UIC graduate students receive Outstanding Thesis and Dissertation Award

University of Illinois Chicago Richard and Loan Hill Department of Biomedical Engineering alumnus Giuseppe Lauricella received the Graduate College’s annual Outstanding Thesis and Dissertation Award. The award was given in recognition of his master’s thesis “Computational Study of Inertial Migration of Prolate Particles in a Straight Rectangular Channel.”

BME alumnus Kaustubh Pachpor also received an honorable mention from the Graduate College’s annual Outstanding Thesis and Dissertation Award. Pachpor was recognized for his master’s thesis, “Multi-omics Metabolic and Microbiome Profiling of Mouse Pregnancy (MOMMI-MP): Database for Integrated Analysis of Metabolic and Microbiome Profiling of Mouse Pregnancy.”

Lauricella’s thesis focused on understanding the effect of the shape of particles as the equilibrium position of a microfluidic device is influenced by many factors.

In particular, he modeled prolate ellipsoidal particles, spheroids with an elongated shape, which have not been heavily explored. Most of the connecting literature has discussed spherical particles, which are easy to manufacture and model. Lauricella ran systematic in silico experiments to have better control over the variables within the tests, performed by Richard and Loan Hill Professor Ian Papautsky’s group.

As a result, Lauricella and his team, including his advisor Assistant Professor Zhangli Peng, Papautsky, Research Assistant Professor Jian Zhou, and Ph.D. student Qiyue Luan, were able to better categorize the behavior of ellipsoidal particles including how they flow and rotate in the microfluidic channel. His researchrevealed a unique rotational behavior of prolate particles. Under specific conditions, while flowing downstream, the particle can undergo a so-called “logrolling” motion, instead of the commonly reported “tumbling” motion.

They employed a numerical method called smoothed particle hydrodynamics, or SPH. While able to provide many details and insights into the underlying physics of the phenomenon, this method is computationally expensive and needs powerful computer equipment. Lauricella and his team used the Theta supercomputer at Argonne National Laboratory to complete simulations.

After graduating with his master’s in biomedical engineering, Lauricella continued his work with Peng and Papautsky to expand the work of his thesis. In doing so, they did fundamental research about fluid dynamic forces, including how the particles behave and how they move, to aid the development of new particle enrichment methods, useful for cell separation and diagnosis. As a result, this additional work was submitted to the Journal of Fluid Mechanics, the leading journal in fluid mechanics.

Lauricella was part of the dual degree program between UIC and Politecnico di Milano in Italy.

He graduated in 2022 and is currently pursuing a PhD in molecular engineering at the University of Chicago. His PhD primarily focuses on the interaction of the human microbiota and cancer. During his time as a master’s student, the publication of his thesis findings in the Physics of Fluids journal was selected as an editor’s pick as well as he presented the findings at various conferences including the 2022 MicroTAS conference in China virtually and the American Physical Society’s Division of Fluid Dynamics in Indianapolis.

Pachpor’s thesis was focused on finding the interactions between the microbiome and the metabolome in mouse pregnancy.

With existing research, “it was found that during pregnancy [in mice], there were some alterations and variations in the microbiome, which gave rise to gestational diabetes,” Pachpor said. “Since the previous study had a large amount of data, it was a perfect opportunity for me to make use of that data and perform statistical analysis, use neural network models, and machine learning to find sets of microbes and metabolites that were responsible for causing alterations in the insulin levels in mice during pregnancy.”

Part of Pachpor’s thesis was to build a database for other researchers. In doing so, he and his advisors, Professor Yang Dai and Brian Layden, UIC College of Medicine professor and chief of the Division of Endocrinology, Diabetes, and Metabolism, aimed to share the results as “they should not just be limited to us, but we wanted to make it public for other researchers,” Pachpor said.

The MOMMI-MP database consists of more than 4,000 results, which provides a source to browse and search differential abundant microbial taxa, metabolites, metabolic pathways, predicted micro-metabolite interactions using an array of state-of-art statistical and machine learning models. It also includes data about how they vary during the gestation period and the postpartum period of the mouse. In the future, if researchers wish to use this data, Pachpor noted, they can visit the website and find different interactions between any microbial metabolite that is related to pregnancy and the gut microbiome.

MOMMI-MP is a resource to facilitate the investigation of novel mechanisms governing metabolic changes during pregnancy.

He graduated from UIC with his master’s degree in bioinformatics in August of 2023 and is currently working for a company performing statistical analysis. Pachpor completed his undergraduate degree in India, where he is from, and chose to attend UIC because of its connections to the Chicago Medical District and its standing as the best public research university in Illinois. He plans to eventually earn his PhD and contribute toward human betterment, particularly in the medical sector.

Pachpor holds a patent for a groundbreaking mortality prediction system with Explainable Artificial Intelligence. He also presented his work on early Japanese Encephalitis prediction at the 2020 International Conference on Computational Intelligence in Malaysia during his undergraduate education.