Jet Zhou holds dual undergraduate degrees in business and financial mathematics from Wilfrid Laurier University, as well as a master’s degree in mathematics. After completing his master’s degree, Jet worked as a research analyst at the Financial Data Analytics Research Lab at the Fields Institute, where he contributed to the development of Canada’s Financial Wellness Lab.
Currently, Jet is a third-year PhD student at the Banking Analytics Lab lead by Dr. Cristián Bravo. His research focuses on assessing the financial consequences of social capital in the boardroom using machine learning with graphs and social network analysis. In addition to his academic pursuits, Jet is a certified Financial Risk Manager (FRM) and has passed all three levels of Chartered Financial Analyst (CFA) exam. Having broad financial knowledge allows him to approach problems from multiple angles and provides him with a comprehensive understanding of financial markets and instruments.
Jet is passionate about using his skills and knowledge to drive positive impact and innovation in the financial industry. He is excited to continue exploring new and exciting areas of machine learning research and developing these methods towards applications that can contribute to better financial outcomes.
Sanghyun is a first-year Ph.D. student in Banking Analytics Lab at Western University. He is supervised by Professor Cristián Bravo Román. He is also joining Canada’s Financial Wellness Lab at Western.
Before his Ph.D., Sanghyun completed an MSc in Statistics at Western University. Prior to this, he completed a MA in Economics and BA degree in Economics at Sogang University. During this period, he conducted research on econometric theory.
His research interests include machine/deep learning, causal inference, and their application to economic and financial data.
Sherly is a mathematician with a strong passion for utilizing machine learning methods to solve real-world problems in the banking and insurance industries. Sherly holds a Master’s degree in Sciences-Mathematics and a Master’s degree in Actuarial Sciences from Universidad Nacional de Colombia, where she conducted research in mathematical fields including Non-euclidean geometries and stochastic models in the FX market.
Currently, Sherly is a third-year PhD student, working under the guidance of esteemed Professors Cristián Bravo Román and Kristina Sendova. Her research interests lie in the application of machine learning techniques, such as reinforcement learning and causal inference, to address specific challenges in the banking and insurance sectors. Sherly is driven by a strong desire to develop objective methods that can facilitate more informed decision-making in these industries.
During her PhD studies at Wester University, She has also been actively engaged as a teacher assistant in various courses offered by the Statistical and Actuarial Sciences Department. This includes assisting in courses such as Introduction to Machine Learning, Data Analysis Consulting, and Life Contingencies III, where she has demonstrated her expertise and dedication to sharing her knowledge with students.
Mahsa Tavakoli is a second-year PhD student at the University of Western Ontario in the field of financial modeling. Her research interests lie in natural language processing, computer vision, multimodal models, transformers, and banking analytics.
With a Master’s degree in Mathematical Statistics, Mahsa is currently working under the guidance of Professor Cristián Bravo Román at the University of Western Ontario and Professor Rohitash Chandra at the UNSW.
Mahsa’s research focuses on designing and improving multimodal models. These deep learning models can handle and integrate data from multiple sources or modalities, such as text, images, audio, and video. Additionally, Mahsa has been actively engaged as a teaching assistant in various courses, including Data Science and Banking Analytics.
Sahab completed his undergraduate program in mechanical engineering at the University of Tehran. He also holds two master’s degrees in mechanical engineering and financial modelling, both from Western University. He is currently a third-year PhD student in the Department of Statistical and Actuarial Sciences at Western University, working under the supervision of Dr. Cristián Bravo Roman and Dr. María Óskarsdóttir. His research interests include machine learning, graph neural networks, and social network analysis with applications to financial analytics and credit risk modelling.
A holder of the Alexander Graham Bell Canada Graduate Scholarship-Doctoral (CGS D), he was a visiting student at the University of Southampton from April to May 2023. Since the beginning of his PhD, he has been actively engaged as a teaching assistant and/or lab coordinator in various courses such as Data Science Concepts and Introduction to Machine Learning.
Kamesh is a final-year PhD student at the University of Southampton, UK. His research focuses on developing innovative methods for risk management of firms under market complexity and illiquidity. His research interests are in applying deep learning for finance such credit risk management, portfolio optimisation and systemic risk.
Matt Stevenson is a final-year PhD candidate at the University of Southampton. His research centres on Deep Learning applications and decision support systems, specifically with the use of novel data types, including natural language, images, and multi-dimensional time-series data. Alongside his PhD, Matt also holds a Masters degree in Business Analytics & Management Science from the University of Southampton.
His doctoral research delves into the development of advanced analytics and AI to enhance the competitiveness and accessibility to funding for Small and Medium Enterprises (SMEs). These concepts form the basis of his forthcoming thesis.
Outside academia, Matt holds the role of Data Scientist at Ki, Lloyd’s of London’s first fully digital and algorithmically-driven syndicate. Here, his primary responsibility involves leveraging data science to improve the accuracy of the insurance underwriting process and optimise risk management strategies.
Daniel Abib is a postdoctoral fellow at the department of Statistics and Actuarial Sciences of the University of Western Ontario.
He is currently working in Spatial Econometrics, Networks and Machine Learning applied to Economics and Finance. His work is to be published in the Journal of Monetary Economics, and has been presented at the FED System, The Swiss National Bank, The NBER Summer Institute, The Study Center Gerzensee, The Central Bank of Brazil among others.
Previously, he obtained a PhD in Economics from the Fundação Getúlio Vargas (FGV) in Rio de Janeiro, working in Macroeconometrics applied to Big Data and worked as a researcher at the Brazilian Institute of Economics (IBRE-FGV).