š Education
Dr. S. Mostafa Mostafavi holds dual PhDs, one in the Application of Machine Learning in Finance from Imperial College London, where his research involved applying Support Vector Machines, LSTMs, and other deep learning models in Python and R to analyze financial market indices and cryptocurrencies. He also earned a PhD in Electronic Engineering from the University of Surrey, focusing on Delay Minimization in Network Coding, where he developed theoretical optimization frameworks validated through MATLAB simulations. Additionally, he holds an MSc in Mathematics and Finance from Imperial College London, specializing in option pricing models and numerical methods in C++, and an MSc in Telecommunications from Kingās College London. His foundational degree is a BEng in Electrical Engineering (Communication) from the Sharif University of Technology, awarded with First Class Honours.
š©āš« Teaching Experience
Dr. Mostafavi has over a decade of experience across major global financial institutions, consulting firms, and fintech ventures. Currently, he works as a Quantitative Consultant at Grant Thornton UK, providing independent advisory on AI, model risk, and quantitative analytics. He also leads SMM Trading Services, where he offers consultancy services in blockchain, machine learning, and quantitative finance to financial institutions. Previously, he served as Senior Quantitative Lead at Evalueserve, where he led model development for ALM, credit risk, market risk, and FRTB, while also providing training and client engagement across Europe.
š°ļø Research Focus
Dr. Mostafaviās research spans both finance and engineering, with recent focus on the application of machine learning in financial markets, particularly cryptocurrencies and emerging market indices. He has published in leading journals, including Computational Economics and Machine Learning with Applications, on hybrid SVR-LSTM models and market prediction using technical indicators. His engineering research includes works on network coding and wireless sensor networks, published in IET Communications and IEEE Letters. He has presented his work at prestigious conferences such as Quant Summit, WatersTechnology, and Liquidity Risk Europe, discussing FRTB, blockchain, and AI applications in finance.
š ļø Skills
Dr. Mostafavi is proficient in a broad array of programming languages and technologies, including Python (Keras, TensorFlow, Pandas, Scikit-Learn), R, C++, Matlab, SAS, SQL, VBA, Scala, and Docker. He is experienced with data analytics tools like Bloomberg, AWS, Azure, Spark, Kubeflow, and Databricks, and has a strong command of GitHub, LaTeX, and containerization technologies. His financial domain expertise spans credit, FX, interest rate and equity derivatives, market and model risk, FRTB, LIBOR transition, IFRS 9, PPNR, CCAR, and stress testing, with practical application of quantitative models in pricing, risk analytics, and capital optimization.
š Awards and Honors
Dr. S. Mostafa Mostafavi has consistently demonstrated academic excellence and professional distinction throughout his career. He was awarded First Class Honours in his BEng in Electrical Engineering (Communication) from Sharif University of Technology, one of the most prestigious engineering schools in Iran. During his postgraduate studies, he earned competitive admission into multiple PhD programs in the UK, including Imperial College London and the University of Surrey, where he was affiliated with the renowned Centre for Communication Systems Research (CCSR), a 5A*-ranked research center.