financial aisecurity, privacyand safety.

He is a Senior Researcher at the FSI. He leads the development of financial AI regulatory guidelines and conducts research on secure AI systems in the financial domain. His work focuses on secure and safe AI for financial institutions, including AI governance and safety evaluation. His work has been published at leading AI and data mining venues, including ACM TKDD, CIKM, and IEEE ICDM, and has contributed to national R&D projects and financial AI governance initiatives.

Yongjae Lee is an Associate Professor at UNIST and the Chief Scientist of LinqAlpha AI Lab. He leads research on how AI systems understand financial information, reason about markets, and make reliable investment decisions. He serves on the Editorial Advisory Board of the Journal of Financial Data Science. He has actively contributed to the AI-for-finance research community as a workshop organizer and chair, including serving as Workshop Chair for ACM ICAIF 2024 and organizing related workshops at NeurIPS, ICLR, CIKM, AAAI, KDD, and ICAIF (Ph.D. in Industrial and Systems Engineering).

He is a Team Leader in the Financial Tech Lab at kakaobank, where he leads AI research and development for advanced banking services. His expertise includes real-world banking AI systems, financial service deployment, and the practical challenges of applying AI in digital banking environments (Ph.D. in Electrical Engineering at KAIST).

Yan Gao is a Research Scientist at Flower Labs and Adjunct Researcher at the University of Cambridge, where he works on privacy-preserving AI and federated learning. He has led the development and operation of a privacy-preserving AI platform (FlowerHub) which includes financial applications such as fraud detection. Given that raw customer data cannot be centrally shared due to privacy, his expertise is important in financial AI privacy (Ph.D. in Computer Science).

He is a Team Leader at KFTC, where he leads initiatives in financial AI transformation, anti–money laundering, financial synthetic data generation, and the development of finance-specific benchmarks (Ph.D. in Computer Science).

Edoardo Vittori is a Business Director within Cross Asset Systematic Trading at Intesa Sanpaolo IMI CIB, where he works on portfolio construction and the development of systematic trading capabilities from research to production. He also contributes to the division’s work on AI strategy. He holds a PhD in Machine Learning from Politecnico di Milano, with research spanning reinforcement learning and online learning for trading, execution, hedging, market making, and portfolio optimization.

Dhagash leads the Applied Artificial Intelligence team within BlackRock, where he oversees efforts in applied AI, generative AI, and Trustworthy AI for financial and wealth management applications. He serves on the editorial board of the Journal of Financial Data Science and the Journal of ESG and Impact Investing, and is on the executive committee of ACM International Conference on AI in Finance (ACM-ICAIF). Dr. Mehta holds a Ph.D. in Theoretical Physics from a joint program between the University of Adelaide (Australia) and Imperial College London (UK), and his current research spans AI, optimization, AI for Finance, and Trustworthy AI.

Saurabh Nagrecha is a senior technical lead in applied research at Google, overseeing fraud defenses across all Google Ad serving surfaces. His work focuses on leveraging multimodal AI, graph neural networks (GNNs), foundation models, and adversarial red teaming to combat sophisticated invalid traffic (IVT) and emerging AI-generated fraud threats. He earned his PhD in Computer Science from the University of Notre Dame, specializing in cost-sensitive imbalanced graph classification. Saurabh is also an active researcher, serving on program committees for top-tier conferences (KDD, NeurIPS, ICML) and collaborating on open-source AI initiatives for election security in Southeast Asia. He has developed and taught courses on network science and ML applications in finance.

He is an AI Research Engineer at kakaobank's Financial Tech Lab, where he works on LLM operations, Agent systems, Retrieval system, and LLM evaluation. His research focuses on trustworthy AI in the financial domain.

She develops AI research strategies for kakaobank’s mid- to long-term R&D roadmap, with research interests in user-centric financial agent design.

He is an AI Research Engineer at KFTC, where he works on LLM and agent systems, retrieval-augmented generation, and their application to financial infrastructure. His research focuses on building reliable LLM-based systems for the financial domain.