The Fundamentals of Machine Learning in Finance

Dr Richard Saldanha is Founder and Co-Head of Oxquant, a consultancy firm that provides expertise and advice on risk management, investments and the impact of artificial intelligence. He is also an Independent Adviser to Oxford Portfolio Advisers.

Richard has over 20 years’ experience in asset management and investment banking in the areas of risk, trading and investments. In particular, he was Global Head of Risk at Investec Asset Management (2010–15), headed a quantitative global macro initiative for the same firm (2006–09) and founded and ran his own hedge fund Oxquant Capital Partners (2004–06).

In addition to his consulting and advisory activities, Richard lectures on statistical machine learning and its applications in finance at Queen Mary University of London. He attended Oriel College, University of Oxford, and holds a doctorate (DPhil) in statistics.

Dr Drago Indjic is an expert data science practitioner and is co-head of Oxquant. He is co-founder of Soft-Finance (Geneva), Technology Partnership (Belgrade) and Richfox Capital (Amsterdam). In addition, Drago has been a technology project funding evaluator for the European Union's ambitious €80bn Horizon 2020 programme since 1997 and will continue in that role with H2020's successor programme. 

Drago has over 25 years’ experience in alternative investments and entrepreneurship and has worked as a portfolio manager and in research at several hedge funds, a family office and for a GCC sovereign wealth fund. He is an investor in a number of fintech businesses. 

Drago lectures regularly on fintech and hedge funds at Queen Mary University of London and Regent's University. He holds a Dipl Ing from the University of Belgrade and a PhD from Imperial College, London; and is a Member of the IEEE and IET.

Rogelio Cuevas is a Data Scientist, Senior Manager at TD Bank where his main responsibility is providing data science and machine learning solutions for different lines of business. Prior to his tenure with TD Bank, he was a Data Scientist at Scotiabank where he developed credit risk models in retail banking through the prototyping and implementation of machine learning techniques. 

He is an active member of the Toronto data science community where he offers mentoring and training to professionals. Part of these activities include being a panelist at Rotman School of Business, mentor at Insight Data Science Toronto and invited speaker at University of Toronto. 

Before his experience in the financial sector, Rogelio contributed with IBM through its Cognitive Class initiative, formerly known as Big Data University. 

Rogelio has a strong academic background and research experience that he acquired working in academic institutions that include McMaster University, Duke University and The University of Western Ontario. 
 

Vishal Gossain is currently the vice president of global risk management responsible for all global regulatory and non-regulatory retail models, and application of artificial intelligence and machine learning for retail products. Vishal has held previous senior retail modeling, risk management, business strategy, P&L management and finance positions in Latin America and North America. Some of them include Head of credit risk for HSBC in Latin America, Head of credit risk for Capital One Canada and several other risk/business management positions in HSBC USA and consulting firms. 
Vishal currently sits on the board of MIT Computer Science and Artificial Intelligence Laboratory and University of Western Post-graduate program.
Vishal holds an undergraduate degree in engineering from Indian Institute of Technology (IIT) Kharagpur and has completed his post-graduation in engineering from University of Texas at Austin.
 

Jesús Calderón advises Canadian and international clients in the financial services and energy industries on the implementation of data-driven solutions for risk management in  banking, insurance, capital markets, and energy trading, as well as anti-money laundering and regulatory activities. Jesús has over twelve years of experience in risk management, internal audit, and fraud investigations, where he has specialized in the application of data science and machine learning methods to optimize risk control activities and examinations.