Ich Long Ngo | Computational Methods | Research Excellence Award

Research Excellence Award

Ich Long Ngo
Ich Long Ngo
Affiliation Hanoi University of Science and Technology
Country Vietnam
Scopus ID 56465015200
Documents 38
Citations 941
h-index 18
Subject Area Computational Methods
Event Global Particle Physics Excellence Awards

Ich Long Ngo is a Vietnamese researcher and associate professor affiliated with Hanoi University of Science and Technology. His academic work primarily focuses on computational methods, heat transfer engineering, thermal conductivity enhancement, microfluidics, electrohydrodynamic systems, and polymer composite materials. His publication portfolio includes contributions to internationally indexed journals in thermal sciences, fluid mechanics, and mechanical engineering.[1] His research activities also encompass electro-conjugate fluid micropumps, geothermal management systems, and computational optimization for engineering applications.[2]

Abstract

The Research Excellence Award recognition for Ich Long Ngo reflects his sustained scholarly contributions in computational methods and thermal-fluid engineering. His academic output includes investigations into polymer composites, microfluidic systems, electrohydrodynamic micropumps, and thermal conductivity optimization. Through computational modeling, numerical simulations, and engineering experimentation, his work has contributed to the development of predictive correlations and optimized engineering designs for thermal management and fluid dynamics systems.[3] His publication record demonstrates interdisciplinary engagement across mechanical engineering, computational fluid dynamics, and materials science.[4]

Keywords

Computational Methods, Thermal Conductivity, Microfluidics, Electrohydrodynamic Systems, Heat Transfer, Polymer Composites, Fluid Engineering, Thermal Sciences, Mechanical Engineering, Numerical Simulation

Introduction

Computational engineering methods have become central to modern developments in heat transfer, energy systems, and microfluidic technologies. Researchers working in this field contribute to both theoretical modeling and practical engineering optimization. Ich Long Ngo has developed research activities that combine finite element analysis, numerical simulation, and experimental validation to investigate thermal conductivity enhancement, electro-conjugate fluid systems, and fluidic transport phenomena.[5]

His research has been published in journals including Physics of Fluids, International Journal of Heat and Mass Transfer, Applied Thermal Engineering, and Journal of Fluids Engineering. These studies contribute to understanding the transport behavior of fluids, optimization of composite materials, and development of engineering correlations applicable to industrial and energy systems.[6]

Research Profile

According to ORCID and Scopus records, Ich Long Ngo has served as Associate Professor and Senior Lecturer in Mechanical Engineering at Hanoi University of Science and Technology since 2009.[7] He obtained his Doctor of Philosophy degree in Mechanical Engineering from Yeungnam University, Republic of Korea, and completed his Master of Science degree at Changwon National University.[8]

His research profile includes publications addressing heat transfer optimization, polymer composite conductivity, microfluidic droplet formation, electro-conjugate fluid micropumps, and geothermal engineering systems. His interdisciplinary approach integrates computational analysis with experimentally validated engineering methodologies.[9]

  • Associate Professor at Hanoi University of Science and Technology
  • Research specialization in thermal-fluid engineering and computational methods
  • Author and co-author of peer-reviewed engineering publications
  • Contributor to electro-conjugate fluid micropump research initiatives
  • Active participant in computational heat transfer and microfluidic studies

Research Contributions

A major component of Ngo’s research contributions involves predictive modeling for thermal conductivity enhancement in heterogeneous composite systems. His studies developed generalized correlations and numerical models for polymer composites reinforced with hybrid fillers and nanofillers.[10]

His investigations into electro-conjugate fluid micropumps and microfluidic devices contributed to understanding flow optimization and electrode geometries for electrohydrodynamic applications.[11] These studies explored fluidic performance enhancement using hydrodynamic-shaped electrodes and computational optimization strategies.

Ngo has also contributed to geothermal management systems and LED thermal management applications through computational and experimental approaches.[12] His work on generalized engineering correlations supports engineering prediction methodologies applicable to thermal sciences and heat transfer analysis.

  • Thermal conductivity prediction models for polymer composites
  • Microfluidic droplet dynamics and flow-focusing systems
  • Electro-conjugate fluid micropump optimization
  • Finite element analysis for thermal management systems
  • Computational fluid dynamics and wake transition studies
  • Geothermal heat exchanger design optimization

Publications

Selected publications associated with Ich Long Ngo include peer-reviewed journal articles in thermal sciences, fluid engineering, and computational modeling.[13]

  1. “A Comprehensive Study on Improving the Electrohydrodynamic Performance of Electroconjugate Fluid Micropumps Using Hydrodynamic-Shaped Electrodes.” Journal of Fluids Engineering (2026).
    DOI: https://doi.org/10.1115/1.4070397
  2. “Achieving High Power and Energy Efficiency for Microfluidic Fuel Cells with Flow-through Porous Electrodes.” International Journal of Precision Engineering and Manufacturing-Green Technology (2026).
    DOI: https://doi.org/10.1007/s40684-025-00822-0
  3. “A generalized correlation for predicting microdroplet sizes in a squeezer T-junction microfluidic device.” Physics of Fluids (2025).
    DOI: https://doi.org/10.1063/5.0294584
  4. “A new design of electro-conjugate fluid micropumps with Venturi and teardrop-shaped electrodes.” Physics of Fluids (2024).
    DOI: https://doi.org/10.1063/5.0221203
  5. “Experimental study on thermal management of surface mount device–LED chips.” Applied Thermal Engineering (2023).
    DOI: https://doi.org/10.1016/j.applthermaleng.2022.119846

Research Impact

The scholarly impact of Ich Long Ngo’s work is reflected through citations, journal visibility, and interdisciplinary collaboration in computational engineering and thermal sciences.[14] His studies on thermal conductivity prediction models and electrohydrodynamic systems contribute to ongoing research in efficient thermal management and microfluidic optimization.

His publications have appeared in internationally recognized engineering journals, supporting academic discussions in heat transfer engineering, polymer composites, and fluid mechanics.[15] His contributions to computational analysis and predictive correlations continue to support engineering modeling methodologies in applied sciences.

Award Suitability

Ich Long Ngo’s research profile demonstrates sustained engagement in computational methods and thermal-fluid engineering research. His publication record, interdisciplinary research activities, and contributions to numerical modeling align with the objectives commonly associated with research excellence recognition programs.[16]

The combination of experimental and computational methodologies present in his work illustrates academic contributions relevant to energy systems, microfluidic technologies, and thermal management engineering. These characteristics support consideration for professional recognition within computational engineering and applied mechanics disciplines.

Conclusion

Ich Long Ngo has contributed to research areas involving computational methods, thermal sciences, and fluid engineering through publications addressing thermal conductivity enhancement, microfluidics, and electro-conjugate fluid systems. His academic activities at Hanoi University of Science and Technology and his publication portfolio in international engineering journals demonstrate continued participation in computational and applied engineering research.[17]

References

  1. Elsevier. (n.d.). Scopus author details: Ich Long Ngo, Author ID 56465015200. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=56465015200
  2. ORCID. (n.d.). Ich Long Ngo ORCID Profile.
    https://orcid.org/0000-0003-2406-5725
  3. Ngo, I.L., et al. (2026). A Comprehensive Study on Improving the Electrohydrodynamic Performance of Electroconjugate Fluid Micropumps Using Hydrodynamic-Shaped Electrodes. Journal of Fluids Engineering.
    https://doi.org/10.1115/1.4070397
  4. Ngo, I.L., et al. (2026). Achieving High Power and Energy Efficiency for Microfluidic Fuel Cells with Flow-through Porous Electrodes.
    https://doi.org/10.1007/s40684-025-00822-0
  5. Ngo, I.L., et al. (2025). A generalized correlation for predicting microdroplet sizes in a squeezer T-junction microfluidic device. Physics of Fluids.
    https://doi.org/10.1063/5.0294584
  6. Ngo, I.L., et al. (2024). A new design of electro-conjugate fluid micropumps with Venturi and teardrop-shaped electrodes. Physics of Fluids.
    https://doi.org/10.1063/5.0221203
  7. ORCID. (n.d.). Employment details of Ich Long Ngo.
    https://orcid.org/0000-0003-2406-5725
  8. ORCID. (n.d.). Education and qualifications of Ich Long Ngo.
    https://orcid.org/0000-0003-2406-5725
  9. Elsevier. (n.d.). Research publications and citation profile.
    https://www.scopus.com/authid/detail.uri?authorId=56465015200
  10. Ngo, I.L.; Byon, C. (2019). An investigation on effective thermal conductivity of hybrid-filler polymer composites.
    https://doi.org/10.1016/j.ijheatmasstransfer.2019.118605
  11. Ngo, I.L.; Lai, T.K. (2026). Electroconjugate fluid micropump optimization research.
    https://doi.org/10.1115/1.4070397
  12. Ngo, I.L.; Ngo, V.H. (2022). A new design of ground heat exchanger with insulation plate for effectively geothermal management.
    https://doi.org/10.1016/j.geothermics.2022.102512
  13. Elsevier and Crossref indexed journal publications associated with Ich Long Ngo.
    https://www.scopus.com/authid/detail.uri?authorId=56465015200
  14. Scopus Preview. (2026). Citation metrics and scholarly indicators.
    https://www.scopus.com/authid/detail.uri?authorId=56465015200
  15. ORCID and Crossref publication metadata records.
    https://orcid.org/0000-0003-2406-5725
  16. Global Tech Excellence. (2026). Global Particle Physics Excellence Awards.

    Global Tech Excellence Awards


  17. Compiled academic profile data from Scopus and ORCID records for Ich Long Ngo.
    https://orcid.org/0000-0003-2406-5725

Mohsen Khatibinia | Structural Control | Best Researcher Award

Assoc. Prof. Dr. Mohsen Khatibinia | Structural Control | Best Researcher Award

Civil Engineering at University of Birjand, Iran

Mohsen Khatibinia, Ph.D., is an Associate Professor of Civil Engineering at Shahid Bahonar University of Kerman, Iran. With a robust academic background, he has contributed significantly to the field of structural engineering, particularly in optimizing structures for earthquake resilience. His research integrates computational intelligence methods with advanced structural analysis, focusing on performance-based design and soil-structure interaction. Dr. Khatibinia is an experienced educator and a skilled user of advanced engineering software.

Professional Profile

Education

  • Ph.D. in Civil Engineering (Structural Engineering)
    Shahid Bahonar University of Kerman, Iran (2006–2013)
    Dissertation focused on reliability-based optimization of reinforced concrete structures with soil-structure interaction.
  • M.Sc. in Civil Engineering (Structural Engineering)
    Shahid Bahonar University of Kerman, Iran (2002–2004)
    Thesis: Optimal design of space structures using genetic algorithms.
  • B.Sc. in Civil Engineering
    University of Sistan and Baluchestan, Zahedan, Iran (1998–2002).

Professional Experience

Associate Professor, Shahid Bahonar University of Kerman, Iran
Mohsen Khatibinia has extensive academic experience, specializing in teaching undergraduate and graduate courses such as Structural Analysis, Theory of Elasticity, Advanced Engineering Mathematics, and Stability of Structures.

  • Expertise in computational tools including FORTRAN, MATLAB, SAP, ETABS, SAFE, Ansys, and OpenSees.
  • Proficient in developing optimization algorithms and conducting numerical simulations for structural engineering applications.

Research Interest

  • Structural optimization for earthquake-resistant design.
  • Soil-structure interaction and performance-based design.
  • Application of soft computing methods (e.g., genetic algorithms, particle swarm optimization, gravitational search algorithms, hybrid optimization algorithms, fuzzy logic, and neural networks) in structural and earthquake engineering.
  • Seismic reliability assessment and optimization of reinforced concrete and steel structures.

Author Metric

  • Published 12 peer-reviewed journal articles in prestigious journals such as Reliability Engineering & System Safety, Journal of Sound and Vibration, and Engineering Optimization.
  • Presented research at 16 international and national conferences, highlighting advancements in structural and earthquake engineering.
  • Expertise in developing hybrid computational models, with numerous citations in domains of structural optimization and earthquake engineering.

Publications Top Noted

1. Truss Optimization on Shape and Sizing with Frequency Constraints Based on Orthogonal Multi-Gravitational Search Algorithm

  • Authors: m. khatibinia, s.s. naseralavi
  • Journal: Journal of Sound and Vibration, Volume 333, Issue 24, Pages 6349-6369, 2014
  • Citations: 112
  • Abstract:
    This paper introduces an Orthogonal Multi-Gravitational Search Algorithm (OMGSA) for optimizing truss structures in terms of shape and size while satisfying frequency constraints. The approach integrates orthogonal learning and multi-agent search to enhance solution accuracy and convergence speed. The method’s effectiveness is demonstrated through benchmark problems and comparison with existing algorithms.

2. A Hybrid Approach Based on an Improved Gravitational Search Algorithm and Orthogonal Crossover for Optimal Shape Design of Concrete Gravity Dams

  • Authors: m. khatibinia, s. khosravi
  • Journal: Applied Soft Computing, Volume 16, Pages 223-233, 2014
  • Citations: 99
  • Abstract:
    This research presents a hybrid optimization technique combining an Improved Gravitational Search Algorithm (IGSA) with Orthogonal Crossover for the shape optimization of concrete gravity dams. The hybrid method addresses computational challenges in design optimization, yielding high-quality solutions with improved convergence efficiency.

3. RETRACTED: Shear Behaviour of Concrete Beams with Recycled Aggregate and Steel Fibres

  • Authors: h.r. chaboki, m. ghalehnovi, a. karimipour, j. de brito, m. khatibinia
  • Journal: Construction and Building Materials, Volume 204, Pages 809-827, 2019
  • Citations: 95
  • Abstract:
    (Retracted) The study initially examined the shear behavior of concrete beams incorporating recycled aggregates and steel fibers, aiming to explore their structural and sustainability benefits. However, the paper has been retracted, and further details are unavailable or unreliable.

4. Optimizing Parameters of Tuned Mass Damper Subjected to Critical Earthquake

  • Authors: r. kamgar, p. samea, m. khatibinia
  • Journal: The Structural Design of Tall and Special Buildings, Volume 27, Issue 7, Article e1460, 2018
  • Citations: 92
  • Abstract:
    This paper focuses on optimizing the parameters of Tuned Mass Dampers (TMDs) to enhance their performance under critical seismic events. The study utilizes advanced optimization techniques to achieve an optimal balance between cost and efficiency, improving the structural stability of tall buildings.

5. Seismic Reliability Assessment of RC Structures Including Soil–Structure Interaction Using Wavelet Weighted Least Squares Support Vector Machine

  • Authors: m. khatibinia, m.j. fadaee, j. salajegheh, e. salajegheh
  • Journal: Reliability Engineering & System Safety, Volume 110, Pages 22-33, 2013
  • Citations: 92
  • Abstract:
    This study proposes a novel approach using the Wavelet Weighted Least Squares Support Vector Machine (WLS-SVM) model for seismic reliability analysis of reinforced concrete (RC) structures, incorporating the effects of soil-structure interaction (SSI). The method offers a computationally efficient way to assess structural reliability under seismic loading conditions.

Conclusion

Dr. Mohsen Khatibinia is a strong candidate for the Best Researcher Award due to his impactful contributions to structural engineering, particularly in earthquake-resilient design and optimization. His innovative application of computational intelligence and hybrid optimization techniques highlights his expertise and commitment to advancing the field. While addressing the retraction and expanding his collaborative and publication scope could enhance his profile, his achievements make him a deserving nominee for this prestigious recognition.