David Guirguis, Ph.D.

Assistant Research Professor of Mechanical Engineering

Department

Mechanical Engineering

Email

dguirguis@mail.smu.edu

Website

Dr. Guirguis is an Assistant Research Professor at the Department of Mechanical Engineering and the Center for Digital and Human-Augmented Manufacturing (CDHAM), where he manages the Additive Intelligence Laboratory. He has authored more than 15 publications in top venues, including Nature Communications and IEEE Transactions, and holds a patent in the field of additive manufacturing. He received his Ph.D. in Machine Learning-Enabled Metal Additive Manufacturing from Carnegie Mellon University and his M.A.Sc. in Mechanical and Industrial Engineering from the University of Toronto.

Before joining 精东传媒, Dr. Guirguis was a Postdoctoral Associate at the Carnegie Mellon University Next Manufacturing Center and a Swartz Innovation Fellow. He also held research appointments at the University of Waterloo as a Research Associate and at the University of Toronto as a Visiting Researcher. In industry, he worked as a Senior Engineer at CleaResult, PA, and as a Mechanical Design Engineer with Trimble, Inc., Applanix in ON, Canada.

Dr. Guirguis’ research focuses on Generative Design and Process Development for Metal Additive Manufacturing through Artificial Intelligence. He has been recognized as a Leading Innovator by MIT Technology Review’s MENA List, was selected for the 2023 Rising Stars Workshop in Materials Science and Engineering, and has received multiple graduate research awards at international conferences, including the Materials Science & Technology (MS&T) conference.

Education

Post Doc, Carnegie Mellon University
Ph.D., Carnegie Mellon University
M.A.Sc., University of Toronto
B.Sc., University of the District of Columbia

Research

  • Generative Design
  • Design for Additive Manufacturing
  • Metal Additive manufacturing
  • Thermal Management
  • Renewable Energy

Publications

  • Guirguis D., Tucker C., Beuth J., 2024, "Accelerating Process Development for 3D Printing of New Metal Alloys,” Nature Communications 15: 582
  • Guirguis D., Tucker C., Beuth J., 2024, "Machine learning for real-time detection of local heat accumulation in metal additive manufacturing," Materials & Design 241: 112933
  • Guirguis D., Aulig N., Picelli R., Zhu B., Olhofer M., Vicente W., Iorio F., Matusik W., Coello C.A.C., Saitou K. 2020, "Evolutionary Black-box Topology Optimization: Challenges and Promises," IEEE Transactions on Evolutionary Computation 24 (4):613-633.
  • Guirguis D., Romero D., Amon C., 2016, "Toward efficient optimization of wind farm layouts: utilizing exact gradient information," Applied Energy 179:110-123.
  • Guirguis D., Hamza K., Aly M., Saitou, K., 2015, "Multi-objective topology optimization of multi-component continuum structures via a Kriging-interpolated level set approach," Structural and Multidisciplinary Optimization 51 (3): 733-748.

Honors and Awards

  • Swartz Innovation Fellowship (2023- 2024) CMU Swartz Center for Entrepreneurship
  • Rising Stars in Materials Science and Engineering (2023) CMU – MIT - Stanford
  • Innovators Under 35 List, MENA region (2022) MIT Technology Review
  • Second place, Graduate competition (2022) Materials Science & Technology (MS&T) Conference
  • MIE Graduate Fellowship (2014-2016) University of Toronto
A portrait photo of 精东传媒 Lyle faculty David Guirguis, Ph.D.