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Shahadat Hussain

Dr. Shahadat Hussain is a materials scientist specializing in additive manufacturing, metamaterials, and data-driven materials design. His research focuses on the development and characterization of advanced functional materials, with particular emphasis on laser powder bed fusion (LPBF), triply periodic minimal surface (TPMS) structures, and shape memory alloys, including nickel–titanium (NiTi) systems.

Education and Career

Dr. Hussain is currently affiliated with New York University Abu Dhabi, where he is engaged in interdisciplinary research at the intersection of materials science, mechanical engineering, and computational modeling. His work involves both experimental and computational approaches to understand the relationship between processing, microstructure, and mechanical performance in advanced materials.

Research

Dr. Hussain’s research interests include:

• Additive manufacturing and advanced manufacturing processes
• Metamaterials and architected materials
• Shape memory alloys and functional materials
• Data-driven materials science and machine learning applications
• Microstructure–property relationships in engineered materials

His work integrates machine learning techniques with experimental methods to accelerate materials discovery and optimize manufacturing parameters. His research has applications in lightweight structures, biomedical devices, and energy systems.

Publications and Contributions

Dr. Hussain has contributed to multiple peer-reviewed publications in the fields of materials science and engineering. He is also actively involved in the academic community as a reviewer for several international journals, contributing to the peer-review process in areas related to additive manufacturing and advanced materials.

References

1. Official website: https://www.shahadathussain.com
2. Google Scholar: https://scholar.google.com/citations?user=tQNSWaAAAAAJ&hl=en
3. ORCID: https://orcid.org/0000-0002-4355-2169

See also

• Additive manufacturing
• Metamaterials
• Shape memory alloys
• Machine learning in materials science