Adel Alaeddini Ph.D.

Adel Alaeddini

Adel Alaeddini, Ph.D.

O'Donnell Foundation Professor
Professor of Mechanical Engineering
Co-Executive Director of Center for Digital and Human-Augmented Manufacturing (CDHAM)
Professor of Operation Research and Engineering Management (by Courtesy)
Professor of Computer Science (by Courtesy)

Room #301-I, J. Lindsay Embrey Engineering Building, Mechanical Engineering Department

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Education

  • Post Doc, University of Michigan

  • Ph.D., Wayne State University

  • Ph.D., Iran University of Science and Technology, Tehran, Iran

Biography

Dr. Adel Alaeddini holds the O'Donnell Foundation Professorship in Mechanical Engineering and serves as the Executive Director of Research Innovation at the Center for Digital and Human-Augmented Manufacturing (CDHAM) at 91制片廠合集 (SMU). His research, inspired by the principles of physics and human expertise, integrates theoretical and applied aspects of artificial intelligence and machine learning within Mechanical Engineering. His work spans diverse applications in Advanced Manufacturing, Healthcare, and Energy.  Dr. Alaeddini’s research endeavors are marked by numerous grants and awards, totaling near $8M, including DOD, DOE, NSF, NIH, VA, DHS, and USDA among others. He has contributed to over 50 peer-reviewed publications in venues such as IISE Transactions, POMS, and Energy. Dr. Alaeddini is an Associate Editor of the Journal of Applied Statistics, Healthcare Management Science, and IISE Transactions on Healthcare Systems Engineering. He is also currently serving as the Technical Vice President of IISE.

Honors and Awards

  • Summer Faculty Fellowship (2021, 2022, 2023)
    Office of Naval Research (ONR)

  • Best Poster Award (2019)
    Quality Control and Reliability Engineering (QCRE) Track
    Institute of Industrial & Systems Engineering (IISE) Annual Conference, Orlando, FL

  • Young Investigator Award (2016)
    Air Force Office of Scientific Research (AFOSR)

  • Summer Faculty Fellowship (2016)
    Air Force Office of Scientific Research (AFOSR)

  • Pierskalla Competition - Health Applications Society- Finalist (2010)
    Institute for Operations Research and Management Sciences (INFORMS) Annual Conference, Austin, TX 

  • Best Student Paper Award (2009)
    Quality Control and Reliability Engineering (QCRE) Track
    Industrial Engineering Research Conference (IERC), Cancun, Mexico

  • Selected Paper (2007)
    International Fuzzy Systems Association (IFSA) World Congress, Cancun, Mexico 

     

Research

  • Physics-Inspired Machine Learning for Engineering Prognosis and Discovery
  • Human-Augmented Control and Optimization of Complex Systems
  • Industry 5.0-Driven Multi-Stream Sensor Data Modeling, Analytics, and Control
  • Sample-Efficient Learning and Optimization of Black-Box Functions
  • Generative AI-Enhanced Digital Twins for Collaborative Design, Strategic Planning, and Optimization
  • Deep Graph Analytics for Unraveling Complex System Dynamics
     

Recent Publications

  • B Siddiqui, A Alaeddini, D Zhu, Structured segment rescaling with Gaussian processes for parameter efficient ConvNets, Journal of Systems Architecture, 2024, 103246

  • Carolina Ramirez-Tamayo, Syed Hasib Akhter Faruqui, Stanford Martinez, Angel Brisco, Nicholas Czarnek, Adel Alaeddini, Jeffrey R Mock, Edward J Golob, Kal L Clark, Incorporation of Eye Tracking and Gaze Feedback to Characterize and Improve Radiologist Search Patterns of Chest X-Rays: A Randomized Controlled Clinical Trial, Journal of the American College of Radiology, 2024, 21 (6), 942-946

  • JC Rico, A Alaeddini, SHS Faruqui, SP Fisher-Hoch, JB Mccormick,  A Laplacian regularized graph neural network for predictive modeling of multiple chronic conditions. Computer Methods and Programs in Biomedicine, 2024, 247, 108058.

  • K Keith, KK Castillo-Villar, A Alaeddini, Machine Learning-based Problem Space Reduction in Stochastic Programming Models: An Application in Biofuel Supply Chain Network Design. 2024, IEEE Access

  • HK Koodiani, E Jafari, A Majlesi, M Shahin, A Matamoros, A Alaeddini, Machine learning tools to improve nonlinear modeling parameters of RC columns, Journal of Building Engineering, 2023 84, 108492

 

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