New Computational Science Group formed at University of Findlay
University of Findlay is enhancing its computational capabilities in the College of Sciences, thanks in large part to a Super RAPIDS grant tied to Ohio’s 5G broadband initiative. To bolster its capacity for computational work, the university has invested in faculty with computational expertise and established a Computational Science Group led by Helen Schneider, professor and chair of the Department of Computer Science and principal investigator for the 5G grant.
The group includes at least seven faculty members specializing in areas such as artificial intelligence, cryptography and number theory, data science, drug discovery, clean energy materials, microwaves, and nanotechnology. The grant has facilitated the acquisition of advanced hardware and software to support education, workforce training, and research, while fostering collaborations with industry and regional partners.
Among the new resources is the University’s most powerful workstation, featuring an AMD Ryzen Threadripper 7960X 24-core, 48-thread CPU, and 256GB of RAM running on a Linux operating system. A second workstation with 512GB of RAM is also being acquired. Specialized software such as COMSOL, Gaussian, and MATLAB has been installed to address engineering and physical science challenges.
The expanded resources have enabled impactful research across disciplines. Daniel Osborne’s computational group is focused on drug discovery, specifically targeting the S1P_S1PR axis in cancer metastasis. Sphingosine-1-phosphate (S1P) promotes tumor activity in 80% of S1P receptors, and Osborne’s team, which includes five undergraduate STEM students, is developing drug classes to inhibit receptor activation. The group is also building collaborations with the College of Pharmacy.
In materials science, Steven Wild uses Gaussian software to calculate the electronic and material properties of molecular systems, with applications in electronics, solar cells, and pharmaceuticals. In clean energy, research is underway to uncover the mechanisms behind triboelectric phenomena to improve the efficiency of green energy sources.
Data science applications include Dr. Dominic Wilson’s work on leveraging advanced computational methods in data science and knowledge engineering to tackle computer security challenges. In the Department of Mathematics, Daniel Baczkowski and his students are using computational methods to search for the smallest Sierpiński and Riesel numbers, which have cryptographic significance.
The evolution of computing, alongside experimentation and theory, has transformed scientific research and societal applications, including the internet and artificial intelligence. With funding from the State of Ohio, the University of Findlay now offers exceptional computational resources to benefit its students, faculty, and community partners.
To learn more about the College of Sciences at University of Findlay, Visit the college’s website.
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