Keynote Speakers




  • Daniel Palomar (Hong Kong University of Science and Technology)
    Daniel Palomar is a Professor in the Department of Electronic and Computer Engineering and Department of Industrial Engineering & Decision Analytics at the Hong Kong University of Science and Technology (HKUST), which he joined in 2006. He received the Electrical Engineering degree and the Ph.D. degree from the Technical University of Catalonia (UPC), Barcelona, Spain, in 1998 and 2003, respectively, and he was a Fulbright Scholar at Princeton University during 2004-2006. He has held several visiting research appointments, namely, at King’s College London (KCL), London, UK; Technical University of Catalonia (UPC), Barcelona; Stanford University, Stanford, CA; Telecommunications Technological Center of Catalonia (CTTC), Barcelona; Royal Institute of Technology (KTH), Stockholm, Sweden; University of Rome “La Sapienza”, Rome, Italy; and Princeton University, Princeton, NJ.


Daniel is an IEEE Fellow and, among others, has been awarded with the 2004/06 Fulbright Research Fellowship and the 2004, 2015, and 2020 Young Author Best Paper Awards by the IEEE Signal Processing Society. He has served as Associate Editor of IEEE Transactions on Information Theory, Associate Editor of IEEE Transactions on Signal Processing, Guest Editor of the IEEE JSTSP 2016 Special Issue on “Financial Signal Processing and Machine Learning for Electronic Trading,” Guest Editor of the IEEE Signal Processing Magazine 2010 Special Issue on “Convex Optimization for Signal Processing,” Guest Editor of the IEEE Journal on Selected Areas in Communications 2008 Special Issue on “Game Theory in Communication Systems,” the Lead Guest Editor of the IEEE Journal on Selected Areas in Communications 2007 Special Issue on “Optimization of MIMO Transceivers for Realistic Communication Networks.” He was the General Co-Chair of the 2009 IEEE Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP) and have served as part of the Organizing Committee of ICASSP 2015, SPAWC 2015, and EUSIPCO 2011.


  • Stefano Pasquali (BlackRock, Inc.)

Stefano Pasquali is a Managing Director and the Head of Liquidity and Trading Research at BlackRock, Inc. He oversees product development and research for Bloomberg's liquidity and systemic risk solutions and has been instrumental in bringing machine learning including natural language processing as well as network science and graph machine learning into liquidity, trading, portfolio optimization and investment processes in general.

Prior to working at BlackRock, Stefano was a quantitative analyst/specialist supporting Bloomberg Valuation Services (BVAL), an evaluated pricing product, since 2009. In 2010 Stefano moved on to lead liquidity research for Bloomberg's Pricing Services, which conducted fixed income market liquidity research and calibrates financial models for measuring risk and market impact. Prior to joining Bloomberg, Stefano held senior positions at several European banks and asset management firms where he oversaw risk management, portfolio risk analysis, model development and risk management committees. Stefano built a risk management process for a global asset management firm with 100 Billion+ AUM involving projects from data acquisition and normalization to model development and portfolio management support.

Before his career in finance, Stefano was a researcher in physics focusing on Theoretical and Computational Physics (in particular Monte Carlo Simulation, Solid State physics, Environment Science, Acoustic Optimization). Originally from Carrara, Italy, Stefano is a graduate of Parma University and holds master degree in Theoretical Physics, as well as research fellowships in Computational Physics at Parma University and Reading University (UK).


  • Prof Tomaso Aste (University College London)

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.