Rate My Professor Seyed Hojat

Seyed Mohammad Hojjatzadeh is an Assistant Professor in the Department of Mechanical Engineering at the University of Memphis, joining the faculty in 2024. He serves as Director of the Metal Additive Manufacturing Laboratory, a core research facility within the Herff College of Engineering dedicated to developing next-generation products using metal additive manufacturing for industries including aviation, automotive, and biomedical. Hojjatzadeh's academic background includes a B.S. degree earned in 2014 from Chamran University of Ahvaz, an M.S. in Mechanical Engineering in 2022, and a Ph.D. in Mechanical Engineering in 2023 from the University of Wisconsin-Madison. His doctoral dissertation, titled "Defect Formation, Evolution and Prediction in Metal Additive Manufacturing," explored challenges in laser powder bed fusion processes. Following his Ph.D., he held a Postdoctoral Associateship in Materials Science and Engineering at Virginia Tech from 2023 to 2024.

Hojjatzadeh's research specializations encompass smart manufacturing, in-situ monitoring, additive manufacturing, and machine learning. His work advances metal additive manufacturing through in-situ synchrotron X-ray monitoring to analyze real-time process dynamics, including pore and crack formation, melt pool behaviors, process instabilities, and the development of closed-loop systems for part qualification, as well as novel alloy designs to improve printability and performance. Key publications include "Direct Observation of Pore Formation Mechanisms during LPBF Additive Manufacturing Process" (2020, cited over 350 times), "Controlling Process Instability for Defect Lean Metal Additive Manufacturing" in Nature Communications (2022), "In-Situ Characterization of Pore Formation Dynamics in Pulsed Wave Laser Powder Bed Fusion" (2021), and "Effects of Particle Size Distribution with Efficient Packing on Powder Bed" (2022, cited 59 times). His research has amassed over 2,100 citations, underscoring its substantial impact on defect mitigation and optimization in the additive manufacturing field.