Portrait of Eric Horvitz

Eric Horvitz

Technical Fellow/Managing Director, Microsoft Research Redmond


Eric is a Technical Fellow and the Managing Director of the Microsoft Research lab at Redmond, balancing labwide responsibilities with ongoing research on machine intelligence and on opportunities to leverage the complementarities of human and machine intelligence.

Eric’s ongoing research builds on representations of probability and utility, and centers on identifying ideal actions under uncertainty and bounded informational, computational, and cognitive resources.  Beyond curiosity-driven research on foundations of machine perception, learning, and reasoning, he is excited about building real-world systems that provide value to people, organizations, and society, working in multiple areas, including human-computer interaction, information retrieval, healthcare, transportation, operating systems, and aerospace.


Dialog and Conversational Systems Research

Established: March 14, 2014

Conversational systems interact with people through language to assist, enable, or entertain. Research at Microsoft spans dialogs that use language exclusively, or in conjunctions with additional modalities like gesture; where language is spoken or in text; and in a variety…

Spatial Crowdsourcing

Established: January 28, 2014

We are studying how we can get regular people to do simple tasks at specific locations. An example task is to take a picture of a sign at a certain location. We are interested in who to ask and how…

Predictive Analytics for Traffic

Established: September 26, 2011

Machine Learning and Intelligence for Sensing, Inferring, and Forecasting Traffic Flows Machine learning and intelligence are being applied in multiple ways to addressing difficult challenges in multiple fields, including transportation, energy, and healthcare. Research scientists at Microsoft Research have been…



























Integrative AI: Panel Link description

Integrative AI: Panel


July 27, 2015


Charles Rich, Dan Bohus, Eric Horvitz, Larry Zitnick, Lidong Zhou, and Manuela Veloso


Microsoft Research, Microsoft, Worcester Polytechnic Institute

Integrative AI Link description

Integrative AI


July 27, 2015


Dan Bohus, Eric Horvitz, and Larry Zitnick


Microsoft, Microsoft Research


The Microsoft Research home page is a starting point for browsing through projects, events, and people at the lab at Redmond, and for our sister labs in the U.S. and throughout the world.

Students may find these career reflections by computer scientists interesting and inspirational–stemming from an event that we organized to mark the 20th anniversary of Microsoft Research.

Research overview

I’ve long been curious about the computational foundations of intelligence: How do our minds work? What computational principles and architectures underly thinking and intelligent behavior? I’ve pursued answers via studies of machine perception, learning, reasoning, and decision making. Many questions remain unanswered and much research is to be done. On the way to a deeper understanding, I work to field working systems that can immediately deliver value in the world. Projects include efforts in time-critical decisions, information retrieval, healthcare, urban infrastructure, sustainability, and development–with goals of understanding how computational models perform amidst real-world complexities, and of deploying systems that deliver value to people and society. A key focus of my work has been on opportunities to leverage the complementarities of human and machine intelligence. Related interests include machine learning and decision making for crowdsourcing and human computation, information triage and alerting that takes human attention into consideration, spanning work on notification systems, surprise modeling, multitasking, and psychological studies of interruption and recovery. On the more theoretical front, I’ve been long interested in offline and real-time optimization of the expected value of computational systems under limited and varying resources. Areas of concentration in this realm include flexible or anytime computation, ideal metareasoning for guiding computation, compilation for reducing real-time deliberation, ongoing, continual computation, and the construction of bounded-optimal reasoning systems–systems that maximize the expected utility of the people they serve, given the expected costs of reasoning, the problems encountered over time, and assertions about a system’s constitution. Research in this arena includes tackling hard reasoning problems with learning and decision making methods.

Recent activities

Completed cycle of service as president and then past-president of the Association for the Advancement of Artificial Intelligence (AAAI), and remain active with AAAI strategic planning. Recently completed service as chair of the Section on Information, Computing, and Communication of the American Association for the Advancement of Science (AAAS), representing AAAS members with interests in data and computation. Serving this year on the PCAST NITR&D Working Group, NIH Advisory Committee to the Director (ACD) NLM Working Group, and National Academies Committee on Information Technology, Automation, and the Workforce. Served on the Computing Community Consortium, an organization that works to envision computing futures–and to stoke the fires of creativity within our community. As part of that effort, assisted with creating a whitepaper series for communicating the value of research on machine learning and decision support to government leaders and the public. I’ve worked with colleagues to kick off a new AAAI conference in 2013 human computation and crowdsourcing, to serve an exciting and evolving community. Fellow of the AAAI, ACM, AAAS, the American Academy of Arts and Sciences, and National Academy of Engineering (NAE), and elected to the CHI Academy.

Recent news and events