Research Lead, J.P. Morgan AI Research
Dr. Liu is an AI Research Lead at JP Morgan AI Research focusing on machine learning and natural language processing to improve the productivity in financial services. Prior to JP Morgan, Xiaomo was a Director of Data Science at S&P Global and 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. Xiaomo has serviced as PCs in various conferences like KDD, IJCAI, CIKM, IWSC etc. He also organized two AAAI workshops.
Managing Director, J.P. Morgan AI Research
Sameena 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. She was one of the invited speakers in IJCAI 2021. She has organized several workshops in AAAI, KDD, ICML, etc.
Research Director, J.P. Morgan AI Research
Armineh is Vice President of AI Research at J.P. Morgan Chase. Her career spans a decade of applied research in Natural Language Processing in areas such as targeted sentiment analysis, event detection and verification, information extraction, and social data mining. Prior to J.P. Morgan, Armineh was a Director of Data Science at S&P Global, where she led efforts to transform operational workflows related to the ingestion and processing of financial disclosures. In addition to numerous publications and patents, Armineh’s research has been deployed in award-winning AI-driven technologies such as Reuters Tracer, Westlaw Quick Check, and the SocialZ Verve index.
Research Lead, J.P. Morgan AI Research
Zhiqiang is a research scientist at JP Morgan AI Research. His work concentrates on natural language processing such as information extraction from financial documents, news text clustering and classification, event detection, and topic modeling. Previously, he was a Senior Data Scientist at S&P Global Ratings. He received his Ph.D. in computer science from UNC at Charlotte. He had co-organized two AAAI workshops and served as PC members for multiple conferences and workshops.
Gerard de Melo
Professor, University of Potsdam (Chair for AI and Intelligent Systems)
Dr. Melo has developed core natural language processing, data mining, and machine learning methodologies. He received his doctoral degree from Saarland University / the Max Planck Institute for Informatics, Germany and spent two years as a post-doctoral research scholar at ICSI/UC Berkeley. He then worked as an assistant professor at Tsinghua University in Beijing and at Rutgers University in New Jersey prior to joining the University of Potsdam. He has published more than 120 peer-reviewed papers and received multiple best paper awards. He served as area chairs and senior program committee members for ACL, COLING, EMNLP, NAACL, WWW, IJCAI, etc. He also has organized five workshops in various conferences.
Professor, Mohamed bin Zayed University of Artificial Intelligence
Prof. Le Song is the Deputy Department Chair of the Machine Learning Department, MBZUAI. Prof. Le Song was an Associate Professor of Computational Science and Engineering and also the Associate Director of Center for Machine Learning at Georgia Institute of Technology in the USA. He holds the PhD in Computer Science from the University of Sydney and National ICT Australia. Prof. Le Song published more than 160 papers in peer-reviewed top machine learning conferences and journals such as NeurIPS, ICML, ICLR, AISTATS and JMLR over the past 15 years. He was invited as an Area Chair in many international conferences. Prof. Le Sone is also an active member of several regional and international groups in the field of Machine Learning, Artificial Intelligence and Statistics, such as the board member of the International Conference on Machine Learning. Prof. Le Song’s remarkable works won several best paper awards at the ACM Conference on Recommendation System (Recsys) in 2016, Artificial Intelligence and Statistics (AISTATS) in 2016, IEEE International Parallel & Distributed Processing Symposium (IPDPS) in 2015, Neural Information Processing Systems (NeurIPS) in 2013, and International Conference on Machine Learning (ICML) in 2010. He was also the recipient of the National Science Foundation CAREER Award in 2014, and Outstanding Junior Faculty Research Award in 2014 and Lockheed Martin Inspirational Young Faculty Award in 2014.