Julia K. Hoskins
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Graduate Research Assistant
Graduate Student Researcher
Research Areas
Biomedical Subjects
Links
Biography and Research Information
OverviewAI-generated summary
Julia K. Hoskins' research focuses on the application of additive manufacturing techniques, specifically 3D printing, for creating customized devices in neuroscience and microfluidics. She has investigated the development of bioinspired surfaces for enhanced wear resistance and friction reduction, and explored the use of machine learning and machine vision in femtosecond laser machining. Her work includes the design and fabrication of 3D printed microsampling devices and high-porosity membranes with submicron pores for neuroscience applications and microfluidics. Hoskins has also explored the integration of multiscale 2PP and LCD 3D printing for creating membrane-integrated microfluidic chips. Her scholarship metrics include an h-index of 3 with 7 total publications and 31 citations. She has collaborated with Patrick M. Pysz, Julie A. Stenken, and Min Zou at the University of Arkansas at Fayetteville on multiple publications.
Metrics
- h-index: 3
- Publications: 7
- Citations: 32
Selected Publications
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Co-tuning ultrathin ZnO films and programmable 3D textures to control lunar dust simulant adhesion (2026)
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Multiscale 2PP and LCD 3D Printing for High-Resolution Membrane-Integrated Microfluidic Chips (2025)
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3D Printing of High-Porosity Membranes with Submicron Pores for Microfluidics (2024)
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3D Printed Microsampling Probe for Neuroscience (2024)
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Exploring Machine Learning and Machine Vision in Femtosecond Laser Machining (2023)
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3D Printed Customizable Microsampling Devices for Neuroscience Applications (2023)
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Designing a Bioinspired Surface for Improved Wear Resistance and Friction Reduction (2021)
Collaboration Network
Top Collaborators
- Designing a Bioinspired Surface for Improved Wear Resistance and Friction Reduction
- 3D Printed Customizable Microsampling Devices for Neuroscience Applications
- 3D Printing of High-Porosity Membranes with Submicron Pores for Microfluidics
- Exploring Machine Learning and Machine Vision in Femtosecond Laser Machining
- 3D Printed Microsampling Probe for Neuroscience
Showing 5 of 6 shared publications
- 3D Printed Customizable Microsampling Devices for Neuroscience Applications
- 3D Printed Microsampling Probe for Neuroscience
- Multiscale 2PP and LCD 3D Printing for High-Resolution Membrane-Integrated Microfluidic Chips
- 3D Printed Customizable Microsampling Devices for Neuroscience Applications
- 3D Printed Microsampling Probe for Neuroscience
- Multiscale 2PP and LCD 3D Printing for High-Resolution Membrane-Integrated Microfluidic Chips
- Exploring Machine Learning and Machine Vision in Femtosecond Laser Machining
- Co-tuning ultrathin ZnO films and programmable 3D textures to control lunar dust simulant adhesion
- Co-tuning ultrathin ZnO films and programmable 3D textures to control lunar dust simulant adhesion
- Co-tuning ultrathin ZnO films and programmable 3D textures to control lunar dust simulant adhesion
- Co-tuning ultrathin ZnO films and programmable 3D textures to control lunar dust simulant adhesion
- Co-tuning ultrathin ZnO films and programmable 3D textures to control lunar dust simulant adhesion
- Co-tuning ultrathin ZnO films and programmable 3D textures to control lunar dust simulant adhesion
- Co-tuning ultrathin ZnO films and programmable 3D textures to control lunar dust simulant adhesion
- Co-tuning ultrathin ZnO films and programmable 3D textures to control lunar dust simulant adhesion
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