Saleema Amershi
Partner Research Manager, Microsoft AI Frontiers
About
Saleema Amershi is a Partner Research Manager at Microsoft and a founding member of AI Frontiers, Microsoft’s advanced AI research lab focused on next generation agentic AI models and systems. She leads the Magentic Team (short for “multi-agentic”), an interdisciplinary group of researchers and engineers building AI agents, multi-agent platforms, and technologies for collective intelligence.
In collaboration with partners across AI Frontiers, her team has created some of Microsoft’s most influential open-source AI technologies, including:
- AutoGen (opens in new tab), a widely-adopted multi-agent framework that became the Microsoft Agent Framework and helped shape Microsoft’s agent platform strategy.
- Magentic-One/Magentic-UI (opens in new tab), an open-source computer-use agent for enabling research in human-agent interaction and driving training data generation for Fara (opens in new tab), our open-source computer-use model series.
- MarkItDown (opens in new tab), Microsoft’s second most-starred open-source repository, enabling LLMs to understand and reason over virtually any document or content type.
Today, Saleema’s team focuses on multi-agent networks, building the foundations for AI agents to work together with people and other agents. Their work spans agent-to-agent platforms and simulation environments (Magentic Marketplace), emergent risks and behaviors in agent networks (Red-teaming a Network of Agents), benchmarks for evaluating collaborative capabilities (SocialReasoning-Bench, The Collaboration Gap (opens in new tab), SentinelBench (opens in new tab)), and post-training for collaboration and social reasoning (Strategic Negotiators (opens in new tab)).
Previously, Saleema led Microsoft’s Human-AI Experiences (HAX) team, focused on human-AI interaction and responsible AI. She is the author of the widely used Guidelines for Human-AI Interaction (opens in new tab) and HAX Toolkit (opens in new tab), whose guidance and best practices helped shape Microsoft’s Responsible AI Standard (opens in new tab). Saleema also serves on Microsoft’s advisory Committee on AI, Engineering, and Ethics, helping guide responsible AI development across the company.
Saleema holds a PhD in Computer Science & Engineering from the University of Washington’s Paul G. Allen School (opens in new tab) and an MSc in Computer Science and a BSc in Computer Science & Mathematics from the University of British Columbia (opens in new tab).
Featured Content
CES 2020: AI Requires Human-Centered Design
January 7, 2020 - Successful applications of AI require more than big data and advanced algorithms. AI technology must be developed and deployed with humans in mind. This session will explore what we truly mean by “human-centered” design and how the approach is effective.
MSR Podcast: Responsible AI with Dr. Saleema Amershi
Episode 105 | February 5, 2020 - There’s an old adage that says if you fail to plan, you plan to fail. But when it comes to AI, Dr. Saleema Amershi, a principal researcher in the Adaptive Systems and Interaction group at Microsoft Research, contends that if you plan to fail, you’re actually more likely to succeed! She’s an advocate of calling failure what it is, getting ahead of it in the AI development cycle and making end-users a part of the process. Today, Dr. Amershi talks about life at the intersection of AI and HCI and does a little AI myth-busting. She also gives us an overview of what – and who – it takes to build responsible AI systems and reveals how a personal desire to make her own life easier may make your life easier too.
The Hanselminutes Podcast: Guidelines for Human-AI Interaction
Episode 698 | August 22, 2019 - Dr. Saleema Amershi and researchers at Microsoft have published 18 guidelines for Human-AI Interaction that prescribe how an AI system should behave upon initial interaction, as the user interacts with the system, when the system is wrong, and over time. Scott talks with Dr. Amershi about the how and why of these rules and why they are so important.
Data Stories Podcast: Human-Driven Machine Learning
Episode 115 | February 20, 2018 - How should we interact with machine learning? Is there a way to better understand what machine learning systems do and how? What role can visualization play in machine learning? These are some of the questions we discuss with Saleema Amershi on the podcast this week. On the show we explore the need for interaction in machine learning and discuss some of the fascinating work Saleema has done in this space, as well as what visualization can do to make machine learning more transparent for its users.