Xiaomo Liu
Xiaomo is a Director of Data Science at S&P Global Ratings focusing on using machine learning and natural language processing to improve credit rating practices. Prior to S&P, Xiaomo was a senior research scientist at Thomson Reuters, where he invented AI algorithms and systems to help news and legal professionals to automate their workflow. His work has been reported by numerous news media and won industry awards. Xiaomo holds a PhD in computer science from Virginia Tech and published more than 30 peer reviewed papers and 3 US patents.
Sameena Shah
Sameena Shah is a Managing Director in AI Research group at JPMorgan. She is a highly accomplished technology leader with over 20 years of educational and industry experience in engineering, AI, and leading development teams that created top AI technologies in the world for financial, news, commodities and legal businesses. Previously, Sameena was Managing Director, Head of Data Science at S&P Global Ratings where she led the firm’s strategy and development for Augmented Intelligence. Prior to that, Sameena worked at Thomson Reuters for seven years in roles of increasing responsibility that involved building state of the art AI systems resulting in business growth and operational efficiencies. Sameena is also the Founder and CEO of Aylan Analytics LLC, and has worked at Yahoo! Research, a NYC based hedge fund, an International hedge fund, and a global startup. Sameena has a PhD in Distributed Machine Learning and a Masters in Computer Science from IIT Delhi. She is the winner of the top PhD in the country award, Cloudera top AI/ML application award, several best paper awards and recognitions. She has contributed 41 Publications, and 11 Patents.
Manuela M. Veloso
Manuela is on leave from Carnegie Mellon University (CMU) where she is Herbert A. Simon University Professor in the School of Computer Science, and where she was the Head of the Machine Learning Department until June 2018. Manuela recently joined J.P.Morgan Chase to create and head an Artificial Intelligence (AI) Research Center. She researches in AI, Robotics, and Machine Learning. At CMU, she founded and directs the CORAL research laboratory,for the study of autonomous agents that Collaborate, Observe, Reason, Act, and Learn, www.cs.cmu.edu/~coral. Veloso is AAAI Fellow, ACM Fellow, AAAS Fellow, and IEEE Fellow, Einstein Chair Professor of the Chinese National Academy of Science, the co-founder and past President of RoboCup, and past President of AAAI. Veloso and her students research a variety of autonomous robots, including mobile service robots and soccer robots. See www.cs.cmu.edu/~mmv for further information, including publications. Manuela was the Program Chair for IJCAI-07 and Program Co-chair for AAAI-05. She also served as organizers for multiple workshops.
Quanzhi Li
Quanzhi is a senior manager at Alibaba Group.His research interests are NLP, information retrieval, data mining, and machine learning. He has worked on many AI projects in financial domain during his tenure at Alibaba, Thomson Reuters, FactSet and Financial Times. He has published 50+ peer-reviewed papers and is the organizer of the yearly IEEE International Workshop on Big Data for Financial News and Data.
Le Song
Le is a Sr. Director of AI at Ant Financial and Associate Professor at Computational Science and Engineering, Georgia Institute of Technology. Le is heading the machine learning group at Georgia Tech. He developed core machine learning methodology, including kernel methods, feature space embedding methods, graphical models, probabilistic and stochastic modeling, deep learning models, etc. Le received his Ph.D. in Computer Science from the University of Sydney, Australia. He worked as a postdoc fellow at Carnegie Mellon University and a research scientist at Google Research before joining Georgia Tech. He has published more than 140 peer-reviewed papers and received multiple recognitions including best paper awards in NIPS 2013 and ICML 2010. He has organized six workshops in various machine learning conferences and gave tutorial talks in KDD, ICML, and WWW.