Organizers

Alina Oprea is an Associate Professor at Northeastern University in the Khoury College of Computer Sciences. She joined Northeastern University in Fall 2016. Before that, Alina was a Consultant Research Scientist at RSA Laboratories, performing research in security analytics, cloud security, applied cryptography, and foundations of cybersecurity. She is the recipient of the Technology Review TR35 award for research in cloud security in 2011 and the recipient of the Google Security and Privacy Award 2019. Alina serves as Program Committee co-chair for the IEEE Symposium on Security and Privacy 2020.

Avigdor Gal is a Professor of the Faculty of Industrial Engineering & Management at the Technion and an expert on information systems. His research focuses on effective methods of integrating data from multiple and diverse sources, which affect the way businesses and consumers seek information over the Internet. After a two-year stint from 1995-1997 as a postdoctoral fellow at the University of Toronto in the Department of Computer Science, Prof. Gal started his academic career as an assistant professor at Rutgers University. He joined the Technion in 2001 and has been active in numerous Technion activities including having served as Vice Dean for Teaching from 2008-2011. Prof. Gal has published more than 100 papers in leading professional journals (e.g. Journal of the ACM (JACM), ACM Transactions on Database Systems (TODS), IEEE Transactions on Knowledge and Data Engineering (TKDE), ACM Transactions on Internet Technology (TOIT), and the VLDB Journal) and conferences (SIGMOD, VLDB, ICDE, BPM, DEBS, ER, CoopIS) and books (Schema Matching and Mapping). He authored the book Uncertain schema Matching in 2011, serves in various editorial capacities for periodicals including the Journal on Data Semantics (JoDS), Encyclopedia of Database Systems and Computing, and has helped organize professional workshops and conferences nearly every year since 1998.

Eren Kurshan is the Executive Head of AI and Machine Learning for Client Protection at Bank of America Corporation. In this role she is responsible for leading the development of custom Machine Learning and Deep Learning solutions for fraud detection, prevention and operational improvement for Bank of America. Dr. Kurshan and her team built the first generation of in-house AI and Machine Learning models for Bank of America’s payment systems portfolio (including Credit Card, Debit Card, ATM, Wire, ACH, P2P Payments, Checks, Deposits, Online/Bill Pay transactions, Alert Processing and Prioritization etc) processing over 50MM transaction/day volume in real-time. Prior to her role at Bank of America, Dr. Kurshan has served as the executive lead for various AI and Data Science Programs at Columbia University, J.P. Morgan Corporate and Investment Bank, and IBM. Dr. Kurshan was a Visiting Fellow at Princeton University Center for Information Technology Policy during 2015-2016. She has been serving as an Adjunct Professor of Computer Science at Columbia University since 2014. Dr. Kurshan received her Ph.D. in Applied Algorithms and Theoretical Computer Science from the University of California. She has over 60 peer reviewed technical conference and journal publications and over 100 patents. She was the recipient of 2 Best Paper Awards from IEEE and ACM Conferences, Outstanding Research and Corporate Accomplishment Awards from IBM.

Isabelle Moulinier is a Senior Director of Data Science at Capital One where she leads research and development in NLP. Before joining Capital One, she was a Director of Research at Thomson Reuters where she led research efforts in information retrieval and machine learning for the Legal and Tax verticals. Isabelle has been alternating as the Artificial and Data Science program co-chair at the Grace Hopper Celebration of Women in Computing for the past 5 years, she has co-chaired the 2014 and 2019 SIGIR industry track, she co-organized workshops on Operational Text Classification (SIGIR, KDD) and has been a member of various program committees (AAAI, SIGIR, CIKM). https://www.linkedin.com/in/isabellemoulinier/

Jiahao Chen is a Vice President and Research Lead at JPMorgan AI Research in New York, with research focusing on explainability and fairness in machine learning, as well as semantic knowledge management. He was previously a Senior Manager of Data Science at Capital One focusing on machine learning research for credit analytics and retail operations. When still in academia, Jiahao was a Research Scientist at MIT CSAIL where he co-founded and led the Julia Lab, focusing on applications of the Julia programming language to data science, scientific computing, and machine learning. Jiahao has organized JuliaCon, the Julia conference, for the years 2014-2016, as well as organized workshops at NeurIPS, SIAM CSE, and the American Chemical Society National Meetings. Jiahao holds a PhD in chemical physics, a MS in applied mathematics, and a BS in chemistry, all from UIUC. He was formerly a postdoctoral associate at MIT, a visiting scholar at Ritsumeikan University in Japan, and a member of technical staff at DSO National Laboratories in Singapore. Jiahao has written 35 papers with over 400 citations, as well as over 120 packages for numerical computation, data science and machine learning for the Julia programming language, in addition to numerous contributions to the base language itself. https://jiahao.github.io

Manuela M. Veloso 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.

Senthil Kumar is a Director of Data Science at Capital One where he applies Machine Learning and AI to various business problems. Prior to joining Capital One, he was at Bell Labs where he developed and managed several successful products that have been licensed around the world. He has published over 30 papers and holds 6 patents. Most recently, he co-organized the KDD 2017 Workshop on Anomaly Detection in Finance, the 2018 NeurIPS Workshop on Challenges and Opportunities of AI in Financial Services: the Impact of Fairness, Explainability, Accuracy, and Privacy, the 2019 ICML Workshop on AI in Finance: Applications and Infrastructure for Multi-Agent Learning, and the 2019 2nd KDD Workshop on Anomaly Detection in Finance.

Tanveer A Faruquie is a Senior Director of Data Science at Capital One where he heads the Machine Learning and AI group for small business. Prior to joining Capital One, he worked at IBM Research where he conducted research, developed products and built solutions in the areas of Human Language Technologies, Information Management and Business Analytics. His interests include Machine Learning, Natural Language Processing, and Scalable analytics. He has over 50 publications and 20 patents, served as PC member of over 30 conferences and is a senior member of IEEE and ACM.