Luis Pérez Domínguez | Methaheuristic and Multicriteria | Best Researcher Award

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Prof. Dr. Luis Pérez Domínguez | Methaheuristic and Multicriteria | Best Researcher Award

UNIVERSIDAD AUTONOMA DE CIUDAD JUAREZ | Mexico

Professor Luis Asunción Pérez-Dominguez, a distinguished academic and researcher in industrial engineering, holds a B.Sc. in Industrial Engineering from Instituto Tecnológico de Villahermosa, Tabasco, México, an M.Sc. in Industrial Engineering from Instituto Tecnológico de Ciudad Juárez, Chihuahua, México, and a Ph.D. in the Science of Engineering from the Autonomous University of Ciudad Juárez, Chihuahua, México. Currently serving as a professor in research at the Universidad Autónoma de Ciudad Juárez, Dr. Pérez-Dominguez has dedicated his career to advancing knowledge and practice in multiple-criteria decision making, fuzzy set applications, and the implementation of continuous improvement tools within the manufacturing sector. His work bridges theoretical innovation and practical applications, focusing on improving efficiency, precision, and decision-making processes in industrial environments. Dr. Pérez-Dominguez is actively engaged with professional communities as a member of the Canadian Operational Research Society (CORS) and the Society for Industrial and Applied Mathematics (SIAM), demonstrating his commitment to global research standards and collaborative scientific advancement. Over his academic tenure, he has contributed numerous high-quality publications, providing insights into optimization, decision-making frameworks, and advanced analytical methodologies. He also emphasizes mentorship, supervising graduate and postgraduate research projects while fostering innovation among students and colleagues. His research consistently seeks to integrate modern computational methods, fuzzy logic principles, and multi-criteria evaluation techniques to address complex industrial problems. With a strong emphasis on continuous improvement, Dr. Pérez-Dominguez’s work empowers organizations to enhance operational efficiency, make informed strategic decisions, and adopt evidence-based methodologies in production and management. By combining rigorous academic research with practical industry insights, he has established himself as a leading authority in industrial engineering, known for translating complex concepts into actionable solutions for manufacturing systems, intelligent decision support, and optimization of industrial processes, positioning him as a highly influential figure in his field.

Featured Publications:

Pérez-Domínguez, L., Rodríguez-Picón, L. A., Alvarado-Iniesta, A., … MOORA under Pythagorean Fuzzy Set for Multiple Criteria Decision Making. Complexity, 134.

Ramírez-Ochoa, D. D., Pérez-Domínguez, L. A., Martínez-Gómez, E. A., … PSO, a swarm intelligence-based evolutionary algorithm as a decision-making strategy: A review. Symmetry, 14(3), 455.

Villagran-Vizcarra, D. C., Luviano-Cruz, D., Pérez-Domínguez, L. A., … Applications analyses, challenges and development of augmented reality in education, industry, marketing, medicine, and entertainment. Applied Sciences, 13(5), 2766.

Pérez-Domínguez, L., Alvarado-Iniesta, A., Rodríguez-Borbón, I., … Intuitionistic fuzzy MOORA for supplier selection. Dyna, 82(191), 34–41.

Garcia Aguirre, P. A., Perez-Dominguez, L., Luviano-Cruz, D., … PFDA-FMEA, an integrated method improving FMEA assessment in product design. Applied Sciences, 11(4), 1406.

Contreras-Masse, R., Ochoa-Zezzatti, A., García, V., Pérez-Dominguez, L., … Implementing a novel use of multicriteria decision analysis to select IIoT platforms for smart manufacturing. Symmetry, 12(3), 368.

Bulent Koc | Digital Lean System | Best Researcher Award

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Dr. Bulent Koc | Digital Lean System | Best Researcher Award

Researcher | Istanbul Technical University | Turkey

Dr. Bulent Koc is a Ph.D. candidate in Textile Engineering at Istanbul Technical University with more than two decades of experience in the apparel and textile industry. His expertise lies in integrating lean production principles with digital transformation strategies to enhance efficiency and sustainability in garment manufacturing. Throughout his career, he has worked in diverse roles, from production planning and product management to certification and digital productivity systems. His current research focuses on designing sustainable digital lean models for ready-made garment enterprises, particularly in labor-intensive sewing operations. He has collaborated with multiple organizations, implementing projects on workflow optimization, efficiency enhancement, and the use of real-time Process Monitoring Devices (PMDs). By bridging academic research with industrial applications, Koc contributes significantly to advancing operational excellence and competitiveness in the textile and apparel sector. His work underscores the potential of digital lean transformation as a sustainable solution for future manufacturing systems.

Professional Profile

Scopus

Education

Dr. Bulent Koc pursued his academic journey entirely at Istanbul Technical University, specializing in Textile Engineering. He earned his B.Sc. in Textile Engineering, where he built a foundation in fabric production, apparel processes, and material technology. He then completed his M.Sc. in Textile Engineering, focusing on production management and optimization in knitted garment manufacturing. His master’s thesis explored methods to enhance efficiency, cost-effectiveness, and lean principles in textile production environments. Currently, he is a Ph.D. candidate in the same department, expected to complete. His doctoral research centers on lean production and the development of sustainable digital lean models tailored for the ready-made garment industry. This work combines advanced lean management techniques with Industry, including real-time production monitoring, digital line balancing, and sustainability frameworks. Through this academic progression, Koc has developed a strong balance of theoretical knowledge and practical industrial insights in textile engineering.

Experience

Dr. Bulent Koc has built extensive professional experience in textile and apparel manufacturing since. He began as Production Planning Manager at Serfil Yarn and Fabric Factory, where he led efficiency projects and factory setup operations. Later, as Product Group Leader at Tars International Trade Ltd., he managed men’s wear collections and coordinated procurement. At Koton Mensucat, he advanced as a Product Manager, overseeing procurement and R&D in fabric development. he worked at Certurk Certification and Inspection Services, managing professional qualification certifications and training in textiles. His latest role was as Productivity Management Specialist at ITM Techsoft, where he developed digital lean systems, real-time data integration, and line balancing algorithms. Across his career, Koc has successfully combined lean manufacturing principles with technology-driven innovations. His projects consistently targeted productivity, sustainability, and competitiveness, making him a key contributor to both industry practices and applied textile engineering research.

Research Focus

Dr. Bulent Kocs research is centered on the integration of lean production systems with digital transformation in apparel manufacturing. His work focuses particularly on labor-intensive sewing operations, where workflow optimization and productivity are critical. He explores how real-time Process Monitoring Devices (PMDs) can track lean metrics, improve line balancing, and reduce inefficiencies. By combining lean principles with Industry such as digital data management and automation, his research offers scalable frameworks for sustainable production. He also examines the role of digital lean models in enhancing overall equipment effectiveness (OEE), minimizing waste, and promoting eco-friendly manufacturing practices. Field-based studies conducted in collaboration with Turkish textile companies validate his approaches and demonstrate measurable improvements in efficiency and sustainability. Kocs research bridges theory and practice, offering both academic contributions and real-world industrial solutions. His goal is to transform digital lean systems into a long-term driver of competitiveness in the apparel sector.

Awards and Honors

Throughout his career, Bulent Koc has been recognized for his contributions to lean manufacturing and digital transformation in apparel production. His applied research has been acknowledged at academic and industrial platforms, particularly in the field of textile engineering innovation. He has collaborated on projects supported, which emphasize efficiency, sustainability, and competitiveness in textile SMEs. His industry-driven lean transformation projects were recognized for advancing operational excellence, including notable work in digital line balancing and real-time production monitoring. He has been invited to share his expertise at professional seminars and academic discussions on lean systems in apparel manufacturing. In addition, his involvement in mechanics-related awards and conferences reflects his interdisciplinary contributions to engineering-focused production methodologies. These honors highlight his role as a bridge between academic research and industrial practice, reinforcing his reputation as an innovator in digital lean textile systems.

Publication Top Notes

Conclusion

Dr. Bulent Koc demonstrates potential as a researcher in lean production systems and digital transformation in apparel manufacturing, with a strong practical background and research focus. His industry projects and contributions to operational excellence are notable, and his research has the potential to make a significant impact in the industry. With further development of his publication record and international collaboration, he could become a strong candidate for the Best Researcher Award.

Dr. Edward Reutzel | Additive Manufacturing Process Planning | Best Researcher Award

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Dr. Edward Reutzel | Additive Manufacturing Process Planning | Best Researcher Award 

Research Professor, Penn State University, Applied Research Laboratory, United States

Edward W. (Ted) Reutzel is a renowned expert in additive manufacturing and materials processing. As the Director of the Center for Innovative Material Processing thru Direct Digital Deposition at Pennsylvania State University, Reutzel leads cutting-edge research in additive manufacturing. With a strong background in mechanical engineering, Reutzel has made significant contributions to the development of innovative materials processing techniques. Their research has far-reaching implications for industries such as aerospace, healthcare, and energy.

Profile

Orcid

🎓 Education

Reutzel holds a Ph.D. in Mechanical Engineering from Pennsylvania State University (2007), an M.S. in Mechanical Engineering from the Georgia Institute of Technology (1993), and a B.S. in Mechanical Engineering from Pennsylvania State University (1991). Their educational background has provided a solid foundation in mechanical engineering principles and prepared them for a career in research and development.

👨‍🔬 Experience

Reutzel has held various positions, including Director of the Center for Innovative Material Processing thru Direct Digital Deposition, Associate Research Professor at ARL Penn State, and Graduate Faculty in the Mechanical Engineering Department and Additive Manufacturing and Design Program at Penn State. With over two decades of experience in research and development, Reutzel has demonstrated expertise in additive manufacturing, materials processing, and laser systems engineering.

🔍 Research Interest

Reutzel’s research focuses on additive manufacturing, materials processing, and laser systems engineering. Their work explores innovative techniques for direct digital deposition, process monitoring, and defect detection in additive manufacturing. With applications in industries such as aerospace and healthcare, Reutzel’s research has the potential to transform manufacturing processes and improve product quality.

Awards and Honors 🏆

Although specific awards and honors are not detailed in the provided information, Reutzel’s research achievements and leadership roles suggest a high level of recognition within the field of additive manufacturing. Their certification and involvement in various research projects demonstrate a commitment to excellence and a strong reputation among peers.

📚 Publications

 

1. Automated defect recognition for additive manufactured parts using machine perception and visual saliency 🤖
2. IN SITU LASER ULTRASOUND-BASED RAYLEIGH WAVE PROCESS MONITORING OF DED-AM METALS 💡
3. Multi-spectral method for detection of anomalies during powder bed fusion additive manufacturing 🔍
4. Effect of interlayer temperature on meltpool morphology in laser powder bed fusion 🔥
5. Multi-modal sensor fusion with machine learning for data-driven process monitoring for additive manufacturing 📊
6. Electro-strengthening of the additively manufactured Ti–6Al–4V alloy 💪
7. Effect of processing conditions on the microstructure, porosity, and mechanical properties of Ti-6Al-4V repair fabricated by directed energy deposition 🔩
8. Formation processes for large ejecta and interactions with melt pool formation in powder bed fusion additive manufacturing 🌐
9. Multi-sensor investigations of optical emissions and their relations to directed energy deposition processes and quality 🔎
10. Design and evaluation of an additively manufactured aircraft heat exchanger ❄️

Conclusion

Edward W. (Ted) Reutzel is an outstanding researcher with a strong background in additive manufacturing and mechanical engineering. Their extensive research experience, leadership roles, and prolific publication record make them an excellent candidate for the Best Researcher Award. While there are areas for improvement, Reutzel’s research achievements and potential for future impact make them a compelling candidate for this award.

Tadeu Castro da Silva | Additive manufacturing technologies | Best Researcher Award

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Assist. Prof. Dr Tadeu Castro da Silva | Additive manufacturing technologies | Best Researcher Award

Prof. Dr-Ing, National Institute of Technology, Portugal

T.C. da Silva is a researcher and engineer with a strong background in mechanical engineering. He holds a PhD from the University of Brasília and has completed postdoctoral research at various institutions. Silva’s research focuses on smart materials, additive manufacturing, and thermal characterization.

Profile

orcid

scholar

Education 🎓

PhD in Mechanical Engineering, University of Brasília (2019)  Master’s in Mechanical Engineering, University of Brasília (2014)  Specialization in Software Engineering, Catholic University of Brasília (2009-2010)  Bachelor’s in Mechanical Engineering, University for the Development of the State and Region of Pantanal (2003-2008)

Experience 🧪

Researcher, University of Brasília (2012-present)  Postdoctoral researcher, University of Brasília (2020-2021)  Engineer, Brazilian Air Force (2011-2012)  Professor, Federal Institute of Education, Science, and Technology (2005-2007)

Awards & Honors🏆

Unfortunately, the provided text does not mention any specific awards or honors received by T.C. da Silva.

Research Focus 🔍

Smart materials and structures  Additive manufacturing (3D/4D printing) Thermal characterization of materials  Shape memory alloys

Publications📚

1. The effect of a chemical additive on the fermentation and aerobic stability of high-moisture corn 🌽🧬 (2015)
2. Filho TC da Silva, E Sallica-Leva, E Rayón, CT Santos transformation 🔩🔧 (2018)
3. Emissivity measurements on shape memory alloys 🔍💡 (2016)
4. Development of a gas metal arc based prototype for direct energy deposition with micrometric wire 💻🔩 (2024)
5. Influence of Deep Cryogenic Treatment on the Pseudoelastic Behavior of the Ni57Ti43 Alloy ❄️💡 (2022)
6. Stainless and low-alloy steels additively manufactured by micro gas metal arc-based directed energy deposition: microstructure and mechanical behavior 🔩🔧 (2024)
7. Study of the influence of high-energy milling time on the Cu–13Al–4Ni alloy manufactured by powder metallurgy process ⚗️💡 (2021)
8. Cryogenic treatment effect on NiTi wire under thermomechanical cycling ❄️💡 (2018)
9. Effect of Cryogenic Treatment on the Phase Transformation Temperatures and Latent Heat of Ni54Ti46 Shape Memory Alloy ❄️💡 (2022)
10. Cryogenic Treatment Effect on Cyclic Behavior of Ni54Ti46 Shape Memory Alloy ❄️💡 (2021)
11. Influence of thermal cycling on the phase transformation temperatures and latent heat of a NiTi shape memory alloy 🔩🔧 (2017)
12. Effect of the Cooling Time in Annealing at 350°C on the Phase Transformation Temperatures of a Ni55Ti45 wt. Alloy 🔩🔧 (2015)
13. Experimental evaluation of the emissivity of a NiTi alloy 🔍💡 (2015)
14. Microstructure, Thermal, and Mechanical Behavior of NiTi Shape Memory Alloy Obtained by Micro Wire and Arc Direct Energy Deposition 🔩🔧 (2025)
15. Low-Annealing Temperature Influence in the Microstructure Evolution of Ni53Ti47 Shape Memory Alloy 🔩🔧 (2024)
16. Use of Infrared Temperature Sensor to Estimate the Evolution of Transformation Temperature of SMA Actuator Wires 🔍💡 (2023)
17. Use of infrared temperature sensor to estimate the evolution of transformation temperature of SMA actuator wires 🔍💡 (2021)
18. Effet du traitement cryogénique sur le comportement cyclique de l’alliage Ni54Ti46 à mémoire de forme ❄️💡 (2020)
19. Efeito de tratamento criogênico no comportamento cíclico da liga Ni54Ti46 com memória de forma ❄️💡 (2020)
20. Functional and Structural Fatigue of NiTi Shape Memory Wires Subject to Thermomechanical Cycling 🔩🔧 (2019)

Conclusion

T.C. da Silva is an accomplished researcher with a strong track record in additive manufacturing, materials science, and mechanical engineering. His extensive research experience, interdisciplinary approach, and commitment to knowledge sharing make him an ideal candidate for the Best Researcher Award. By addressing areas for improvement, he can continue to grow as a researcher and make even more significant contributions to his field.