ACE Talk stands for Accelerate, Create, and Empower — three pillars that embody our vision to advance research and innovation across disciplines.Launched in 2022 by Microsoft Research Asia (MSRA), the ACE Talk Series provides an international platform for faculty, researchers, and emerging scholars to share…
How we build robust-by-design algorithms Heuristic algorithms power nearly every production system -- from scheduling to routing to resource allocation --- because exact solutions are intractable. Yet, when inputs deviate from the designers' base assumptions, these heuristics can collapse and perform poorly. Robusta aims to…
This explainer video unpacks the science behind paraphrasing a protein—a defining technique of Microsoft’s Paraphrase Project. Researchers discovered it is possible to use advanced open-source AI tools to reformulate toxic proteins, potentially preserving their function while disguising their form. The goal? To test whether existing…
Study information page We are a group of researchers at Microsoft Research, Northwestern University, University of Minnesota, Dartmouth College, Mental Health America and LivingWorks looking to improve AI chatbots (e.g., ChatGPT, Copilot, Claude) for users experiencing suicidal distress. The goal of this study is to…
Technology-mediated communication tools are widely used to maintain connections between older adults and their remote family members. However, challenges often arise due to differences in their life rhythms and communication preferences, such as time zones, daily routines, or preferred platforms. To address these challenges, we…
RAG (Retrieval Augmented Generation) allows LLMs (large language models) to generate better responses with external knowledge, but using more external knowledge causes higher response delay. Prior work focuses either on reducing the response delay (e.g., better scheduling of RAG queries) or on maximizing quality (e.g.,…
Polymers are a versatile class of materials with widespread industrial applications. Advanced computational tools could revolutionize their design, but their complex, multi-scale nature poses significant modeling challenges. Conventional force fields often lack the accuracy and transferability required to capture the intricate interactions governing polymer behavior.…
The widespread adoption of Large Language Models (LLMs) is driving the rapidly growing demand for large-scale computations like training and fine-tuning models. In many areas, the confidentiality of the underlying data is of critical importance to their corporate or government owners. However, securing data in…
Microsoft is a proud sponsor of SOSP 2025, the 31st Symposium on Operating Systems Principles (opens in new tab), held on October 13 – 16, 2025 at Lotte Hotel World, Seoul, Republic of Korea. The annual ACM Symposium on Operating Systems Principles is the world's…
Large language model (LLM) applications often reuse previously processed context, such as chat history and documents, which in troduces significant redundant computation. Existing LLM serving systems address such redundant computation by storing the KV caches of processed context and loading the corresponding KV cache when…
Checkpointing is a special task in the modern deep learning training process as it poses a hard tradeoff between training efficiency and reliability. Frequent checkpoints of model states can enhance resilience to random system failures, yet obtaining checkpoints must halt the training process to prevent…
Recent advances in agentic workflows have enabled the automation of tasks such as professional document generation. However, they primarily focus on textual quality, neglecting visual structure and style, which are crucial for readability and engagement. This gap arises mainly from the absence of suitable reward…
