Session Type : Opening Remarks Speakers : Friederike Niedtner, Principal Technical Research Program Manager, Microsoft Research AI Frontiers Description : Session Type : Keynote Speakers : Hoifung Poon, General Manager, Microsoft Health Futures Description : Multimodal generative AI for precision health
This talk introduces an agenda in precision health, utilizing generative AI to pretrain high-fidelity patient embeddings from multimodal, longitudinal patient journeys. This approach unlocks population-scale real-world evidence, optimizing clinical care and accelerating biomedical discovery. Session Type : Panel Discussion Speakers : Matthew Lungren, Chief Data Science Officer, Microsoft Health & Life Sciences Description : AI for precision health: Learning the language of nature and patients
This panel discussion with Microsoft researchers and external guests explores the transformative potential of generative AI in learning the language of nature and patients for precision health, from proteins to medical imaging, from electronic medical records to home health monitoring. Emphasis is placed on the end-to-end innovation cycle from foundational research to deep partnership to productization. Session Type : Talk Speakers : Marwin Segler, Principal Researcher Manager, Microsoft Research AI for Science Description : Chimera: Accurate synthesis prediction by ensembling models with diverse induction biases
This talk addresses chemical synthesis in drug discovery with a learning-to-rank framework that integrates AI-based models, significantly boosting prediction accuracy and preferred by chemists. Session Type : Talk Speakers : Jianwei Yang, Principal Researcher, Microsoft Research Redmond Description : Magma: A foundation model for multimodal AI agents
This talk introduces Magma, a new multimodal agentic foundation model designed for UI navigation in digital environments and robotics manipulation in physical settings. It covers two new techniques, Set-of-Mark and Trace-of-Mark, for action grounding and planning, and details the unified pretraining pipeline that learns agentic capabilities. Session Type : Talk Speakers : John Langford, Partner Research Manager, Microsoft Research AI Frontiers Description : Belief state transformers
This talk showcases a new transformer architecture that generates compact belief states for goal-conditioned planning, enhancing planning algorithms' efficiency and effectiveness. Session Type : Talk Speakers : Gagan Basal, Senior Researcher, Microsoft Research AI Frontiers Description : AutoGen v0.4: Reimagining the foundation of agentic AI for scale, extensibility, and robustness
This talk introduces a transformative update to the AutoGen framework that builds on user feedback and redefines modularity, stability, and flexibility to empower the next generation of agentic AI research and applications. Session Type : Talk Speakers : Pantazis Deligiannis, Principal Research Engineer, Microsoft Research FoSSE (Future of Scalable Software Engineering) Description : Using LLMs for safe low-level programming
This talk covers two technical results from ICSE'2025 on using Large Language Models (LLMs) for safe low-level programming. The results demonstrate LLMs inferring machine-checkable memory safety invariants in legacy C code, and how LLMs assist in fixing compilation errors in Rust codebases. Session Type : Closing Remarks Speakers : Friederike Niedtner, Principal Technical Research Program Manager, Microsoft Research AI Frontiers Description :

---

Session Type : Opening Remarks Speakers : Friederike Niedtner, Principal Technical Research Program Manager, Microsoft Research AI Frontiers Description : Session Type : Keynote Speakers : Hoifung Poon, General Manager, Microsoft Health Futures Description : Multimodal generative AI for precision health
This talk introduces an agenda in precision health, utilizing generative AI to pretrain high-fidelity patient embeddings from multimodal, longitudinal patient journeys. This approach unlocks population-scale real-world evidence, optimizing clinical care and accelerating biomedical discovery. Session Type : Panel Discussion Speakers : Carlo Bifulco, CMO, Providence Genomics
Matthew Lungren, Chief Data Science Officer, Microsoft Health & Life Sciences Description : AI for precision health: Learning the language of nature and patients
This panel discussion with Microsoft researchers and external guests explores the transformative potential of generative AI in learning the language of nature and patients for precision health, from proteins to medical imaging, from electronic medical records to home health monitoring. Emphasis is placed on the end-to-end innovation cycle from foundational research to deep partnership to productization. Session Type : Talk Speakers : Marwin Segler, Principal Researcher Manager, Microsoft Research AI for Science Description : Chimera: Accurate synthesis prediction by ensembling models with diverse induction biases
This talk addresses chemical synthesis in drug discovery with a learning-to-rank framework that integrates AI-based models, significantly boosting prediction accuracy and preferred by chemists. Session Type : Talk Speakers : Jianwei Yang, Principal Researcher, Microsoft Research Redmond Description : Magma: A foundation model for multimodal AI agents
This talk introduces Magma, a new multimodal agentic foundation model designed for UI navigation in digital environments and robotics manipulation in physical settings. It covers two new techniques, Set-of-Mark and Trace-of-Mark, for action grounding and planning, and details the unified pretraining pipeline that learns agentic capabilities. Session Type : Talk Speakers : John Langford, Partner Research Manager, Microsoft Research AI Frontiers Description : Belief state transformers
This talk showcases a new transformer architecture that generates compact belief states for goal-conditioned planning, enhancing planning algorithms' efficiency and effectiveness. Session Type : Talk Speakers : Gagan Basal, Senior Researcher, Microsoft Research AI Frontiers Description : AutoGen v0.4: Reimagining the foundation of agentic AI for scale, extensibility, and robustness
This talk introduces a transformative update to the AutoGen framework that builds on user feedback and redefines modularity, stability, and flexibility to empower the next generation of agentic AI research and applications. Session Type : Talk Speakers : Pantazis Deligiannis, Principal Research Engineer, Microsoft Research FoSSE (Future of Scalable Software Engineering) Description : Using LLMs for safe low-level programming
This talk covers two technical results from ICSE'2025 on using Large Language Models (LLMs) for safe low-level programming. The results demonstrate LLMs inferring machine-checkable memory safety invariants in legacy C code, and how LLMs assist in fixing compilation errors in Rust codebases. Session Type : Closing Remarks Speakers : Friederike Niedtner, Principal Technical Research Program Manager, Microsoft Research AI Frontiers Description :

---