Organizers
Leman Akoglu, Carnegie Mellon University: Leman Akoglu is an associate professor of Information Systems at the Heinz College of Carnegie Mellon University, with courtesy appointments in the Computer Science and Machine Learning Departments of School of Computer Science. She received her PhD from the Computer Science Department at Carnegie Mellon University in 2012. Her research interests are algorithmic problems in data mining and applied machine learning, focusing on patterns and anomalies, with applications to fraud and event detection. Dr. Akoglu's research has won 7 publication awards; Best Paper at SIAM SDM 2019, Best Student Machine Learning Paper Runner-up at ECML PKDD 2018, Best Paper Runner-up at SIAM SDM 2016, Best Paper at SIAM SDM 2015, Best Paper at ADC 2014, Best Paper at PAKDD 2010, and Best Knowledge Discovery Paper at ECML PKDD 2009. Dr. Akoglu is a recipient of the NSF CAREER award (2015) and Army Research Office Young Investigator award (2013). Her research has been supported by the NSF, US ARO, DARPA, Adobe, Facebook, Northrop Grumman, PNC Bank, and PwC.
Email: lakoglu@andrew.cmu.edu
Mihai Cucuringu, University of Oxford & The Alan Turing Institute: Dr. Cucuringu is an Associate Professor in the Department of Statistics, an Affiliate Faculty in the Mathematical and Computational Finance group at the Mathematical Institute, at University of Oxford, and a Fellow at Turing Institute in London. Previously, he was a CAM Assistant Adjunct Professor in the UCLA Dept. of Mathematics. He finished his Ph.D. in Applied Mathematics at Princeton University in 2012. His research pertains to the development and mathematical analysis of algorithms that extract information from massive noisy data sets, network analysis and certain inverse problems on graphs, such as clustering and ranking, with an eye towards extracting structure from time-dependent data which can be subsequently leveraged for prediction. His research interests in finance focus on statistical arbitrage, machine-learning for asset pricing, market microstructure in equity and crypto markets, synthetic data generation, and anomaly detection in financial networks. He previously organized a workshop on Network Science in Financial Services at The Turing Institute.
Email: mihai.cucuringu@stats.ox.ac.uk
Xiaowen Dong, University of Oxford: Dr Xiaowen Dong is an Associate Professor in the Department of Engineering Science at the University of Oxford, where he is an academic member of both the Machine Learning Research Group and the Oxford-Man Institute. His main research interests concern signal processing and machine learning techniques for analysing network data, and their applications in studying questions across social and economic sciences.
Email: xdong@robots.ox.ac.uk
Dhagash Mehta, BlackRock, Inc. (Primary Organizer): Dr Dhagash Mehta is the Head of Applied Machine Learning Research (Investment Management) at Blackrock Inc. Previously, he was a Senior Manager of Investment Strategies at The Vanguard Group leading a research group on machine learning and investment strategies. He was a Senior Research Scientist at United Technologies Research Center; a research assistant professor at University of Notre Dame and North Carolina State University; a research fellow at Syracuse University, the University of Cambridge, Simons Center for Theory of Computing and National University of Ireland Maynooth. He possesses Part III Mathematical Tripos from the University of Cambridge, and a Ph.D. between the University of Adelaide, Australia, and Imperial College London in Applied Math/Theoretical Physics areas. He has published 55+ journal articles and 25+ conference proceedings, and his research expertise are in loss landscapes of deep learning, applications of algebraic geometry to machine learning, machine learning and non-convex methods for portfolio optimization, NLP and graph machine learning for financial applications, robo-advisory system and behavioural finance. Dr Mehta is also on the editorial advisory board at Journal for Financial Data Science. Dr Mehta has co-organized three large conferences at International Center for Theoretical Physics Trieste (Italy) and Sanya International Mathematics Forum; a workshop at Neurips 2020; multiple mini-symposia at Society for Applied and Industrial Mathematics conferences; and, multiple sectionals at American Mathematical Society conferences.
Email: dhagashbmehta@gmail.com
Saurabh Nagrecha, eBay: Saurabh Nagrecha is an Applied Researcher at eBay Search Science. Before joining eBay, he was Senior Machine Learning Researcher and Tech Lead at Capital One. He received his PhD from the Department of Computer Science and Engineering at the University of Notre Dame in 2017 specializing in machine learning. His research interests span across data science and machine learning with a focus on highly imbalanced cost-sensitive systems problems. He has 6 years of experience leading projects combating fraud and money laundering in retail trading platforms, financial institutions, auto insurance and travel & expense sectors. He also has a background in teaching as an adjunct faculty member at Capital One Tech College where he led the development of courses in the area of Network Science.
Saurabh organized multiple workshops including a series of workshops on Machine Learning in Finance at Knowledge, Discovery and Data mining (KDD) in 2020 and 2021.
Email: snagrecha@ebay.com
Stefan Zohren, University of Oxford & Turing Institute: Dr. Stefan Zohren is the Deputy Director of the Oxford-Man Institute of Quantitative Finance, an Associate Professor at the Deparment of Engineering Science, an Associate at the Oxford Internet Institute and a Mentor in the FinTech stream at the Creative Destruction Lab at Said Business School, all at the University of Oxford. He is also a Turing Fellow and a member of the European Laboratory for Learning and Intelligent Systems. Outside of academia, Stefan works as a Scientific Advisor at Man Group. His research is focused on machine learning in finance, including deep learning, reinforcement learning, network and NLP approaches, as well as early use cases of quantum computing. Stefan is also a frequent speaker on AI in finance at academic conferences, as well as industry panels and corporate events. He has organised a number of workshops on related areas, including one on Agent-based Modelling and Simulation in Finance at the Turing Institute and one on Machine Learning in Computational Finance at the SIAM conference on Financial Mathematics.
Email: stefan.zohren@eng.ox.ac.uk