Fourteen Ohio State research teams have been awarded funding through the President’s Research Excellence (PRE) program in the latest cycle. The PRE program provides seed support to catalyze and accelerate multidisciplinary, interdisciplinary or convergent research teams pursuing external funding. Administered by the Enterprise for Research, Innovation and Knowledge (ERIK), the program awards up to $2.5 million per year through two tiers of grants.
Catalyst Grant Awardees
Catalyst grants are awarded to medium or large teams of three to five investigators representing three or more distinct disciplinary perspectives that are formed to pursue high-impact research towards an identified national-leadership level or highly strategically significant proposal target.
Unlocking the Spinal-Immune Axis: Foundational Mapping and Computational Modeling for a New Paradigm in Neuroimmunology
Lead PI: Phillip Popovich (College of Medicine)
Co-investigators: Eugene Oltz and Qin Ma (College of Medicine)
Project description: This project maps a novel spinal "immune synergy encoding" network, challenging the dogma that only the brain controls systemic immunity. Using 3D mapping and multi-omics to build a computational model (NIGI), the group aims to unlock new bioelectronic treatments for immune diseases.
Kinetic Plasma Control Models for Defense and Space Application
Lead PI: Fernando Teixeira (College of Engineering)
Co-investigators: Debdipta Goswami and Shanker Balasubramaniam (College of Engineering)
Project description: Plasma-based devices are critical components in defense and space applications. This effort will develop transformative computational tools and create new model-predictive real-time control for plasmas systems and devices in those applications.
Causal Systems Science: Bridging Impact Evaluation and Population-Level Predictions in Coupled Human-Environment Systems
Lead PI: Grzegorz Rempala (College of Public Health)
Co-investigators: Qianying Lin and Denis Tverskoi (College of Public Health); Daniela Miteva (College of Food, Agricultural and Environmental, Sciences); and Andrew Perrault (College of Engineering)
Project description: Proposal develops causal systems science to integrate causal inference, agent-based simulation and genomic data for modeling human–environment health dynamics. Using Lyme disease in Ohio, it links land use, behavior and transmission to support scalable prediction and NIH RM1 proposal submission.
XR-Enabled Remote Mentoring for Space-Relevant Medical Contingency Response
Lead PI: Hussam Salhi (College of Medicine)
Co-investigators: Nicholas Kman (College of Medicine); Mark Weir (College of Public Health); Jeremy Patterson (College of Arts and Sciences); Abigail Harrison (College of Engineering); and Michael Dial (Enterprise for Research, Innovation and Knowledge)
Project description: This project seeks to deliver the foundational components of a next generation XR system that enhances skill acquisition, reduces cognitive load, and improves mission critical medical readiness for defense, commercial space, and other extreme operational domains.
Accelerator Grant Awardees
Accelerator grants are reserved for small teams formed to pursue curiosity-driven, novel, high-risk and high-reward research.
Guided Ion Transport Across Hybrid Interfaces Toward Adaptive Energy Storage
Lead PI: Yiying Wu, Professor (College of Arts and Sciences)
Co-Investigator: Xiaoguang Wang (College of Engineering)
Project Abstract: This project uses liquid-crystal-templated polymer electrolytes to control chain alignment at inorganic solid-electrolyte interfaces, probing how orientation and temperature-driven order–disorder transitions tune heteroionic resistance and enable self-throttling, thermally safe solid-state batteries.
Advanced Membrane-Based Emulsions from Black Soldier Fly Lipids to improve Anti-Inflammatory and Anti-Cancer Efficiency
Lead PI: Emmanouil Chatzakis (College of Food, Agricultural, and Environmental Sciences)
Co-Investigators: Silvia de Lamo Castellvi (College of Food, Agricultural, and Environmental Sciences); and Ouliana Ziouzenkova (College of Education and Human Ecology)
Project Abstract: This project focuses on advancing the use of black soldier fly lipids as a sustainable source for the development of oil/water emulsions with enhanced bioactivity against inflammation-related chronic diseases, using scalable encapsulation technologies to preserve lipid composition and functionality.
Modeling Disease Trajectory in Huntington’s Disease Using Speech-Derived Digital Biomarkers
Lead PI: Simon Lageniere (College of Medicine)
Co-Investigator: Changchang Yin (College of Medicine)
Project Abstract: This project develops a speech-based digital biomarker to measure individual disease progression in Huntington’s disease over 12 months. We will test whether movement along a clinically anchored speech-derived metric detects short-interval progression beyond measurement noise.
Bioengineering a human extracellular matrix biomaterial product for advanced cell and tissue culture
Lead PI: Aleksander Skardal (College of Engineering)
Co-Investigator: Priya Dedhia (College of Medicine)
Project Abstract: Bioengineered cellular models used for drug development and disease modeling are generated using hydrogel biomaterials derived from the tissue of mouse tumors that suffer from batch to batch variability. The team has developed a human cell-based biomaterial that is produced in a controlled manner.
Discovery of natural products to control Lyme disease vectors
Lead PI: Peter Piermarini (College of Food, Agricultural, and Environmental Sciences)
Co-Investigator: Troy Koser (College of Veterinary Medicine)
Project Abstract: The goal of the proposed research is to discover natural product pesticides for controlling ticks that transmit Lyme disease. The project will use both lab and semi-field bioassays to identify the most promising natural products to control ticks.
Precision-Targeted, pH-Responsive ZIF-8 Nanocarriers for Temozolomide Delivery for Glioblastoma Tumors
Lead PI: Nicholas Brunelli (College of Engineering)
Co-Investigators: Katelyn Reilly (College of Engineering) and Buddini Iroshika Karawdeniya (College of Engineering)
Project Abstract: The team is developing targeted drug delivery vehicles for treating glioblastoma. The collaboration brings together a variety of expertise, including scalable nanomanufacturing, drug delivery, surface modifications and cancer models.
Dissecting the Coupling Between Neural Circuit Stability and Local Metabolic Demand using a Multimodal Implantable Platform
Lead PI: Lin Du (College of Medicine)
Co-Investigators: Laurence Coutellier (College of Arts and Sciences); and Megan Keiser (College of Medicine)
Project Abstract: This project will develop a fully implantable wireless platform to simultaneously measure tissue oxygenation and neural activity in freely behaving mice, establishing an energy-resolved framework for studying circuit stability and advancing leadership in brain-machine interface technologies.
Practical On-Farm Experimentation: Leveraging Spatial Statistics and Minimal Replication
Lead PI: Jie Hu (College of Arts and Sciences)
Co-Investigator: Elizabeth Hawkins (College of Food, Agricultural and Environmental Sciences)
Project Abstract: Farmers want to conduct on-farm experiments to test treatment choices specific to their own fields but are blocked by the lack of experimental design and analysis tools. This team develops such tools to empower farmers to make data-informed management decisions using on-farm experiments at low cost.
Investigating the role of Adipose Tissue-Derived Extracellular Vesicles as Drivers and Biomarkers of Cardiometabolic Risk After Spinal Cord Injury
Lead PI: Andrea Tedeschi (College of Medicine)
Co-Investigator: Emanuele Cocucci (College of Pharmacy)
Project Abstract: Spinal cord injury increases cardiometabolic risk, partly through dysfunction of perigonadal white adipose tissue (pWAT). The team will investigate pWAT derived extracellular vesicles as biomarkers of adipose dysfunction and potential drivers of metabolic complications after SCI.
Reporting-Ready Cardiac MRI Foundation Model for Automated Ventricular Quantification
Lead PI: Yuan Xue (College of Medicine)
Co-Investigator: Yuchi Han (College of Medicine)
Project Abstract: This project will develop a reporting-ready cardiac MRI AI model for automated ventricular quantification from routine cine CMR and linked clinical reports. Deliverables include a reproducible preprocessing/extraction pipeline, a validated baseline model, and R01-ready preliminary data.