AI in FinanceStarts May 18,

2027

Victoria Averbukh is a Professor of Practice in the School of Operations Research and Information Engineering (ORIE) at Cornell University and the Director of Cornell Financial Engineering Manhattan (CFEM). As Director, Professor Averbukh designs and leads programs that provide practitioner-led education in quantitative finance for ORIE’s Master of Engineering students while cultivating strong connections among students, alumni, and industry leaders. She also plays a central role in curating forums for professional exchange and idea sharing — most notably CFEM’s annual Future of Finance conference, held each September.

In addition to her leadership responsibilities, Professor Averbukh teaches several courses, most notably Bond Math and Mortgage-Backed Securities — a class grounded in her Wall Street experience — as well as the Financial Engineering Colloquium, which brings industry professionals into the classroom to expose students to cutting-edge developments in finance.

Before joining Cornell, Professor Averbukh worked in Fixed Income Research at Salomon Brothers (now Citi) as a strategist covering U.S. Treasury futures and mortgage-backed securities. She later joined Deutsche Bank, where she became Head of Structured Residential Mortgage-Backed Securities Research.
Professor Averbukh received her B.A. in Mathematics from New York University and her M.S. and Ph.D. in Operations Research from Cornell University.

Andrew Chin is Chief AI Officer and a member of the Operating Committee at AllianceBernstein (AB). In this role, he leads the firm’s strategy to leverage AI in transforming the organization and driving better outcomes for clients and the firm. Previously, Andrew was the Head of Investment Solutions and Sciences, overseeing the research, management and strategic growth of the firm’s asset allocation, data science, index, and tax management businesses.

From 2022 to 2023, Andrew was AB’s head of quantitative research and chief data scientist, developing and optimizing the quantitative research and data science infrastructure, capabilities, and resources across the organization. As the firm’s chief risk officer from 2009 to 2021, he led all aspects of risk management and built a global team to identify, manage, and mitigate the various risks across the organization.

Andrew has held various leadership roles in quantitative research, risk management and portfolio management in New York and London since joining AB in 1997. Before joining the firm, he spent three years as a project manager and business analyst in Global Investment Management at Bankers Trust.

Andrew is a Visiting Lecturer in Cornell’s Master of Financial Engineering program and serves on the Board of Directors of the Society of Quantitative Analysts and the editorial boards of the Journal of Portfolio Management and the Journal of Financial Data Science.

Andrew holds a B.A. in Math and Computer Science as well as an MBA in finance from Cornell University.

David A. Goldberg is an Associate Professor in Cornell’s School of Operations Research and Information Engineering (ORIE). Previously, he was the A. Russell Chandler III Associate Professor in the H. Milton Stewart School of Industrial and Systems Engineering at Georgia Tech. Professor Goldberg received his Ph.D. in Operations Research at MIT in 2011 and his B.S. in Computer Science (minors in Operations Research and Applied Math) from Columbia University in 2006.

Professor Goldberg’s research is in applied probability, on topics including optimal stopping and high-dimensional control, the theory of inventories and queues, and applied operations research.  His work has been recognized with accolades that include an NSF CAREER award, 2019 INFORMS Applied Probability Society Best Publication award, 2019 INFORMS Nicholson Competition first place, 2018 INFORMS Finance Student Paper Competition finalist, 2015 INFORMS Nicholson Competition first place, 2015 INFORMS JFIG Competition second place, and 2014 MSOM and 2010 INFORMS Nicholson Competitions finalist.

Professor Goldberg is also an associate editor for the journals Stochastic Systems and Stochastic Models, former associate editor of the journals Operations Research and Queueing Systems, and former chair of the INFORMS Applied Probability Society.  In addition, Professor Goldberg recently led an initiative to engage more undergraduates in OR/analytics research at Cornell (while serving as Director for Undergraduate Studies in ORIE), for which he was awarded both the 2023 Sonny Yau ’72 Teaching Award of the College of Engineering and the 2025 Community-Engaged Practice and Innovation Award of the Einhorn Center for Community Engagement.

Dr. Dhagash Mehta leads the Applied Machine Learning Research team within BlackRock’s Financial Modeling Group, where he oversees efforts in applied AI, generative AI, and responsible AI for financial and wealth management applications. Dr. Mehta serves on the editorial board of the Journal of Financial Data Science and the Journal of ESG and Impact Investing.

Prior to BlackRock, Dr. Mehta worked as Senior Manager and Investment Strategist for machine learning in asset allocation at Vanguard and as a Senior Research Scientist at United Technologies (now Raytheon Tech). In academia, he held roles including Research Professor at the University of Notre Dame and postdoctoral fellowships at the Fields Institute (Toronto) and the Simons Institute (Berkeley). Dr. Mehta’s earlier research appointments span institutions such as the University of Cambridge, Imperial College London, University of Adelaide, Syracuse University, and NUI Maynooth.

Dr. Mehta holds a Ph.D. in Theoretical Physics, and his research spans AI, optimization, AI for finance, AI for mathematics, and the mathematics of AI.

Jeffrey Varner holds a Bachelor of Science degree in Chemistry as well as a Master’s and a Ph.D. degree in Chemical Engineering from Purdue University. Professor Varner’s graduate thesis work at Purdue was done under the direction of Professor D. Ramkrishna in the area of modeling and analysis of metabolic networks.

Following Purdue, Professor Varner was a postdoctoral researcher in the Department of Biology at the ETH-Zurich, where he studied signal transduction mechanisms involved in cell death under Professor Jay Bailey. After the ETH, Professor Varner was a scientist in the oncology business unit of Genencor International, Inc,, in Palo Alto, CA. While at Genencor, he was involved in the discovery of novel targets in human cancers and was a project team member for preclinical, Phase I, and Phase II studies of protein therapeutics for the treatment of colorectal cancer and chronic lymphocytic leukemia.

Professor Varner left Genencor at the end of 2005 to join the faculty of the Chemical and Biomolecular Engineering Department at Cornell University. At Cornell, the Varner Lab is developing physiochemical modeling tools to rationally reprogram human signal transduction architectures.

Joseph Sommer is Managing Director in Financial Services focused on AI, data governance, and knowledge management, with 30 years of experience across trading, operations, technology, and data at leading investment banks, asset managers, and payments firms. His work centers on helping organizations safely adopt AI by strengthening the foundations of data governance, unstructured content management, and enterprise knowledge. He implements solutions that combine data classification, taxonomy, metadata, and policy-based controls, often leveraging platforms like Microsoft Purview, to enable scalable data protection and AI readiness. Joseph also led initiatives in AI monitoring and observability, helping organizations track usage, enforce controls, and manage risk as AI becomes embedded in business workflows.

In parallel, Joseph advises clients on data monetization and platform strategies, ensuring data delivers measurable value while meeting regulatory and privacy requirements. With deep experience in payments, high-volume transaction systems, and financial data operations, he focuses on practical, business driven solutions that connect governance, AI, and real-world outcomes. He also teaches graduate-level Business Analytics at CUNY Baruch’s Zicklin School of Business.

Jamol  Pender is an Associate Professor and Director of Graduate Studies in the School of Operations Research and Information Engineering at Cornell University.  He received his Ph.D. from Princeton University in 2013, where he was advised by Dr. William Massey.  Professor Pender joined Cornell University in 2015 and serves as a Faculty Fellow in the Residence Halls at Cornell.

Professor Pender is a recipient of a Ford Foundation Fellowship, the NSF CAREER award, MIF Career Award, and several teaching and advising awards, including the Sonny Yau award for teaching excellence, the Zellman Warhaft Commitment to Diversity Award, and the 2023 College of Engineering EPICC award for community building.

Professor Pender’s research focuses on how to disseminate information to customers in queues and how this information affects the underlying dynamics in queues.  He is very interested in the interplay among stochastic processes, simulation, and non-linear dynamics.
Professor Pender is heavily involved in the Applied Probability Society of INFORMS, where he served as the INFORMS APS 2019 conference co-chair.