VPRI RAPID Innovation Funding Program

VPRI RAPID Innovation Funding Program is sponsored by Prairie View A&M University. This program supports innovative ideas from faculty, staff, and students at Prairie View A&M University, aiming to develop tangible products and prototypes. Past themes have included projects addressing artificial intelligence and thermal management.

VPRI RAPID Innovation Funding Program – Research The Vice President for Research and Innovation has established a new initiative, Rapid-Response Grant Program (RAPID), to support Innovation ideas to help faculty, staff, and students to develop their ideas into tangible products and prototypes that will lead to viable intellectual property.

These RAPID-Innovation grants are generally for limited time-span and aimed to encourage faculty to jump-start an innovative project. The RAPID-Innovation Program Call for Proposals is announced during academic year and summer months based on the university priorities and societal needs.

The themes or focus areas of recent RAPID-Innovation awards include: COVID-19 Innovation: Projects aimed to innovate, design, develop or commercialize physical or software products and processes to address or mitigate COVID-19 risks and related issues Listed here are few selected projects supported by the VPRI RAPID-Innovation program.

To see more details about the corresponding projects, please visit the faculty in their respective laboratory, department, or college websites.

Semi-supervised Deep Learning for Effective COVID-19 Classification on Medical Images Dr. Xishuang Dong , Assistant Professor, Department of Electrical Engineering, College of Engineering Coronavirus disease 2019 (COVID-19) is an ongoing global pandemic in over 200 countries and territories [1, 2].

Imaging findings play a critical role in constraining the viral transmission and also fighting against COVID-19 in the early stage of its spreading. The objective of this project is to develop software that is capable of implementing the classification of COVID-19 pathology on medical images through building semisupervised deep learning models.

Specifically, the software can complete COVID-19 classification using a considerable amount of medical images without annotations, which significantly reduces the cost of labeling images to build high-performance models. Impact: The proposed effort will advance various areas, including big data analytics, artificial intelligence, and medical knowledge mining, which significantly meets with the research priorities of the university.

Furthermore, it will help educate the students with state-of-the-art technologies and train them to become highly qualified for the workforce and their future career.

3D multiscale structures with optimized properties for engineering/medical applications Dr. Jaejong Park , Assistant Professor, Mechanical Engineering, College of Engineering The research activity focuses on understanding the current state-of-the-art in multiscale structural design using advanced techniques. They include generative design, topology optimization, and machine learning-based approaches.

With a surge of additive manufacturing, designing of organic geometries using computer-based design algorithms have gathered tremendous research attention lately. Especially with robust optimization schemes, property-optimized, (e.g., superwettability – face mask covering, multifunctionality, etc.) structures are showing a significant impact on various applications in engineering and medical setting.

Existing literature will be thoroughly reviewed to recognize the current trend and perceive any standing hurdles that should be immediately addressed. Impact : This literature study has significant potential in leading multiple collaboration opportunities among the PV community.

The design of such an optimized structure involves multi-physics problems that require expertise from architecture, economy, physics, as well as departments from the college of engineering. Upon completion, external funding from relevant agencies will be pursued.

Thermal Management of Electrospun Nanofiber in a Facemask to improve Everyday life against COVID-19 Dr. Nabila Shamim , Assistant Professor, Department of Chemical Engineering, College of Engineering This study aims to develop methods to transform facemasks into providing better protection against microorganisms such as the novel coronavirus, also known as COVID -19.

Here, thermal management is introduced into face masks to enhance the user’s thermal comfort. Air filtration is possible using electrospun nanofibers cloth. However, the qualification of an electrospun nanofibers cloth in a facemask to protect against COVID -19 is still unknown.

The objectives of this proposal are to conduct thermal images, morphology, water droplet absorption, flexibility, and airborne particle filtering capabilities of a poly(ε-caprolactone) nanofiber to evaluate whether it can be used with an existing procedure or generic fabric based mask to protect an individual from novel coronavirus.

These multifunctional face mask designs can be explored for both outdoor and indoor applications to protect people from microorganisms and simultaneously achieve personal thermal comfort. Impact : Effective thermal management of the electrospun nanofibers in a facemask will increase the comfort zone of usage for a more extended time; thus, adopting face masks will slow the spread of COVID-19.

Online/Hybrid Manufacturing Processes Laboratory in Cope with COVID-19 Pandemic Dr. Lai Jiang , Assistant Professor, Department of Mechanical Engineering, College of Engineering Manufacturing Processes Laboratory, as one of the three required lab courses for undergraduate mechanical engineering students, is encountering extreme difficulties due to the remote education policy at PVAMU caused by the COVID-19 pandemic.

The proposed process to be developed in this proposal will solve issues such as limited classroom spacing, social distancing in class, clear instructions, etc. New lab modules and course materials will be developed to replace current ones that cannot be moved online. This effort will serve as a practical trial for all other traditional engineering lab courses that have moved to online/hybrid for the fall semester.

Impact : Research activities performed in the proposed project will provide guidelines for faculties in creating equivalent online or hybrid lab courses for semesters when remote education is required. High-quality courses developed with new modules will reduce the virus spreading in regular face-to-face lab classes and thus help mitigate COVID-19 risks.

Virtual Reality/Mixed Reality: A COVID-19 Response to Chemical Engineering Laboratory Dr. Keisha C. A. Antoine , Department of Chemical Engineering, College of Engineering The project goal is to use virtual reality/mixed reality (VR/MR) tools in the Chemical Engineering laboratory curriculum to address COVID-19 requirements for social distancing.

By introducing VR/MR technology, we can meet the current need for remote learning while providing an enhanced learning experience in the senior laboratory course to reinforce abstract engineering concepts. VR/MR is being successfully used in providing workforce training in a range of fields: engineering, architecture, medicine, aerospace, even sales/marketing.

Our proposal stays true to the COVID-19 innovation theme by pioneering an immersive, digital (yet hands-on) learning experience that is unavailable in face-to-face labs characteristic in STEM education. Impact: We are tackling STEM learning in a COVID-19 world because with VR/MR technology, we can eliminate COVID-19 transmission modes present in face-to-face instruction.

With VR/MR at PVAMU, we can provide quality education to underrepresented groups in a remote learning format, while modernizing the chemical engineering curriculum.

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