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Strategic Thinking for Engineering Research in the Era of Artificial Intelligence

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Thematic Task Force Role: An ad hoc group of cross sector experts guide content planning to develop a report that will include actionable findings and identified research directions intended to catalyze action.

Exploratory Domains

The workshop developed key insights and major opportunities for academic, industry and government organizations answering the following questions:

  1. What are the major opportunities for engineering to lead advances in AI?
  2. What new questions can be formulated and feasibly answered to dramatically move engineering research to greater successes?
  3. What can engineering leaders do to ensure their organizations will thrive and meet their missions in the coming era of AI?

THEME OVERVIEW

Academic and industrial researchers have achieved very impressive breakthroughs in artificial intelligence (AI) in recent years. Large-scale investments in AI from governments and the private sector worldwide will likely fuel breakthrough achievements, new technologies, and new tools that potentially transform industries, businesses, governments, and educational institutions.

Engineering subfields are actively engaged in these developments. Robotics, automation, and control theory are leading the development of AI with autonomy and safety guarantees. Information theory and signal processing are also making important contributions. At the same, other fields such as civil engineering, environmental engineering, mechanical engineering, materials science, etc. are taking advantage of powerful new machine learning and big data technologies.

In view of the rapid progress in AI, it is critically important that engineering leaders in academic, industry, and government organizations are leaning forward and positioning engineering research community to play leadership roles in (1) the development of new AI technologies suited for engineering applications and imperatives as well as (2) in the use of the most powerful AI techniques to advance engineering research fields.

Host

Tuff_logo 2023

Timeline

  • September 2023
    Established
  • November 2023
    Visioning Event
  • June 2024
    View Final Report

Thematic Task Force

Chair

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Pramod P. Khargonekar

ERVA Co-Principal Investigator
Distinguished Professor of Electrical Engineering and Computer Science and Vice Chancellor for Research
University of California, Irvine
Headshot of woman with dark hair

Bea (Birgit) Braun

Principal Research Scientist, Data Science & Hybrid Modeling
Dow
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Mary (Missy) Cummings

Professor, College of Engineering and Computing
George Mason University
Director, Mason Autonomy and Robotics Center (MARC)
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Henry Jerez

Senior Vice President for AI Infrastructure, Oracle
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Vijay Kumar

Family Dean of Penn Engineering with appointments in the Departments of Mechanical Engineering and Applied Mechanics, Computer and Information Science, and Electrical and Systems Engineering
University of Pennsylvania
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Eric L. Miller

Professor of Electronics and Communicaiton Engineering
Tufts University
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William H. Sanders

Dean, Carnegie Mellon University College of Engineering
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Pascal Van Hentenryck

Director, NSF AI Institute for Advances in Optimization (AI4OPT)
A. Russell Chandler III Chair and Professor
Georgia Institute of Technology
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