Pinku Yadav | Metal Additive Manufacturing | Best Researcher Award

Published on by Metallurgical Engineering

Best Researcher Award

Pinku Yadav
Swiss Federal Laboratories for Materials Science and Technology (EMPA), Switzerland

Pinku Yadav
Affiliation Swiss Federal Laboratories for Materials Science and Technology
Country Switzerland
Scopus ID 57209256782
Documents 13
Citations 241
h-index 7
Subject Area Metal Additive Manufacturing
Event Metallurgical Engineering Awards
ORCID 0000-0002-4014-627X

Pinku Yadav nomination recognizes the scholarly achievements and scientific contributions of the Best Researcher Award, a researcher specializing in metal additive manufacturing, laser powder bed fusion, advanced materials processing, process monitoring, and data-driven manufacturing systems. His academic and industrial experience spans Switzerland, the United Kingdom, Belgium, France, Germany, and Spain, reflecting substantial international engagement in advanced manufacturing research. His work has contributed to the understanding of process stability, defect detection, microstructural evolution, and performance optimization in additive manufacturing systems.[1]

Abstract

Pinku Yadav is a materials scientist and manufacturing researcher whose work focuses on additive manufacturing technologies, particularly laser powder bed fusion, process monitoring, machine learning applications, and advanced alloy development. His research combines experimental characterization, process optimization, in-situ monitoring, and computational approaches to improve manufacturing reliability and material performance. Through collaborations with leading industrial and academic institutions, he has contributed to advancements in defect detection, texture evolution, welding science, alloy development, and metal additive manufacturing systems.[2]

Keywords

Metal Additive Manufacturing, Laser Powder Bed Fusion, In-Situ Monitoring, Process Analytics, Machine Learning, Alloy Development, Laser Welding, Advanced Materials, Defect Detection, Metallurgical Engineering.

Introduction

The field of metal additive manufacturing has emerged as a transformative technology for producing complex engineering components with enhanced material utilization and design flexibility. Researchers working at the intersection of materials science, process engineering, and digital manufacturing play a critical role in advancing this discipline. Pinku Yadav’s research portfolio reflects multidisciplinary engagement across these domains, emphasizing process understanding, manufacturing quality assurance, and materials innovation.[1][3]

Research Profile

Pinku Yadav completed his Ph.D. in Metal Additive Manufacturing through the University of Bordeaux and SIRRIS, focusing on drift detection in laser powder bed fusion processes using in-situ monitoring instrumentation and data analytics techniques.[2] His subsequent research and industrial appointments have involved alloy development, process optimization, additive manufacturing qualification, machine learning integration, laser welding, and advanced materials characterization.[1]

  • Postdoctoral Researcher at EMPA, Switzerland.
  • Former AM Lab Engineer at Alloyed Ltd., Oxford, United Kingdom.
  • Marie SkΕ‚odowska-Curie Actions Fellowship recipient.

Research Contributions

Pinku Yadav has contributed to several areas of metallurgical and manufacturing research. His investigations into melt pool monitoring and machine-learning-based defect identification have supported the development of more reliable quality assurance methodologies for laser powder bed fusion systems.[2]

  1. Development of monitoring methodologies for additive manufacturing processes.
  2. Research on texture evolution in aluminum alloys processed through additive manufacturing.
  3. Development of NdFeB magnet fabrication approaches using laser-based manufacturing technologies.

Publications

Pinku Yadav has established a growing publication record within the field of metal additive manufacturing, supported by 13 indexed documents and a citation profile demonstrating sustained scholarly engagement. Research outputs include studies on process monitoring, additive manufacturing process optimization, defect prediction, materials characterization, and advanced alloy systems.[1]

  • Laser Powder Bed Fusion Process Monitoring.
  • Machine Learning for Manufacturing Quality Control.
  • Texture Evolution in Aluminum Alloys.
  • Defect Detection and Drift Monitoring.
  • Advanced Metallic Materials for Additive Manufacturing.

Research Impact

Pinku Yadav is reflected through his citation record, industrial collaborations, and successful participation in international research programs. His work addresses practical challenges in additive manufacturing by integrating materials science, process engineering, and data analytics. The resulting outcomes contribute to enhanced manufacturing reliability, process qualification, and industrial adoption of advanced manufacturing technologies.[4]

Award Suitability

Based on documented scholarly output, international research engagement, industrial collaboration, and contributions to metal additive manufacturing, Pinku Yadav demonstrates characteristics commonly associated with candidates for research excellence recognition. His interdisciplinary expertise spanning manufacturing science, materials engineering, process monitoring, machine learning, and advanced alloy development aligns with the objectives of the Metallurgical Engineering Awards program.[1][2]

Conclusion

Pinku Yadav has developed a research portfolio focused on advancing metal additive manufacturing through innovative process monitoring, materials development, and manufacturing optimization strategies.[5] His international research experience, publication record, industrial engagement, and scientific achievements collectively support consideration for the Best Researcher Award within the Metallurgical Engineering Awards framework.[2]

References

  1. Elsevier. (n.d.). Scopus author details: Pinku Yadav, Author ID 57209256782. Scopus.
    https://www.scopus.com/authid/detail.uri?authorId=57209256782
  2. Pinku Yadav,. & et.al. Advanced Engineering Materials. (2022). Binder jetting 3D printing of titanium aluminides based materials: a feasibility study
    https://advanced.onlinelibrary.wiley.com/doi/abs/10.1002/adem.202000408
  3. Pinku Yadav,. & et.al. Advanced Engineering Materials. (2021). Data treatment of in situ monitoring systems in selective laser melting machines.
    https://advanced.onlinelibrary.wiley.com/doi/abs/10.1002/adem.202001327
  4. Pinku Yadav,. & et.al. Journal of Manufacturing Processes. (2022). Data processing techniques for in-situ monitoring in L-PBF process.
    https://www.sciencedirect.com/science/article/pii/S1526612522004509
  5. Pinku Yadav,. & et.al. Advanced Engineering Materials. (2029). Novel hybrid printing of porous TiC/Ti6Al4V composites.
    https://advanced.onlinelibrary.wiley.com/doi/abs/10.1002/adem.201900336

Mahmoud Afshari | Direct Metal Deposition | Best Researcher Award

Published on by Metallurgical Engineering

Dr. Mahmoud Afshari | Direct Metal Deposition | Best Researcher Award

Adjunct Professor at Ministry of Education of the Islamic Republic of Iran | Iran

Dr. Mahmoud Afshari’s research focuses on the integration of additive manufacturing, welding technologies, and composite materials design to advance high-precision fabrication methods in modern engineering. His body of work explores the mechanics, thermodynamics, and microstructural behavior of materials subjected to advanced manufacturing processes. Through the development of laser additive manufacturing models and friction stir welding simulations, Dr. Afshari has contributed to optimizing the thermal and mechanical performance of alloys such as Inconel 718, Ti-6Al-4V, and Al-Mg systems. His investigations have extended into polymer nanocomposites and fused filament fabrication (FFF), enhancing tensile modulus, hardness, and impact resistance through process-parameter optimization. His research outputs-comprising 30 Scopus-indexed publications with 168 citations and an h-index of 8-reflect rigorous experimentation combined with computational modeling. Notably, his recent articles in high-impact journals like Optics and Laser Technology, Journal of Molecular Structure, and Journal of Materials Science: Materials in Electronics highlight his expertise in material characterization, heat-transfer simulation, and nanostructure control. Alongside his scholarly publications, Dr. Afshari’s patents on advanced thermal systems and automated machinery demonstrate his applied research orientation and industry relevance. His scientific productivity, innovation in simulation-based design, and multidomain mastery exemplify excellence in metallurgical and manufacturing research, marking him as a strong candidate for the Best Researcher Award.

Profiles : Scopus | ORCID | Google Scholar

Featured Publications

Afshari, H., Taher, F., Alavi, S. A., Afshari, M., Samadi, M. R., & Allahyari, F. (2024). Studying the effects of FDM process parameters on the mechanical properties of parts produced from PLA using response surface methodology. Colloid and Polymer Science, 302(6), 955–970. Cited by: 26

Afshari, M., Bakhshi, S., Samadi, M. R., & Afshari, H. (2023). Optimizing the mechanical properties of TiOβ‚‚/PA12 nano-composites fabricated by SLS 3D printing. Polymer Engineering & Science, 63(1), 267–280. Cited by: 26

Afshari, M., Hamzekolaei, H. G., Mohammadi, N., Yazdanshenas, M., … (2023). Investigating the effect of laser cladding parameters on the microstructure, geometry and temperature changes of Inconel 718 superalloy using the numerical and experimental approaches. Materials Today Communications, 35, 106329. Cited by: 25

Taher, F., Afshari, M., Houmani, A., Samadi, M. R., Bakhshi, S., & Afshari, H. (2024). Simultaneous enhancement of the impact strength and tensile modulus of PP/EPDM/TiOβ‚‚ nanocomposite fabricated by fused filament fabrication. Colloid and Polymer Science, 302(3), 393–407. Cited by: 15

Hardani, H., Afshari, M., Samadi, M. R., Afshari, H., & LΓ³pez, S. A. (2025). An enhancement in the tensile modulus and bending resistance of polylactic acid/carbon nanotube composite by optimizing FFF process parameters. Journal of Thermoplastic Composite Materials, 38(4), 1379–1403. Cited by: 13

Jiaqi Chang | Manufacturing | Best Researcher Award

Published on by Metallurgical Engineering

Mr. Jiaqi Chang | Manufacturing | Best Researcher Award

Doctoral Researcher at Tongji university, China.

Jiaqi Chang is a dedicated researcher specializing in tunnel and underground engineering. πŸŒŒπŸ‘·β€β™‚οΈ His passion for advancing civil and geotechnical engineering has driven him to excel in academia and research. Currently pursuing a dual Doctor of Engineering degree at Tongji University in China and Ruhr University Bochum in Germany, Jiaqi has consistently demonstrated exceptional talent and commitment. πŸ“šπŸŒ His work focuses on cutting-edge technologies like machine learning, wireless sensing, and numerical simulations in tunneling projects. He is a recipient of numerous awards for his academic excellence and research contributions. πŸ†πŸŒŸ In his leisure time, Jiaqi enjoys exploring innovative approaches to solving complex engineering challenges. πŸ’‘βš™οΈ

Professional ProfilesπŸ“–

ORCID

Scopus

Education πŸŽ“

Jiaqi Chang embarked on his academic journey at Tongji University, earning a Bachelor of Engineering in Civil Engineering in 2019, ranking an impressive 7th out of 429 students. πŸ…πŸ“ He deepened his expertise with advanced coursework in soil mechanics, rock mechanics, structural mechanics, and mathematical modeling. 🌟✏️ Currently, he is pursuing dual doctoral degrees at Tongji University, China, and Ruhr University Bochum, Germany, with anticipated graduation dates in June 2025. 🌍 His education integrates rigorous training in tunnel engineering and computational modeling, preparing him for impactful research and innovation in his field. πŸ’‘πŸ”¬

Professional ExperienceπŸ’Ό

Jiaqi Chang’s career is marked by a blend of research, practical application, and collaboration on high-profile projects. 🌐 He has actively contributed to Chinese national and international research initiatives, focusing on safety risks in shield tunnels, adaptive intelligent construction technologies, and undersea tunnel diagnostics. πŸŒŠπŸ—οΈ His responsibilities include analyzing disturbances caused by tunnel construction, intelligent sensing, and mechanical analysis. As a skilled communicator, Jiaqi has delivered oral presentations at prestigious conferences such as ECSMGE 2024 and ISGSR 2022. πŸŽ€πŸ“Š His hands-on approach and academic rigor make him a standout in his field. πŸ’ͺ✨

Research Focus πŸ”

Jiaqi’s research delves into the intersection of traditional civil engineering and advanced computational methods. πŸŒπŸ’» His work in shield tunneling construction leverages physics-informed machine learning, wireless sensing, and numerical simulation to address real-world challenges. πŸš‡πŸ“ˆ He also explores surrogate modeling to optimize tunnel designs, ensuring safety and efficiency. πŸ› οΈπŸ“‰ His interdisciplinary approach integrates engineering principles with data-driven technologies, aiming to revolutionize geotechnical practices. πŸ”„πŸ’‘

Awards and Honors

Jiaqi Chang’s dedication has been recognized with several accolades, including the Scholarship of Outstanding Doctor at Tongji University (2019, 2023) and the prestigious China Scholarship Council award in 2022. πŸŽ–οΈπŸ’Ό His achievements extend to international competitions, such as the ISSMGE TC304 Student Contest, where he won an Excellent Award in 2021. πŸŒŽβš™οΈ Notably, he received the 1st Prize in the Concrete Canoe Competition at the ASCE Mid-Pacific Student Conference in 2018. 🚀✨ These honors reflect his excellence in academic performance and innovative research contributions. πŸŒŸπŸ“œ

Conclusion βœ…

Jiaqi Chang exemplifies the qualities of a distinguished researcher with a rare combination of theoretical depth and practical impact. His prolific contributions to tunneling and underground engineering, coupled with his pioneering use of machine learning and advanced modeling, make him a strong candidate for the Best Researcher Award. Continued expansion into multidisciplinary collaborations and global initiatives will only further solidify his position as a leader in his field.

Publications to NotedπŸ“š

Improved model-free adaptive control of shield machine posture during tunnelling

Authors: Hongwei Huang, Jiaqi Chang, Dongming Zhang, Markus Thewes, Wei Lin

Year: 2025

Journal: Advanced Engineering Informatics

Deformational behaviors of existing three-line tunnels induced by under-crossing of three-line mechanized tunnels: A case study

Authors: Jiaqi Chang, Markus Thewes, Dongming Zhang, Hongwei Huang, Wei Lin

Year: 2024

Journal: Canadian Geotechnical Journal

Data-Based postural prediction of shield tunneling via machine learning with physical information

Authors: Jiaqi Chang, Hongwei Huang, Markus Thewes, Dongming Zhang, Wu H.M.

Year: 2024

Journal: Computers and Geotechnics

Machine learning-based automatic control of tunneling posture of shield machine

Authors: Hongwei Huang, Jiaqi Chang, Dongming Zhang, Zhang J., Wu H.M., Li G.

Citations: 60 (Google Scholar)

Year: 2022

Journal: Journal of Rock Mechanics and Geotechnical Engineering

Transverse deformational behaviors of segmental lining during shield tunneling: A case study

Authors: Jiaqi Chang, Hongwei Huang, Dongming Zhang, Wu H.M., Yan J.Y.

Year: 2022

Journal: Structural Control & Health Monitoring

A hybrid sensing of rotation-induced stress of segmental lining during shield tunneling via WSN and surrogate numerical modeling

Authors: Jiaqi Chang, Dongming Zhang, Hongwei Huang, Jia J.W.

Year: 2023

Journal: Tunnelling and Underground Space Technology