World's Best Scientists 2026 revealed!

D-Index & Metrics

Engineering and Technology

D-Index
40
Citations
8614
World Ranking
7200
National Ranking
1966

Overview

Linkan Bian is affiliated with Mississippi State University in the United States. Their research primarily falls within the broad field of Engineering, with a significant focus on Mechanical Engineering and related subfields.

The scientist's work spans several specialized areas including:

  • Mechanical Engineering
  • Industrial and Manufacturing Engineering
  • Automotive Engineering
  • Mechanics of Materials
  • Radiology, Nuclear Medicine and Imaging

Linkan Bian's research topics cover a range of applied and theoretical subjects. Main topics include:

  • Additive Manufacturing Materials and Processes
  • Additive Manufacturing and 3D Printing Technologies
  • Welding Techniques and Residual Stresses
  • Industrial Vision Systems and Defect Detection
  • Radiomics and Machine Learning in Medical Imaging
  • Head and Neck Cancer Studies
  • Thermography and Photoacoustic Techniques

This body of work is reflected in publications across various specialized journals. The frequent publication venues where Linkan Bian's work appears include:

  • Journal of Manufacturing Science and Engineering
  • Journal of Manufacturing Processes
  • IEEE Access
  • Manufacturing Letters
  • International Journal of Services and Operations Management

Examples of recent papers authored or co-authored by Linkan Bian are:

  • "Deep Learning-Based Data Fusion Method for In Situ Porosity Detection in Laser-Based Additive Manufacturing," 2020, Journal of Manufacturing Science and Engineering
  • "Drone routing and optimization for post-disaster inspection," 2021, Computers & Industrial Engineering
  • "Fatigue-life prediction of additively manufactured material: Effects of heat treatment and build orientation," 2020, Fatigue & Fracture of Engineering Materials & Structures
  • "Effects of crack orientation and heat treatment on fatigue-crack-growth behavior of AM 17-4 PH stainless steel," 2020, Engineering Fracture Mechanics
  • "DLAM: Deep Learning Based Real-Time Porosity Prediction for Additive Manufacturing Using Thermal Images of the Melt Pool," 2021, IEEE Access

The scientist frequently collaborates with a network of co-authors, including:

  • Wenmeng Tian
  • Shenghan Guo
  • Christian Zamiela
  • Mahathir Mohammad Bappy
  • Haley Doude

Best Publications

  • An overview of Direct Laser Deposition for additive manufacturing; Part I: Transport phenomena, modeling and diagnostics

    Scott M. Thompson;Linkan Bian;Nima Shamsaei;Aref Yadollahi

  • An overview of Direct Laser Deposition for additive manufacturing; Part II: Mechanical behavior, process parameter optimization and control

    Nima Shamsaei;Aref Yadollahi;Linkan Bian;Scott M. Thompson

  • Effects of building orientation and heat treatment on fatigue behavior of selective laser melted 17-4 PH stainless steel

    Aref Yadollahi;Nima Shamsaei;Scott M. Thompson;Alaa Elwany

  • Porosity prediction: Supervised-learning of thermal history for direct laser deposition

    Mojtaba Khanzadeh;Sudipta Chowdhury;Mohammad Marufuzzaman;Mark A. Tschopp

  • Drones for disaster response and relief operations: A continuous approximation model

    Sudipta Chowdhury;Adindu Emelogu;Mohammad Marufuzzaman;Sarah G. Nurre

  • In-situ monitoring of melt pool images for porosity prediction in directed energy deposition processes

    Mojtaba Khanzadeh;Sudipta Chowdhury;Mark A. Tschopp;Haley R. Doude

  • Additive manufacturing of heat exchangers: A case study on a multi-layered Ti–6Al–4V oscillating heat pipe

    Scott M. Thompson;Zachary S. Aspin;Nima Shamsaei;Alaa Elwany

  • Deep Learning for Distortion Prediction in Laser-Based Additive Manufacturing using Big Data

    Jack Francis;Linkan Bian

  • Mechanical properties and microstructural characterization of selective laser melted 17-4 PH stainless steel

    Mohamad Mahmoudi;Alaa Elwany;Aref Yadollahi;Scott M. Thompson

  • Mechanical Properties and Microstructural Features of Direct Laser-Deposited Ti-6Al-4V

    Linkan Bian;Scott M. Thompson;Nima Shamsaei

  • Toward the digital twin of additive manufacturing: Integrating thermal simulations, sensing, and analytics to detect process faults

    Aniruddha Gaikwad;Reza Yavari;Mohammad Montazeri;Kevin Cole

  • Additive manufacturing of biomedical implants: A feasibility assessment via supply-chain cost analysis

    Adindu Emelogu;Mohammad Marufuzzaman;Scott M. Thompson;Nima Shamsaei

  • Botnet detection using graph-based feature clustering

    Sudipta Chowdhury;Mojtaba Khanzadeh;Ravi Akula;Fangyan Zhang

  • Stochastic modeling and real-time prognostics for multi-component systems with degradation rate interactions

    Linkan Bian;Nagi Gebraeel

  • Quantifying Geometric Accuracy With Unsupervised Machine Learning: Using Self-Organizing Map on Fused Filament Fabrication Additive Manufacturing Parts

    Mojtaba Khanzadeh;Prahalada Rao;Ruholla Jafari-Marandi;Brian K. Smith

  • Dual process monitoring of metal-based additive manufacturing using tensor decomposition of thermal image streams

    Mojtaba Khanzadeh;Wenmeng Tian;Aref Yadollahi;Haley R. Doude

  • An exploratory investigation of Additively Manufactured Product life cycle sustainability assessment

    Junfeng Ma;James D. Harstvedt;Daniel Dunaway;Linkan Bian

  • A two-stage chance-constrained stochastic programming model for a bio-fuel supply chain network

    Abdul Quddus;Sudipta Chowdhury;Mohammad Marufuzzaman;Fei Yu

  • From in-situ monitoring toward high-throughput process control: cost-driven decision-making framework for laser-based additive manufacturing

    Ruholla Jafari-Marandi;Mojtaba Khanzadeh;Wenmeng Tian;Brian Smith

  • Deep Learning-Based Data Fusion Method for In-Situ Porosity Detection in Laser-Based Additive Manufacturing

    Qi Tian;Qi Tian;Shenghan Guo;Erika Melder;Linkan Bian

  • Degradation modeling for real-time estimation of residual lifetimes in dynamic environments

    Linkan Bian;Nagi Gebraeel;Jeffrey P. Kharoufeh

Frequent Co-Authors

Nima Shamsaei
Nima Shamsaei Auburn University
Mark A. Tschopp
Mark A. Tschopp United States Army Research Laboratory
James C. Newman
James C. Newman Mississippi State University
Shuai Shao
Shuai Shao Auburn University
Jianjun Shi
Jianjun Shi Georgia Institute of Technology
Xiaopeng Li
Xiaopeng Li University of Wisconsin–Madison
Yaguo Lei
Yaguo Lei Xi'an Jiaotong University
J. Edward Swan
J. Edward Swan Mississippi State University

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