 2022.

Mehdi TOMAS:
These de doctorat de l’Institut Polytechnique de Paris, preparee a l’Ecole Polytechnique 2022.

MSc Supervision:

Linda Mazinova: MSc Thesis 2023, Oxford University.

Jonathan Plenk: MSc Thesis 2023, Technical University of Munich.
First job: (before graduation) Visiting Researcher at Oxford Man Institute (OMI) and at the Oxford Mathematical Institute

Felix Fuchs: MSc Thesis 2023, Technical University of Munich.
First job:  (before graduation) Assenagon, First job after graduation: Munich Re.

Anton Hancaryk: Analysing the relation of expected signatures to laws of stochastic processes, (MSc Thesis), 2022, Technical University of Munich.

Cedric Huberty: Deep Hedging and Market Generation (MSc Thesis), 2022, Technical University of Munich.

Josip Bencic: The Signature Transform and Applications (MSc Thesis), 2022 , Technical University of Munich.
First job after graduation: Quantitative Analyst at Citadel, London.

Zan Zuric ‘Aspects of Portfolio optimisation in Rough Volatility models ’, MSc Thesis, ongoing, Jointly with Josef Teichmann,  2019, ETH Zürich  student exchange programme.
First job after graduation: PhD Studies at Imperial College London and ATI with Antoine Jacquier and Lukasz Szpruch.

Mehdi Tomas, ‘Pricing and Calibration of Stochastic Models via Neural Networks’, MSc Thesis, 2018, Imperial College London (placement at FX options at HSBC during thesis).
First job after graduation: PhD Studies at Ecole Polytechnnique Paris with Mathieu Rosenbaum  and Michael Benzaquen.

Laurids Gert Nielsen, ‘Machine Learning for Foreign Exchange Rate Forecasting’, MSc Thesis, 2018, Imperial College London (jointly with Thorsten Schoeneborn  at Deutsche Bank)
After graduation: Quantitative Analyst at Deutsche Bank.

Nelson Okou, ‘Fractional Brownian Motion an Machine Learning for Variance Prediction’, MSc Thesis, 2018, Imperial College London.

Anne-Marie Bausch ‘Optimal Option Pricing for the SABR Model’, MSc Thesis, Submitted March 2018, Jointly with Martin Larsson, ETH Zürich-Imperial College London (student exchange programme).

Full details about my activities in thesis supervision and advising and a selection of topics that I am interested in can be found here.

Throughout the year there is a large number of lectures and seminars in Mathematical Finance with the aim to mirror latest trends and developments both in academia and industry practice. These provide an opportunity to highlight a selection of important recent developments within the field. Below is a selection of seminars and lectures with my organisational involvement and a selection of my most recent teaching activities. A larger overview of seminars and events within the London Math Finance community can be found here. 

Teaching (2017-2023)

Seminar  (Lecturer, Technical University of Munich) Fall Term 2021.

Fixed Income Markets (Lecturer, Technical University of Munich) Fall Term 2021.

Machine Learning for Mathematical Finance (Lecturer, Technical University of Munich) Spring Term 2021.

Machine Learning for Mathematical Finance (Lecturer, King's College London) Spring Term 2020.

Mathematical Finance Continuous Time (Lecturer, King's College London) Spring term 2019 and 2020.

Introduction to Python and R (Instructor, Imperial College London) This is an introductory overview of basics in Python and R which will be prerequisites to a number of courses in the MSc in Mathematics and Finance. Course materials.

Statistical Methods for Finance M5MF38 (Lecturer,  Imperial College London)  This course concentrates on rough volatility models, their statistical properties, and their properties with respect to volatility forecasting, option pricing, and their microstructural foundations. This unit takes 12 hours of lecture time including exercise classes. Course Content. Useful links: Volatility with python for implementations.

Numerical Methods in Finance M5MF2 (Lecturer,  Imperial College London) Course contents: Finite difference methods for parabolic PDEs; Fourier transform and quadrature methods;  Numerical optimisation; Linear programming. Course materials.