Organizers

Leman Akoglu, Carnegie Mellon University:

Leman Akoglu is an associate professor of Information Systems at the Heinz College of Carnegie Mellon University, with courtesy appointments in the Computer Science and Machine Learning Departments of School of Computer Science. She received her PhD from the Computer Science Department at Carnegie Mellon University in 2012. Her research interests are algorithmic problems in data mining and applied machine learning, focusing on patterns and anomalies, with applications to fraud and event detection. Dr. Akoglu's research has won 7 publication awards; Best Paper at SIAM SDM 2019, Best Student Machine Learning Paper Runner-up at ECML PKDD 2018, Best Paper Runner-up at SIAM SDM 2016, Best Paper at SIAM SDM 2015, Best Paper at ADC 2014, Best Paper at PAKDD 2010, and Best Knowledge Discovery Paper at ECML PKDD 2009. Dr. Akoglu is a recipient of the NSF CAREER award (2015) and Army Research Office Young Investigator award (2013). Her research has been supported by the NSF, US ARO, DARPA, Adobe, Facebook, Northrop Grumman, PNC Bank, and PwC.

Nitesh Chawla, University of Notre Dame:

Nitesh Chawla is the Frank M. Freimann Professor of Computer Science and Engineering, and Director of the Lucy Family Institute for Data and Society at the University of Notre Dame. His research is focused on artificial intelligence, data science, and network science, and is motivated by the question of how technology can advance the common good through interdisciplinary research. As such, his research is not only at the frontier of fundamental methods and algorithms but is also making interdisciplinary advances in areas such as health and wellbeing, environmental sciences, finance, and social good. He is a recipient of multiple awards for research and teaching innovation including outstanding teacher awards (2007 and 2010), a National Academy of Engineers New Faculty Fellowship, and a number of best paper awards and nominations. He also is the recipient of the 2015 IEEE CIS Outstanding Early Career Award; the IBM Watson Faculty Award; the IBM Big Data and Analytics Faculty Award; the National Academy of Engineering New Faculty Fellowship; and the 1st Source Bank Technology Commercialization Award. In recognition of the societal and community driven impact of his research, Chawla was recognized with the Rodney F. Ganey Award and Michiana 40 under 40 honor.

Senthil Kumar, Capital One:

Senthil Kumar is the Chief Scientist at the Center for Machine Learning at Capital One where he applies Machine Learning and AI to various business problems.. He is also an adjunct faculty member at Capital One Tech College where he co-leads an MLE training program. Prior to joining Capital One, Dr. Kumar 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 2021 KDD Workshop on ML in Finance and the 2021 ICML Workshop on Representation Learning for e-Commerce and Finance. He is also the co-chair of the 2022 ACM International Conference on AI in Finance.

Vidyut Naware, PayPal:

Vidyut Naware is the Director of AI Research at PayPal where he leads the R&D group’s applied research initiatives in the broad areas of deep learning, graph learning and NLP focusing on domains like fraud / credit risk management, customer service, automation and compliance. Before joining PayPal, he was Director of AI in NIO’s autonomous driving group where his team focused on using advanced AI / ML techniques for building a robust autonomous driving stack by identifying and collecting data from edge case driving scenarios in the field. He also has over a decade of experience in the wireless semiconductor industry at Qualcomm where he led several novel modem and sensor system design projects. His primary research interests are in the areas of Machine learning, Signal Processing, Communication Theory and Information Theory. He has published 10 papers, holds 6 patents and received his PhD in Electrical and Computer Engineering from Cornell University in 2005 and B.Tech in Electrical Engineering from the Indian Institute of Technology (IIT), Bombay in 2000.

Tanveer Faruquie, Capital One:

Tanveer A Faruquie is a Senior Director of Data Science at Capital One Labs where he heads the Machine Learning and AI group. 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, Cognitive computing 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.

Saurabh Nagrecha, eBay Inc:

Saurabh Nagrecha is an Applied Research Tech Lead at eBay Search Science & Monetization and an independent fraud & AML consultant to multiple startups. Before joining eBay, he was Senior Machine Learning Researcher, Manager and Tech Lead at Capital One. He received his PhD from the Department of Computer Science and Engineering at the University of Notre Dame in 2017 specializing in machine learning. His research interests include working on highly scalable, cost-sensitive imbalanced graph classification problems. He has 6 years of experience leading projects combating fraud and money laundering in retail trading platforms, financial institutions, auto insurance and travel & expense sectors. He also has a background in teaching as an adjunct faculty member at Capital One Tech College where he led the development of courses in the area of Network Science.