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.
Josep Domingo-Ferrer, Universitat Rovira i Virgili:
Josep Domingo-Ferrer is a Distinguished Full Professor of Computer Science and an ICREA-Acadèmia Researcher at Universitat Rovira i Virgili, Tarragona, Catalonia, where he is the founding director of CYBERCAT-Center for Cybersecurity Research of Catalonia. He also runs the UNESCO Chair in Data Privacy. His research interests are in data privacy, data security, statistical disclosure control and cryptographic protocols, with a focus on the conciliation of privacy, security and functionality. He currently works on ethics-by-design in information technologies, with an emphasis on trustworthy machine learning. He has won four consecutive times the ICREA-Acadèmia Prize, awarded for a 5-year period by the Government of Catalonia to research leaders. He is an IEEE Fellow, an ACM Distinguished Scientist, an AAIA Fellow, an elected member of Academia Europaea and the International Statistical Institute, and a Fellow of the Institut d’Estudis Catalans (the Catalan national academy).
Eren Kurshan, Morgan Stanley:
Eren Kurshan currently leads Research and Methodology efforts at Morgan Stanley towards building capabilities in emerging AI/ML techniques such as graph AI/ML, KG based reasoning etc. Prior to this role, she was the Executive Head of AI and Machine Learning for Client Protection at Bank of America Corporation, where she was responsible for leading the development of custom Machine Learning and Deep Learning solutions for fraud detection, prevention and operational improvement. 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, Wires, ACH, P2P Payments, Checks, Deposits, Online/Bill Pay transactions, Alert Processing and Prioritization etc). Dr. Kurshan has served as the technical lead for various AI and Data Science programs at Columbia University, J.P. Morgan Corporate and Investment Bank, and IBM. She was a Visiting Fellow at Princeton University Center for Information Technology Policy during 2015-2016 and served 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.
Senthil Kumar, Capital One:
Senthil Kumar heads Emerging Research 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 2022 KDD Workshop on ML in Finance and the 2021 ICML Workshop on Representation Learning for e-Commerce and Finance. He was also the co-chair of the 2022 ACM International Conference on AI in Finance.
Vidyut Naware, PayPal:
Vidyut Naware is Senior Director, Head of Generative AI Center of Excellence at PayPal where his team is responsible for driving Generative AI initiatives across all functions of the company with an objective of achieving key business objectives while balancing the need of mitigating risks of Generative AI through proper governance and technology guardrails. Prior to that he led PayPal’s applied AI/ML 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. 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 VP of Data Science at Capital One 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, Google:
Saurabh Nagrecha is an Engineering Manager fighting ad abuse on mobile at Google’s scale of operations. Before Google, he was at eBay, Capital One and was an independent fraud & AML consultant to multiple startups. 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 7 years of experience leading projects combating fraud and money laundering in ad tech, 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.
Mahashweta Das, Visa Research:
Mahashweta Das is a Senior Director, AI at Visa Research where she leads a group of AI researchers and engineers focused on conducting foundational research, creating new products/early prototypes that incorporate research breakthroughs, and delivering innovative technologies to Visa's strategic products and businesses. She is also affiliated with Northeastern University Silicon Valley Campus as part-time lecturer. Previously, she has held positions at Hewlett Packard Lab, Yahoo! Research, Technicolor Research, and IBM Research. Mahashweta received her Ph.D. in Computer Science from the University of Texas at Arlington in 2013. Her research interests include machine learning, deep learning, data mining, and algorithms. She has published over thirty refereed articles at premier international research conferences and journals, and regularly serves on the program committee of these conferences. Her PhD dissertation received Honorable Mention at ACM SIGKDD 2014 Doctoral Dissertation Award.
Isha Chaturvedi, Capital One:
Isha Chaturvedi is an AI researcher at Capital One working in LLM space. She has 5+ years of industry experience in ML and has worked in Conversational AI space and Computer Vision. Previously, she worked as a data scientist on the computer vision team at Ericsson. She has also worked in the Urban Observatory and Sounds of New York City research labs at New York University, where she completed her master’s degree in urban data science. Isha earned her undergraduate degree in environmental technology and computer science at Hong Kong University of Science and Technology and later worked on augmented reality and computer vision in HKUST-Deutsche Telecom Systems and Media Lab as a research assistant. Isha is an Oreilly instructor where she teaches courses on Few-Shot Learning. She also serves as an Advisory Board Member at University of California, Riverside.
Jose A. Rodriguez-Serrano, Esade
Jose A. Rodríguez-Serrano is a Senior Lecturer at the Esade Business School (Barcelona) since 2022. Formerly he was Data Science Program Manager at BBVA, and Machine Learning Area Manager at Xerox Research. His trajectory is a mix of applied research and technology transfer: he has published papers in top AI conferences and journals such as CVPR, ICCV, NeurIPS, IEEE PAMI, IJCV, holds over 20 patents and has participated, both as a contributor and as manager, in delivering machine learning functionalities both into functioning prototypes as well as products that are commercially available. In the last 8 years he has worked in applications of machine learning for retail banking: at BBVA, he led the team deploying the first ML models in the app and set up an internal innovation program which was awarded by FastCompany. Now at Esade he continues a research line in real estate valuation and other financial applications of AI.