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Misam
Abbas
Staff AI Engineer
LinkedIn
Misam Abbas is a Staff AI Engineer specializing in Search and Recommendation systems and Responsible AI. Misam has varied experience at leading technology companies including LinkedIn, Dropbox, and Meta, he has made significant contributions to fairness metrics for recommender systems and built large-scale AI systems serving billions of users. At Meta, he developed sophisticated user representation models adopted across multiple product teams. At Dropbox, he led the development of their universal search capability combining semantic and lexical approaches. Currently at LinkedIn, he focuses on responsible AI frameworks for both traditional machine learning and LLM-based systems. Misam holds an MBA from London Business School and a B.Tech in Computer Science from the Indian Institute of Technology. His work focuses on building ethical AI systems and developing frameworks for measuring and improving algorithmic fairness at scale.
05 March 2025 15:20 - 15:40
Panel discussion: Highly regulated environments - optimizing generative AI systems in compliance-critical industries
Regulated sectors like financial services and healthcare face distinct challenges in adopting new innovations, where stringent compliance requirements and the risk of penalties often lead to heightened risk aversion. High-quality data is crucial for successful generative AI deployments, demanding rigorous standards and control. In this interactive session, hear from industry experts in finance and healthcare as they delve into the technical complexities and regulatory hurdles of building AI solutions within highly controlled environments.
05 March 2025 12:40 - 13:00
Panel discussion: Explainability x ethical challenges
The battle between innovation, regulation, and being first movers... Plenty is to be debated in this interactive session. Dive into the critical intersection of explainability and ethical challenges in generative AI, as our panel discusses how to balance transparency, fairness, and accountability while developing AI systems that align with ethical standards and regulatory requirements.