Portrait of Eric Horvitz

Eric Horvitz

Technical Fellow and Managing Director MSR AI

Eric Horvitz’s home page can be found here.

Eric Horvitz is a technical fellow and director at Microsoft Research.  He has made contributions in areas of machine learning, perception, natural language understanding, decision making, and human-AI collaboration. His efforts and collaborations have led to fielded systems in healthcare, transportation, ecommerce, operating systems, and aerospace.  He received the Feigenbaum Prize and the Allen Newell Prize for contributions to AI.  He has been elected fellow of the National Academy of Engineering (NAE), the Association of Computing Machinery (ACM) , Association for the Advancement of AI (AAAI), and the American Academy of Arts and Sciences. He has served as president of the AAAI, and on advisory committees for the National Science Foundation, National Institutes of Health, President’s Council of Advisors on Science and Technology, DARPA, and the Allen Institute for AI.  Beyond technical work, he has pursued efforts and studies on the influences of AI on people and society, including issues around ethics, law, and safety.  He established the One Hundred Year Study on AI and served as a founder and co-chair of the Partnership on AI to Support People and Society.  Eric received PhD and MD degrees at Stanford University. More information can be found on his home page.  A list of publications can be found here.

Patient-Friendly Medical Information Displays

Established: October 5, 2016

Patients’ basic understanding of clinical events has been shown to dramatically improve patient care. Unfortunately, patients are frequently under-informed and unclear about our own hospital/clinical courses. The recent emergence of Electronic Medical Records (EMRs) and Personal Health Records (PHRs) makes vast amounts of data available to patients, but does little to help patients understand that data. Our work focuses on designing and building simplified information displays that will help patients understand our medical treatment and…

Windflow: Airplanes as Vast Sensor Network

The best available forecasts in the United States—from the federal government’s Winds Aloft program—have been based largely on data from instrumented weather balloons released twice a day, providing forecasts for 176 stations across the United States. Wind Aloft is often not accurate and may cost in time and fuel for a given flight plan. The Windflow project explores the research question could airplanes in flight be employed as a vast sensor network to determine atmospheric…

Cloud-Powered Virtual Reality

Established: June 3, 2016

We are investigating how Cloud Computing can enable next-generation Virtual Reality experiences. In The News Check out what the press has to say about our work. ProxyIBR:  Neowin  , VROOM FlashBack: Yahoo, Network World, Neowin, Phone Arena, WinBeta, MS Power User, SlashGear Kahawai: ZDNET, Neowin, ExtremeTech, Geek Irides: Neowin, VG24/7, ct magazine Outatime: Tech Crunch, The Verge, Engadget, Slashdot, PC Magazine, GameSpot, The Register, PCWorld, Gizmodo, SlashGear, Ars Technia, The Motley Fool

Dialog and Conversational Systems Research

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 of settings, such as conversational systems in apps or devices, and situated interactions in the real world. Projects Spoken Language Understanding

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 much to pay. This is part of a Microsoft Research study about how we can get regular people to do simple tasks at specific locations. This offer is only valid for people…

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 engaged in efforts in all of these areas. We focus on multiyear efforts at Microsoft Research to infer and forecast the flows of traffic. The work leverages machine learning to build services that make use…

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Task Routing for Prediction Tasks
Haoqi Zhang, Eric Horvitz, Yiling Chen, David C. Parkes, in Proceedings of the 11th International Con- ference on Autonomous Agents and Multiagent Systems (AAMAS 2012), Conitzer,Winikoff, Padgham, and van der Hoek (eds.), International Foundation for Autonomous Agents and Multiagent Systems, June 4, 2012, View abstract, Download PDF

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Automated Reasoning for Biology and Medicine
Eric Horvitz, in Advances in Computer Methods for Systematic Biology: Artificial Intelligence, Databases, and Computer Vision, Johns Hopkins University Press, 1993. Invited opening talk, Conference on AI in Systematic Biology, Napa Valley, California, September 1990. Also, Stanford CS Technical Report KSL-92-55., September 1, 1990, View abstract, Download PDF

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Integrative AI: Panel

July 27, 2015

Speakers

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

Affiliation

Microsoft Research, Microsoft, Worcester Polytechnic Institute

Integrative AI

July 27, 2015

Speakers

Dan Bohus, Eric Horvitz, and Larry Zitnick

Affiliation

Microsoft, Microsoft Research

Panel: Progress in AI: Myths, Realities, and Aspirations

July 10, 2015

Speakers

Christopher Bishop, Eric Horvitz, Fei Fei Li, Josh Tenenbaum, Michael L. Littman, and Oren Etzioni

Affiliation

Microsoft Research, Allen Institute for Artificial Intelligence, Stanford University, Brown University, Massachusetts Institute of Technology

Computational rationality

July 8, 2015

Speakers

Eric Horvitz and Josh Tenenbaum

Affiliation

Microsoft Research, Massachusetts Institute of Technology

Asia Faculty Summit 2012 Highlights

October 26, 2012

Speakers

Eric Horvitz, Hong Tan, Hsiao-Wuen Hon, Jeannette Wing, Lolan Song, and Rick Rashid

Affiliation

Microsoft Research Asia, Microsoft Research Redmond

Human Computation and Crowdsourcing

July 16, 2012

Speakers

Eric Horvitz, Luis von Ahn, Rajesh Patel, and Yiling Chen

Affiliation

Computer Science Dept, Harvard, Microsoft Research, Bing Core Relevance group

FestSchrift Session 3: Founding Microsoft Research

March 9, 2012

Speakers

Nathan Myhrvold, Linda Stone, Eric Horvitz, Jim Larus, Ed Lazowska, Peter Lee, and Xuedong Huang

Affiliation

MSR Redmond, Microsoft Research, University of Washington

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

Blast to the relevant past

Featuring this month:

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