World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
35
Citations
6693
World Ranking
8904
National Ranking
2478

Research.com Recognitions

  • 2016 - Fellow of the American Association for the Advancement of Science (AAAS)
  • 1984 - Fellow of the American Society of Mechanical Engineers

Overview

James H. Garrett is affiliated with Carnegie Mellon University in the United States. Their research spans multiple fields, with a primary focus in Computer Science and contributions to interrelated subfields such as Artificial Intelligence, Oncology, Social Psychology, Cancer Research, and Information Systems.

Their work addresses a range of main topics including:

  • AI in Service Interactions
  • Cutaneous Melanoma Detection and Management
  • Cancer Genomics and Diagnostics
  • CAR-T Cell Therapy Research
  • Social Robot Interaction and Human-Robot Interaction (HRI)
  • ICT in Developing Communities
  • Artificial Intelligence in Healthcare and Education

James H. Garrett has published several papers recently. Notable publications include:

  • "Clinical validation of droplet digital PCR assays in detecting BRAFV600-mutant circulating tumour DNA as a prognostic biomarker in patients with resected stage III melanoma receiving adjuvant therapy (COMBI-AD): a biomarker analysis from a double-blind, randomised phase 3 trial" (2025, The Lancet Oncology)
  • "Building chatbots: A guide to frameworks and platforms" (2024, AIP conference proceedings)
  • "ICE volume 44 issue 8 Cover and Front matter" (2023, Infection Control and Hospital Epidemiology)
  • "Chatbots in medical education: A study on their effectiveness as learning tool" (2024, AIP conference proceedings)
  • "Negative Testing: Automating a Safety Critical Process with Human Factors at its Core" (2024, SPE Annual Technical Conference and Exhibition)

The venues where Garrett most frequently publishes include:

  • AIP conference proceedings
  • The Lancet Oncology
  • Infection Control and Hospital Epidemiology
  • SPE Annual Technical Conference and Exhibition
  • arXiv (Cornell University)

Frequent coauthors collaborating with Garrett are:

  • Prafulla O. Bagde
  • Mahrukh M. Syeda
  • Georgina V Long
  • Victoria Atkinson
  • Mario Santinami

James H. Garrett has been recognized as a fellow by prominent scientific organizations, including:

  • Fellow of the American Association for the Advancement of Science (AAAS), 2016
  • Fellow of the American Society of Mechanical Engineers, 1984

Best Publications

  • Knowledge-Based Modeling of Material Behavior with Neural Networks

    J. Ghaboussi;J. H. Garrett;X. Wu

  • Use of neural networks in detection of structural damage

    X. Wu;J. Ghaboussi;J.H. Garrett

  • Intelligent light control using sensor networks

    Vipul Singhvi;Andreas Krause;Carlos Guestrin;James H. Garrett

  • Neural network-based screening for groundwater reclamation under uncertainty

    S. Ranjithan;J. W. Eheart;J. H. Garrett

  • Sensor andrew: large-scale campus-wide sensing and actuation

    A. Rowe;M. E. Bergeés;G. Bhatia;E. Goldman

  • Artificial Neural Networks for Civil Engineers: Fundamentals and Applications

    Nabil Kartam;Ian Flood;James H. Garrett

  • Automated defect detection for sewer pipeline inspection and condition assessment

    W. Guo;L. Soibelman;J.H. Garrett

  • Toward Data-Driven Structural Health Monitoring: Application of Machine Learning and Signal Processing to Damage Detection

    Yujie Ying;James H. Garrett;Irving J. Oppenheim;Lucio Soibelman

  • Semi-Supervised Multiresolution Classification Using Adaptive Graph Filtering With Application to Indirect Bridge Structural Health Monitoring

    Siheng Chen;Fernando Cerda;Piervincenzo Rizzo;Jacobo Bielak

  • A knowledge-based standards processor for structural component design

    James H. Garrett;Steven J. Fenves

  • Engineering applications of neural networks

    James H. Garrett;Michael P. Case;James W. Hall;Sudhakar Yerramareddy

  • Indirect structural health monitoring of a simplified laboratory-scale bridge model

    Fernando Cerda;Siheng Chen;Jacobo Bielak;James H. Garrett

  • Diagnosis algorithms for indirect structural health monitoring of a bridge model via dimensionality reduction

    Jingxiao Liu;Siheng Chen;Mario Bergés;Jacobo Bielak

  • Neural network-based vehicle detection system and method

    Darcy M. Bullock;James H. Garrett;Chris T. Hendrickson

  • Sensing and Field Data Capture for Construction and Facility Operations

    Saurabh Taneja;Burcu Akinci;James H. Garrett;Lucio Soibelman

  • Algorithms for automated generation of navigation models from building information models to support indoor map-matching

    Saurabh Taneja;Burcu Akinci;James H. Garrett;Lucio Soibelman

  • Object‐Oriented Model of Engineering Design Standards

    James H. Garrett;M. Maher Hakim

  • A framework for representing design intent

    Rajaram Ganeshan;James Garrett;Susan Finger

  • Data Fusion Approaches and Applications for Construction Engineering

    Seyed Mohsen Shahandashti;Saiedeh N. Razavi;Lucio Soibelman;Mario Berges

  • Track-monitoring from the dynamic response of an operational train

    George Lederman;Siheng Chen;James H. Garrett;Jelena Kovacevic

  • Analysis of Three Indoor Localization Technologies for Supporting Operations and Maintenance Field Tasks

    Saurabh Taneja;Asli Akcamete;Burcu Akinci;James H. Garrett

Frequent Co-Authors

Burcu Akinci
Burcu Akinci Carnegie Mellon University
Lucio Soibelman
Lucio Soibelman University of Southern California
Jacobo Bielak
Jacobo Bielak Carnegie Mellon University
Jelena Kovacevic
Jelena Kovacevic New York University
Jose M. F. Moura
Jose M. F. Moura Carnegie Mellon University
H. Scott Matthews
H. Scott Matthews Carnegie Mellon University
Chris Hendrickson
Chris Hendrickson Carnegie Mellon University
Asim Smailagic
Asim Smailagic Carnegie Mellon University
Darcy M. Bullock
Darcy M. Bullock Purdue University West Lafayette
Christiaan J. J. Paredis
Christiaan J. J. Paredis Clemson University

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

For students exploring Engineering and Technology in the USA, many related online degree and career pathway options offer flexibility and speed. A popular option is 6 week online courses, ideal for those looking to gain new skills quickly or supplement existing qualifications. These short-term courses can provide a focused introduction to technical subjects or help you catch up on prerequisites.

If you’re interested in broadening your expertise, accelerated finance degree programs and accelerated mba programs allow ambitious learners to graduate faster and advance their careers without the typical time commitment. These programs are especially useful if you aim to blend technical know-how with essential management or financial skills.

Those seeking a rapid entry into law and technology intersections may also consider fast track paralegal programs. These options help future professionals pivot their career or enhance credentials in a competitive market—all through the flexibility of online study.

Best Scientists Citing James H. Garrett

Trending Scientists