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Aditya
Gautam
Tech Lead, Machine Learning
Meta
Aditya is a seasoned Machine learning practitioner, currently working on LLM (Llama) application to enhance recommendation and ranking algorithms at scale. He has led several critical Machine learning projects in Facebook reels including user interest exploration, trend detection, quality improvement and safeguarding policy by detection violation. He played a pivotal role in mitigating misinformation on Facebook platform by pioneering effective Machine learning techniques and effectively deploying them at scale, resulting in reducing harmful content and ensuring safe user experience.With this, Aditya is also very passionate about space of AI policy and governance. He holds a master’s degree from Carnegie Mellon University and has worked in Machine learning at Google and has been a founding engineer of an AI startup at Area 120 (Google Incubator). Aditya holds a US patent and has been associated with many organizations including IEEE (Senior Member), Integrity Institute and ACM.
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15 April 2026 13:50 - 14:20
Failure, recovery, and containment in autonomous systems
Autonomous systems rarely fail cleanly. Instead, they stall mid-trajectory, loop on partial goals, or leave systems in inconsistent states after taking irreversible actions. These failures are difficult to detect, harder to recover from, and often only surface once real users and real infrastructure are involved. This session examines how engineering teams design for failure in autonomous systems operating in production. We’ll discuss how teams detect and contain failures as they happen, recover safely without losing intent or corrupting state, and limit blast radius when agents interact with multiple tools and services. The focus is on recovery as a first-class systems concern, rather than an afterthought once autonomy is already in place.