Every brilliant experiment, like every great work of art, starts with an act of imagination.
~ Jonah Lehrer
Over my career, I’ve delivered keynote presentations, led industry roundtables, been a panelist, hosted panels, and given lectures at academic institutions covering a number of broad topics, including AI, data science, automation, operations, strategy, and financial technology. My talks focus on bridging strategy, execution, and emerging technologies, providing practical insights for decision-makers, executives, engineers, and technologists. Each presentation is built on personal experiences and is far more practical than academic.
Featured Keynotes & Industry Talks
The Future of Money: How Distributed Ledgers are Changing Finance
An exploration of how distributed ledger technology (DLT) and blockchain are reshaping global finance, payments, and capital markets. Covering use cases from tokenization to smart contracts, this talk examines the strategic implications for banks, fintechs, and asset managers.
Why AI Projects Fail: Setting the Right Goals and Expectations
AI project failure is often due to unclear objectives, unrealistic expectations, and poor execution strategies. This session dissects common pitfalls and outlines a framework for successful AI adoption, ensuring alignment between business strategy and AI capabilities.
Generative AI ROI: Where’s the Promised Return?
Despite the hype around GenAI, organizations struggle to measure its true impact. This talk provides a framework for quantifying early value, tracking ROI for LLM applications, and establishing long-term AI success metrics.
Applying Capital Budgeting Best Practices to Use Case Selection
Many organizations lack a structured approach to prioritizing AI and automation initiatives. This talk applies capital budgeting principles to AI use case selection, helping leaders optimize investments and resource allocation.
Roundtables & Expert Panels
The Next Generation of Intelligent Automation
An expert discussion on the evolution of automation—from RPA to AI-powered decision-making. Exploring the intersection of big data, process optimization, and next-gen automation tools.
The ABCDs in Finance: Automation, Big Data, Cloud, and Digital
A deep dive into the four pillars of modern financial technology, how they intersect, and what forward-thinking firms are doing to leverage these enablers for strategic advantage.
Question-Answering with LLMs, RAG, and Human-in-the-Loop Systems
Exploring the future of AI-powered knowledge retrieval, this talk examines Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and hybrid AI-Human workflows (AH-HI).
Macro Forces Shaping AI Policy and Adoption
From regulatory frameworks to technological autonomy, this discussion explores external forces driving AI adoption, policy challenges, and the future of AI-driven industries.
Investment Management and AI: Two Futures
AI is transforming investment management, but not all firms are keeping up. This talk contrasts AI-driven leaders vs. traditional investment approaches, highlighting the competitive edge of AI-first firms. Thematically, I break the discussion into a story about the leaders versus the story of the laggards.
Business & Strategy Talks
Business Strategy to Project Goals: The 3M Approach
In this talk, I discuss the 3M approach (Macro-Mezzo-Micro) to create a cohesive roadmap for AI, automation, and digital transformation by ensuring alignment between long-term macro trends, organizational strategy, and project-level execution.
The Productivity Equation: Why Tech Alone Won’t Solve the Problem
Digital transformation isn’t just about technology improvements—it requires process optimization, mindset shifts, and cultural change. This session dissects the true drivers of productivity growth.
Digital Enablers and Coping with Change
Addressing the challenges of digital transformation, this talk provides practical strategies for adapting to rapid technological change within organizations.
Strategies to Capitalize on the Drivers of Digital Transformation
A structured approach to leveraging AI, data, and automation to create long-term business value, improve efficiency, and gain a competitive advantage.
The Business Intelligence Innovation Model
BI success depends on tools and a strategic approach to data architecture, decision-making, and analytics adoption. I cover the importance of shifting the mindset from technology-focused to strategy-focused, involving all organization components.
TOM Design: A Foolproof Framework for the Future Organization
How to design and implement a Target Operating Model (aka a TOM) that aligns with business goals, integrating people, processes, and technology to create scalable operating models. I cover the importance of data, governance, infrastructure, and the Lines of Defense (LoD) model.
An AI-First Asset Servicing Model
A vision for leveraging AI in asset servicing, focusing on workflow automation, decision-support, and NLP-powered extraction, summarization, and translation.
University & Academic Lectures
Innovation in Financial Services
A university lecture for MBA students in London on how innovation is reshaping finance, covering AI, quantum computing, and distributed ledger technology.
The Future of Data Science in Finance
A discussion on the evolving role of data science in financial services, covering career pathways, industry needs, and emerging technologies. Lecture given to data science majors at one of Boston’s most storied universities.
The S-E-T Model: Scientist, Engineer, Technician
A framework for creating a sustainable data science lifecycle, ensuring continuous innovation, operational scalability, and cross-functional collaboration.
Target Operating Model Design
Technology & Data Engineering Talks
Blockchain for Finance: Use Cases, Adoption, and Competitive Moats
Beyond crypto, blockchain is reshaping financial services. This talk covers DLT applications in capital markets, payments, and regulatory compliance.
Behavioral Finance and Nudge Theory in Investment Platform Design
How behavioral economics and cognitive biases influence investor decision-making, and how AI-powered platforms can use nudges to improve financial outcomes.
Impact Investing: Big Data and the Data Sparsity Problem
The challenge of using alternative data sources in impact investing and strategies to overcome data limitations while maintaining portfolio integrity.
Designing Multi-Dimensional Models
Part of a series I did on Data Warehousing Fundamentals. This was the best and most discussed part of the series, where I introduced a practical guide to data warehouse design, covering dimension modeling, ETL best practices, and schema optimization. Borrowed heavily from the Kimball books, this talk merged Kimball Institute’s best practices with real-world applications in finance.
Time Series Analysis and Fact Tables in Enterprise Analytics
Bridging the gap between business funding priorities and engineering best practices is challenging in large-scale data analytics initiatives—especially when dealing with terabytes of time-series data. To address this, I developed a concise, practical framework advocating dimensional modeling as the foundation for complex analytical workloads. What began as a simple approach document to facilitate cross-functional alignment quickly gained traction. As I shared it more widely, it evolved into a training program and eventually a conference talk, helping organizations unlock the full potential of fact table design for time-series forecasting and trend analysis.
Building ETL Pipelines: Hand-Coded vs. Modern Data Integration Tools
Lessons learned from building custom ETL pipelines, the trade-offs of manual coding vs. automation tools, and best practices for scalable data engineering.
Want to discuss these topics? Also, check out my projects and writings for more information.
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