AI in Fintech: Bridging Research & Innovation -#NYTechWeek

Wednesday, June 4

5:30pm

ETGMT

Hosted by GoodFin

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Where is AI really taking fintech — and how does cutting-edge research impact and compare to what's actually built and deployed in production? Join GoodFin for a special NY Tech Week session as we unveil new research in collaboration with a leading NYU research team, exploring how AI is transforming financial services. We'll kick things off with a quick dive into the findings, then open it up to a dynamic panel featuring top academics and industry leaders. Expect a candid, cross-disciplinary conversation on how advanced research is actually making its way into commercial fintech products (and vice versa) — and what that means for builders, investors, and consumers. This event is a part of #NYTechWeek—a week of events hosted by VCs and startups to bring together the tech ecosystem. Learn more at www.tech-week.com. Evening Agenda: 5:30 – 6:15 PM | Welcome Mixer Arrivals, networking, drinks & small bites 6:15 – 6:30 PM | Presentations Benchmarking LLMs on CFA-Level Reasoning User Study: AI Concierge in High-Trust Wealth Platforms 6:30 – 7:15 PM | Panel: From Paper to Production How research makes it into real-world fintech tools — or doesn’t. 7:15 – 8:30 PM | Mixer Continues Conversations, connections, and follow-ups Panel: From Paper to Production What does it really take to bring academic breakthroughs to life in fintech? We'll explore the messy middle — the gap between novel ideas and live products — and how leaders navigate technical risk, perception gaps, and real-world constraints. Confirmed Panelists Daniel Wu (Former Head of AI & ML, JPMorgan Chase | Stanford AI Program Instructor) Daniel has led some of the largest AI deployments in commercial banking, including JPMorgan’s firmwide LLM initiatives. With a background spanning finance, healthcare, and enterprise software, he brings a sharp focus on scaling AI systems responsibly. He also teaches in Stanford’s AI Professional Program and is a frequent speaker and author on generative and agentic AI. Srikanth Jagabathula (Professor, NYU Stern School of Business | Academic Director, Khubani BTE Program | Robert Stansky Research Faculty Fellow) Srikanth is a distinguished researcher in AI and operations, with deep expertise in decision-making systems, personalization, and large-scale machine learning. He bridges cutting-edge theory with practical impact across domains, and currently serves as the academic director of Stern’s Khubani Business Technology & Entrepreneurship Program. His startup Celect, based on his doctoral work, was acquired by Nike. Chinmay Hegde (Associate Professor, NYU Tandon | Machine Learning & Signal Processing Expert) Chinmay’s research spans deep learning, signal processing, and optimization. An ICML Best Paper winner and NSF CAREER recipient, his work focuses on algorithmic foundations of modern ML and applications in areas like autonomous driving, risk modeling, and robust inference.

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