Date: Thursday, May 14, 2026
Time: 8:00 a.m. - 5:00 p.m.
Location: Schreiber Center, 16 E. Pearson St., Wintrust Hall, 9th Floor

9:00am | Welcome

9:20am | Session 1: AI Engineering: from POC to Production
Arijit Das, SVP, Digital Asset Innovation, Northern Trust; Pankaj Kamble, SVP, Data and Insights, US Bank; Vijay Pillai, Sr. Director, Head of AI/ML Engineering, CME Group, and Abol Jalilvand (moderator), Department Chair and Professor of Finance; Graduate Program Director, MS Finance; Director, Loyola's Risk Management and Insurance Center
Building a promising AI prototype is the easy part. Getting it into production reliably, securely, in compliance, and at scale is where many financial organizations stall. This session cuts through the noise to examine the engineering discipline required to move from a successful proof of concept to a fully operational system within a regulated financial environment. Panelists will share the architectural decisions, data pipeline design, MLOps frameworks, and organizational challenges that separate one-off experiments from scalable, compliant AI deployments.

10:20am | Keynote: Strategic Implementation of AI at a Major Financial Institution
Tom South, CIO, Northern Trust
The focus of AI at major financial institutions has shifted to production velocity. The CIO roadmap must prioritize an industrialized MLOps infrastructure. This means building a unified platform that ensures security, manages data governance, embeds regulatory guardrails, and abstracts underlying complexity, while still ensuring employee adoption. In this session, Tom South will address how engineering discipline transforms AI from a series of experiments into a scalable, deterministic, and universally available intelligence layer capable of operating within a bank’s strict risk parameters.

11:20am | Break

11:30am | Lighting Sessions

When AI Becomes Your Trading Partner, Diego Klabjan, Professor, Industrial Engineering and Management Sciences, Northwestern University
Beyond AI Code Generation: New Software Engineering Industry Life Cycle, Shadman Zafar, CEO, Vibrant Capital, Former co-CIO, Citi Group
Autonomous Customer Intelligence and AI Agents, Gary Class, Industry Strategist, Financial Services, Teradata
Role of an AI Governance Framework for Growth and Control, Michael Lambert, SVP, Chief Innovation Officer, Wintrust Financial Corp.

12:40pm | Lunch Presentation by Black Kids Predict
Marcelo Worsley, Associate Professor, Computer and Learning Sciences, Northwestern University

1:40pm | Session 2: Engineering Alpha: How Massively Parallel Architectures and World Models Are Reshaping Quantitative Finance
Carson Boneck, Chief Data Officer, Balyasny Asset Management, Guy Lakonishok, Partner and Portfolio Manager, LSV Asset Management, and Shirley Zhang, Senior AI Engineer, Balyasny Asset Management, and Maurits Blok (moderator), Enterprise Cloud Architect, Oracle
The integration of AI at hedge funds has evolved from rudimentary automation to a critical driver of competitive advantage. Today, firms leverage ML and GenAI to analyze diverse, high-frequency data. In this session, we will address the applications and engineering requirements to build hyper-performant, massively parallel processing infrastructures capable of handling terabytes of data and millions of daily queries, presenting challenges in data complexity, speed, and security. In addition, the frontier of world models, which represent a paradigm shift from purely predictive analytics to creating high-fidelity, dynamic simulations of financial markets, will also be discussed. These generative simulators model realistic synthetic data, enabling robust back testing of strategies, perform complex counterfactual market impact analysis, and provide a controlled environment for training reinforcement learning agents without exposing capital to real-world risk. As these world models mature, they promise to equip quantitative funds not just with the ability to find statistical patterns in historical data, but to explore and optimize strategies against a simulated reality.

2:40pm | Session 3: Autonomous Agents and World Models
Dhruv Baronia, SVP, Head of Analytics, Wealth Management, Northern Trust; Ram Peddu, Chief Data and Analytics Officer, BMO; and Steven Keith Platt, Executive Lecturer of Applied AI and Director of Analytics, Loyola's Quinlan School of Business; and LUC Director of the Lab for Applied AI and Site Director, IDEAL
Autonomous agents and world models represent the next frontier of AI in financial services, but what do they actually do, and how do financial institutions begin putting them to work? This session takes a ground-up approach, grounding participants in the core mechanics of how autonomous agents plan, reason, and act across multi-step workflows, and how world models enable institutions to simulate market dynamics, stress-test strategies, and explore counterfactual scenarios without real-world exposure.

From there, the conversation shifts to implementation. Our industry panelists, both actively navigating the integration of these technologies within banking environments, will speak about where autonomous agents are delivering value today. Whether you are evaluating your first agentic workflow or scaling an existing program, this session offers both the conceptual foundation and the institutional perspective to move forward with confidence.

3:40pm | Break and Raffle

3:55pm | Session 4: From Guardrails to Compliance: Enabling AI in a Highly Regulated Environment
Dr. Ajinth Sreedharan, Digital Transformation Initiatives, Business and Enterprise Architecture, Federal Home Loan Bank of Chicago and Garrett Woody, VP, Cloud and AI/ML CoE, Federal Home Loan Bank of Chicago
In highly regulated financial institutions, successful AI adoption depends on well-defined guardrails that enable innovation while protecting trust. Privacy, security, regulatory expectations, ethics, and operational resilience are not obstacles to AI adoption, they are design inputs. When these guardrails are embedded early into how AI is selected, built, and deployed, organizations can move faster with greater confidence. This conversation explores how regulated institutions can operationalize AI in a way that is defensible, scalable, and aligned with both regulatory expectations and business outcomes.

4:55pm | Closing

5:00pm | Adjourn