Keynote Speakers


  • Abhijit Bose, Capital One

  • Rama Cont, University of Oxford

  • Tomaso Aste, University College London

  • Zhi Da, U. Notre Dame

  • Fabio Cacciolli, University College London

  • Petter Kolm, NYU

  • Andreea Minca, Cornell University

  • Bayan Bruss, Capital One

  • Slavi Marinov, Man AHL

  • Yi Dong, NVIDIA


Speaker bios:

  • Tomaso Aste is professor of Complexity Science at UCL Computer Science Department. A trained Physicist, he has substantially contributed to research in financial systems modeling, complex structures analysis, artificial intelligence and machine learning. Prof. Aste is passionate in the investigation of the interplay between technologies and society. He is founder and Head of the Financial Computing and Analytics Group at UCL, co-founder and Scientific Director of the UCL Centre for Blockchain Technologies, Member of the Board of the ESRC LSE-UCL Systemic Risk Centre and Member of the Board of the Whitechapel Think Thank. He collaborates, on FinTech and RegTech topics, with the Financial Conduct Authority, The Bank of England, HMRC and the All-Party Parliamentary Group. He is leading an initiative for training to FinTech central bankers and regulators across South America. He is advisor and consultant for several financial companies, banks, FinTech firms and digital-economy start-ups. He created four Master Programmes at UCL ranging from Risk Management to the Digital Economy.


  • Petter Kolm is the Director of the Mathematics in Finance Master’s Program and Clinical Full Professor at the Courant Institute of Mathematical Sciences, New York University and Partner at CorePoint-Partners.com. Previously, Petter worked at Goldman Sachs Asset Management where his responsibilities included researching and developing new quantitative investment strategies. Petter has coauthored many articles and books on quantitative finance and financial data science and financial data science, serves on several editorial boards for academic journals, professional associations, and company advisory boards. He holds a Ph.D. in Mathematics from Yale, an M.Phil. in Applied Mathematics from the Royal Institute of Technology, and an M.S. in Mathematics from ETH Zurich. Petter’s work and research interests include alternative data, data science, econometrics, forecasting models, high frequency trading, machine learning, portfolio optimization with transaction costs and taxes, quantitative and systematic trading, risk management, robo-advisory and investing, smart beta strategies, transaction costs, and tax-aware investing.


  • Abhijit Bose is the Managing Vice President for Capital One’s The Center for Machine Learning (C4ML). Prior to joining Capital One, Abhijit served as Facebook’s Head of Engineering (Montreal, NYC, Pittsburg) for Facebook AI Research. With over 20+ years of data science expertise, Abhijit encompases an impressive technical and academic career history. He obtained a Bachelor's degree in Mechanical Engineering, received his dual-Masters in Mechanical Engineering as well as Computer Science, and received his dual-Ph.D in Computer Science and Engineering Mechanics. Before joining Facebook, Abhihit was the Managing Director of Data Science for JP Morgan's Digital Organization. He’s also worked for IBM, Google, and American Express. Abhijit and his wife live in New Jersey with their 6-year-old twins and their family pet Eskie. When he’s not working, Abhijit enjoys spending time volunteering with his family at their local animal shelter, as well as hiking and touring state parks.


  • Slavi Marinov is Head of Machine Learning at Man AHL, responsible for everything from hardware through research frameworks to live trading strategies. Prior to joining Man AHL in 2014, he was Co-founder and Vice President of Engineering for a natural language processing fintech start-up, and before that he performed various senior software engineering and product management roles. Slavi holds a BSc in Computer Science and a Silver Medal from the Balkan Olympiad in Informatics.


  • C. Bayan Bruss is the Sr. Director of Applied Machine Learning research at Capital One’s Center For Machine Learning. His team is currently focused on Graph Machine Learning, Decision Theory, Machine Learning for Data and Privacy and Explainable AI. Prior to Capital One Bayan has over a decade of experience in academia, startups and consulting. He has participated in the organizing committees and program committees of several conferences and workshops at KDD, ICAIF, and NeurIPs. He holds an Adjunct Position at Georgetown University.


  • Zhi Da is the Howard J. and Geraldine F. Korth Professor of Finance at the University of Notre Dame’s Mendoza College of Business. His research focuses on empirical asset pricing and investment. In recent papers, he studied the role of limited investor attention, the behavior of institutional investors, and cash flow risks of financial assets. His papers have been published in the Journal of Finance, Review of Financial Studies, Journal of Financial Economics among others. He is currently serving as an associate editor at several leading finance journals including Journal of Finance, Management Science, Journal of Financial and Quantitative Analysis, and Journal of Banking and Finance. Zhi has received the 2017 JFQA William F. Sharpe Award for Scholarship in Financial Research, among other research awards and grants. After gaining a BBA and an MSc from National University of Singapore, he worked at the interest rate and exotic derivative trading desk in DBS Bank. He subsequently earned a PhD in Finance from Northwestern University.


  • Fabio Caccioli is professor of Complex Systems in the Department of Computer Science at University College London. Prior to joining UCL, he has been a research associate in the Centre for Risk Studies, University of Cambridge, and a postdoctoral fellow at the Santa Fe Institute (Santa Fe, US). Fabio holds a PhD in Statistical Physics from the International School for Advanced Studies (Trieste, Italy). His research focuses on the application of statistical mechanics and networks to the study of financial systems, in particular in relation to systemic risk. Other interests include complex networks and non-equilibrium statistical mechanics.


  • Yi Dong is a Senior Deep Learning Solutions Architect at NVIDIA with a role to provide AI solutions to the Financial Service Industry. Yi gained his Ph.D. from John Hopkins University School of Medicine studying computational neuroscience. Yi has 10 years of working experience in computer software engineering, machine learning, and finance. Yi has research interests in fields including neuroscience, artificial intelligence, and high-performance computation.


  • Andreea Minca is an Associate Professor in the School of Operations Research and Information Engineering at Cornell University. She holds degrees from Sorbonne University (PhD in Applied Mathematics) and Ecole Polytechnique (Diplome de l'Ecole Polytechnique). In recognition of "her fundamental research contributions to the understanding of financial instability, quantifying and managing systemic risk, and the control of interbank contagion", Andreea received the 2016 SIAM Activity Group on Financial Mathematics and Engineering Early Career Prize. This award distinguishes contributions to the mathematical modeling of financial markets and is the highest early career distinction in the field of financial engineering and mathematics. Andreea is also a recipient of the NSF CAREER Award (2017), a Research Fellow of the Global Association of Risk Professionals (GARP) (2014), and an AXA Research Fund Awardee (2020). She serves on the editorial board of the SIAM Journal on Financial Mathematics. She has held visiting appointments at Imperial College London, where she delivered the CFM-Imperial Distinguished Lectures in 2018, and at the London Business School, where she taught in the PhD program.


  • Rama Cont is Professor of Mathematics and Chair of Mathematical Finance at Oxford University. He has held previous positions at Columbia University, Imperial College London, Ecole Polytechnique and Sorbonne University, and has served as advisor to IMF, ECB, CME, ICE Clear, Norges Bank, Bovespa and the US Office of Financial Research. His research focuses on stochastic processes and mathematical modeling in finance, with a focus on market instabilities and systemic risk.