Wei Li

Assistant Professor

University of Texas at Dallas

United States

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About

Wei Li is an Assistant Professor at The University of Texas at Dallas, USA. His research focuses on advanced manufacturing techniques including robotic wire arc additive manufacturing, multiphysics modeling of directed energy deposition processes, and improvements in material properties for aerospace applications. Recent publications highlight his work on repairing aluminum alloys and integrating machining with additive manufacturing for potential in-space fabrication.

Articles (13)

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2025

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2025

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2024

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2024

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2024

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2023

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2023

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2023

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2023

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2023

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2023

Year:

2023

Year:

2023

Collaborators (3)

Yingjian Liu

University of Texas at Dallas

UNITED STATES

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Arif Malik

University of Texas at Dallas

UNITED STATES

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Dong Qian

UNITED STATES

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Wei Li

Research Interests

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Articles (13)

Repairing aerospace aluminum alloy with robotic wire arc additive manufacturing for the potential in-space use

Multiphysics modelling of wire-based directed energy deposition process with experimental validation

Hybrid segmented manufacturing of metal part by integrating wire arc additive manufacturing and machining

Comprehensive study of the cold-temperature directed energy deposition: Multi-physics modelling and experimental validation

Exploratory study of repairing damaged aluminum part through robotic hybrid wire arc additive manufacturing and machining for potential in-space manufacturing

Integrating robotic wire arc additive manufacturing and machining: hybrid WAAM machining

Processing aluminum alloy with hybrid wire arc additive manufacturing and ultrasonic nanocrystalline surface modification to improve porosity, surface finish, and hardness

Experimental Study of Low-Temperature Directed Energy Deposition Near Freezing Point Temperature 0°C

Temporally continuous thermofluidic–thermomechanical modeling framework for metal additive manufacturing

Exploratory study of directed energy deposition conducted at low temperature −20 °C

Interlayer machining effects on microstructure and residual stress in directed energy deposition of stainless steel 316L

Porosity evolution under increasing tension in wire-arc additively manufactured aluminum using in-situ micro-computed tomography and convolutional neural network

Comprehensive studies of SS316L/IN718 functionally gradient material fabricated with directed energy deposition: Multi-physics & multi-materials modelling and experimental validation

Collaborators (3)

Yingjian Liu

Arif Malik

Dong Qian

Make your next move.

Wei Li

Research Interests

Explore related searches

Contact this professor

About

Articles (13)

Repairing aerospace aluminum alloy with robotic wire arc additive manufacturing for the potential in-space use

Multiphysics modelling of wire-based directed energy deposition process with experimental validation

Hybrid segmented manufacturing of metal part by integrating wire arc additive manufacturing and machining

Comprehensive study of the cold-temperature directed energy deposition: Multi-physics modelling and experimental validation

Exploratory study of repairing damaged aluminum part through robotic hybrid wire arc additive manufacturing and machining for potential in-space manufacturing

Integrating robotic wire arc additive manufacturing and machining: hybrid WAAM machining

Processing aluminum alloy with hybrid wire arc additive manufacturing and ultrasonic nanocrystalline surface modification to improve porosity, surface finish, and hardness

Experimental Study of Low-Temperature Directed Energy Deposition Near Freezing Point Temperature 0°C

Temporally continuous thermofluidic–thermomechanical modeling framework for metal additive manufacturing

Exploratory study of directed energy deposition conducted at low temperature −20 °C

Interlayer machining effects on microstructure and residual stress in directed energy deposition of stainless steel 316L

Porosity evolution under increasing tension in wire-arc additively manufactured aluminum using in-situ micro-computed tomography and convolutional neural network

Comprehensive studies of SS316L/IN718 functionally gradient material fabricated with directed energy deposition: Multi-physics &amp; multi-materials modelling and experimental validation

Collaborators (3)

Yingjian Liu

Arif Malik

Dong Qian

Make your next move.

Exploratory study of directed energy deposition conducted at low temperature −20 °C

Comprehensive studies of SS316L/IN718 functionally gradient material fabricated with directed energy deposition: Multi-physics & multi-materials modelling and experimental validation