Associate Professor at FDRE Technical and Vocational Training Institute, Ethiopia.
Assoc. Prof. Dr. Gurumurthy B. R. is a textile technologist with extensive academic and industry experience, currently serving at Ethiopian Technical University. With a Ph.D. in Textile Technology and over 13 years of teaching experience across India and Ethiopia, he specializes in sustainable textiles, smart materials, textile composite structures, and AI-driven textile process optimization. He is a life member of numerous professional societies including the Indian Chemical Society, Indian Society for Technical Education, and the American Association of Textile Chemists and Colorists. His research has been published in high-impact journals such as Industrial Crops and Products, International Journal of Fuzzy Systems, and Nanoworld Journal. His interdisciplinary approach connects traditional textile science with modern innovations in materials and machine learning.
Publication Profile
Scopus
Orcid
Google Scholar
Education
Dr. Gurumurthy B. R. holds a Ph.D. in Textile Technology from Visvesvaraya Technological University, Belgaum, Karnataka (2015), with a thesis focused on “Application of Artificial Neural Networks for Predictive Modeling in Selected Areas of Textiles.” He earned his M.Tech in Textile Technology from Bangalore University in 1999, and a B.Tech in Silk Technology from the same university in 1995. His educational qualifications have been credentialed by WES (Reference No: 632675).
Professional Experience
Dr. Gurumurthy has over 13 years of academic experience, with 6+ years of post-Ph.D. teaching and over 5 years as an Associate Professor. Since November 2019, he has been serving as an Associate Professor of Textile Technology at the FDRE Technical and Vocational Training Institute (Ethiopian Technical University, Addis Ababa). Previously, he held similar positions at VFSTR (Deemed to be University), NIT Jalandhar, Lovely Professional University, and other esteemed institutions. In addition to his academic roles, he has over 2 years of industry experience in textile manufacturing and coordination. His combined academic and corporate background underpins his practical and research-oriented approach to textile education.
Research Interest
Dr. Gurumurthy’s research focuses on textile composites, sustainable materials, technical textiles, predictive modeling using AI (particularly artificial neural networks), textile coloration, and smart textiles including conductive fabrics for wearable electronics. His interdisciplinary work spans the fields of fiber science, textile chemistry, and structural mechanics of textiles, with a strong emphasis on green and functional applications.
Author Metrics
- Google Scholar Citations: 192
- h-index: 10
- i10-index: 10
- Web of Science Researcher ID: Y-7956-2018
Top Noted Publication
1. Investigation and Modeling on Protective Textiles Using Artificial Neural Networks for Defense Applications
Authors: GKS Gurumurthy, B. Ramaiah, Radhalakshmi Y., Chennaiah
Journal: Materials Science and Engineering: B, Vol. 168, pp. 100–105
Year: 2010
Citations: 21
Summary:
This paper explores the use of artificial neural networks (ANNs) to model and predict the performance of protective textiles used in defense applications. It emphasizes the importance of textile behavior under extreme conditions, including ballistic impact and thermal exposure. The study shows that ANNs are effective in modeling complex relationships between textile parameters and their protective properties.
2. Developments in Nano-materials and Analysing Its Role in Fighting COVID-19
Authors: GB Ramaiah, A. Tegegne, B. Melese
Journal: Materials Today: Proceedings, Vol. 47, pp. 4357–4363
Year: 2021
Citations: 20
Summary:
This paper discusses recent developments in nanomaterials and their critical role in combating COVID-19, including applications in antiviral coatings, personal protective equipment (PPE), and drug delivery systems. The study focuses on how nanotechnology contributes to pandemic mitigation through innovative solutions in healthcare and hygiene.
3. The Effect of Stir‐Squeeze Casting Process Parameters on Mechanical Property and Density of Aluminum Matrix Composite
Authors: S. Vijayakumar, P.S. Satheesh Kumar, P. Sampath Kumar, S. Manickam, et al.
Journal: Advances in Materials Science and Engineering, 2022 (Article ID 3741718)
Citations: 18
Year: 2022
Summary:
The paper analyzes how different stir-squeeze casting process parameters influence the mechanical strength and density of aluminum matrix composites. It uses experimental data to optimize conditions for manufacturing strong, lightweight materials for aerospace and automotive applications.
4. Theoretical Analysis on Application Aspects of Smart Materials and Internet of Things (IoT) in Textile Technology
Author: GB Ramaiah
Journal: Materials Today: Proceedings, Vol. 45, pp. 4633–4638
Year: 2021
Citations: 16
Summary:
This theoretical paper explores the integration of smart materials and IoT technologies in textile engineering, such as wearable sensors, temperature control fabrics, and data-driven garment performance monitoring. It outlines futuristic applications and the transformative role of smart textiles in healthcare, sports, and defense.
5. Prediction of Fabric Compressive Properties Using Artificial Neural Networks
Author: B.R. Gurumurthy
Journal: AUTEX Research Journal, Vol. 7 (1), pp. 19–31
Year: 2007
Citations: 16
Summary:
This early study applies ANN models to predict the compressive properties of fabrics, offering an efficient alternative to experimental methods. It demonstrates how machine learning can streamline fabric design processes, enhancing performance prediction for diverse applications, especially in technical and industrial textiles.
Conclusion
Assoc. Prof. Dr. Gurumurthy B. R. is well-suited for the Best Researcher Award in the domain of Textile Materials, especially given his:
- Commitment to sustainable and smart textile innovation,
- Integration of AI with classical textile techniques,
- Multinational academic service and education,
- Research that connects science, engineering, and societal needs.
If the award prioritizes interdisciplinary innovation, global educational contributions, and practical application of research, he stands out as a strong contender.
🏆 Recommendation: Highly recommended, especially if the award recognizes contributions to both research and educational capacity-building in developing countries.