Speed School Professors Attract Seed Grant Funding for Research Projects
August 4, 2022
Five Speed School professors were awarded Jon Rieger Seed Grants from the Executive Vice President for Research and Innovation (EVPRI) Office for spring 2022, one of the School’s largest winning classes: Dr. Yanyu Chen, Assistant Professor, Mechanical Engineering; Dr. Luis Segura, Assistant Professor, Industrial Engineering; Dr. Tyler Mahoney, Assistant Professor, Civil & Environmental Engineering; Dr. Xiaomei Wang, Assistant Professor, Industrial Engineering; and Dr. Sabur Baidya, Assistant Professor, Computer Science & Engineering. These approximately $7500 start-up funds are generally used to leverage initial results to attract follow-on external funding.
Dr. Yanyu Chen joined UofL in August 2018. His research interests in mechanical engineering include lightweight mechanical metamaterials, bioinspired composites, phononic metamaterials, 3D lithium-ion battery architectures, and additive manufacturing. His research project that received the seed grant is “Developing 3D printed lattice nasopharyngeal swabs for COVID-19 tests.” Chen said they are using metamaterials strategy to improve the performance and the functions of structures in applications from defense to biomedical.” The 3-D nasal swabs in the research project have three key improvements: Using 3D printing for the swabs makes them more quickly available in the supply chain, helping with uncertainty of demand based on COVID -19’s ebbs and flows in infection rates. Secondly, improvement of structural properties so the swabs don’t break, and thirdly, increased accuracy and reliability due to redesign of the swab itself. With the seed grant funds, Chen said he hopes to add a new undergraduate student to the research team.
Dr. Luis Segura’s research interests in industrial engineering involve the integration of physics-based and data-driven models to optimize processes and product quality in advanced manufacturing. He received seed grant money for his project, “A Physics-based Machine Learning Framework for Smart Self-adaptable Multi-stage Manufacturing Systems.”
For Segura, who joined Speed School in spring 2022, The Jon Rieger Seed Grant would help to develop the foundation for the design, implementation, and validation of the physics-based machine learning SSMS (Smart Self-adaptable Multi-stage Manufacturing System) platform that will enable high manufacturing flexibility without compromising quality and productivity. “This will not only help to increase the performance and quality of manufacturing processes but also will generate a smart understanding of the entire system, which may lead to the modification/redesign and creation of new manufacturing systems in the virtual environment without incurring in the acquisition of expensive setups for preliminary results,” he said.
Dr. Sabur Baidya joined the University in July 2021, and directs the Autonomous Intelligent Mobile Systems Lab (AIMS Lab), conducting research in the CSE department in affiliation with Louisville Automation & Robotics Research Institute (LARRI). His funded project, “Collaborative Multimodal Sensor Fusion with Edge Intelligence for Connected and Autonomous Vehicles,” uses what is known as edge computing. “We basically integrate all the information gathered from the vehicle as well as its own sensor, and employ artificial intelligence-driven algorithms to provide more informed, more accurate and optimized decisions for all the road users,” said Baidya. The CSE professor, who worked as a postdoc researcher in California on smart vehicles, said in Kentucky, there are great opportunities to develop an infrastructure for connected and autonomous vehicles, both in terms of engineering and in terms of research.”
Dr. Tyler Mahoney, with the University less than a year, is already making his mark. Dr. Mahoney’s expertise lies in monitoring and modeling of hydrologic processes and water quality at the watershed scale. His seed grant project, “Quantifying the controls of streamflow permanence and sediment connectivity in urban headwater streams,” using Beargrass Creek watershed as a local case study, is focused on understanding where does sediment come from within watersheds and in particular how do small streams convey and transport sediments,” he said. Mahoney plans to use the seed grant money to hire some undergraduates or a graduate student for hourly work to help collect data. With preliminary data, he hopes to attract a federal partner to develop a proposal for additional external funding. “There are a number of federal research institutions that are very concerned with characterizing headwater streams, such as the US EPA and US Army Corps of Engineers, since they are the ones writing the policies that regulate whether or not a stream can be disturbed, he said. “In addition, the United States Geological Survey (USGS) is another potential partner.”
Dr. Xiaomei Wang joined Speed School in October 2021. Her research interests lie in applying human factors methods on human-AI teaming, decision making, healthcare, and engineering education. Wang received funding for her project, “Eliciting Expert Knowledge in Empirical Selection of Machine Learning Methods.” As her first awarded grant as a single PI (Primary Investigator), Wang said this is a milestone for her, and should help solicit additional dollars. “Once you can convince the external funding agencies you’ve committed to work on this topic, and you’ve already had some good results, I believe it will help me a lot,” she said. Wang’s project involves trying to understand the expertise of some data scientists or machining experts, she said. “This study offers two tracks of benefits for the field, according to Wang. “One is that after we collect the expert knowledge we can make a recommendation system, and two is that in asking the expert how they became experts it can benefit STEM education because data science is something everyone should know a little about,” Wang said. “I’m really thankful for this program.”