Enterprise for Research, Innovation and Knowledge

Eleven research projects funded through the President’s Research Excellence Program Accelerator Grants

July 10, 2024

Ohio State has invested nearly $550,000 in eleven interdisciplinary Ohio State research teams in the most recent cycle of the President’s Research Excellence (PRE) program. The Accelerator awards of up to $50,000 each are designated for small teams formed to pursue curiosity-driven, novel, high-risk and high-reward research. 

In total, through the PRE program, Ohio State has invested nearly $6.5 million in 78 teams of Ohio State investigators since its inception in 2021.

The PRE program also provides Catalyst grants, which further help position Ohio State for leadership in key areas of research. These grants of up to $200,000 each to fund large, cross- and interdisciplinary teams pursuing large-scale, high-impact research that addresses emerging or existing challenges of national and international societal importance and generates long-term, sustained, and significant impact.

Spring 2024 Accelerator Grant Recipients

Dissecting how glial expression of voltage-gated calcium channel subunits suppress adult oligodendrogenesis in the central nervous system

  • Lead PI: Wenjing Sun (College of Medicine) 
  • Co-PIs: Steffen Lindert (College of Arts and Sciences); Ilaria Palmisano (College of Medicine)
  • Project description: Myelination is crucial for the central nervous system (CNS) function. However, the mechanisms underlying myelin formation are not yet fully understood. This project aims to investigate the underlying mechanisms by which glial expression of calcium channel subunits regulate adult oligodendrogenesis.

Building Interdisciplinary Opportunities (BIO)-Astronautics: A Case Study Utilizing Dust as a Nutrient Source for Plant Production to Move Towards a University Bioastronautics Center 

  • Lead PI: Karen Dannemiller (College of Engineering) 
  • Co-PIs: John Horack (College of Engineering); Jonathan Jacobs (College of Food, Agriculture, and Environmental Sciences)
  • Project description: The aim of this project is to provide the opportunity for a case study to use a waste product generated in all human occupied spacecraft, dust, as a resource to support long-duration missions in and beyond low-Earth orbit (LEO) and build toward creation of a Bioastronautics center on campus.

User-Aligned Fair Machine Learning for Automated Hiring

  • Lead PI: Xueru Zhang (College of Engineering) 
  • Co-PIs: Bingjie Liu (College of Arts and Sciences); Kaifeng Jiang (College of Business)
  • Project description: This project aims to conduct human subject studies to understand human perceptions of hiring algorithms and different notions of fairness. Based on such understanding, design human-aligned fair machine learning algorithms for multi-stage automated hiring. 

Diet-related risk factors for postoperative cognitive impairment in older individuals 

  • Lead PI: Michelle Humeidan (College of Medicine)
  • Co-PIs:  Martha Belury (College of Food, Agriculture, and Environmental Sciences); Ruth Barrientos (College of Medicine)
  • Project description: This pilot study will enroll geriatric surgical patients and explore potential relationships between diet, levels of inflammation, and presence of perioperative cognitive dysfunction.      Patient-reported considerations for future study of behavioral/dietary interventions will also be collected.

Transformation of Operational Wildland Fire Behavior Models through Novel Sensing and Data-Driven Regional Adaptations

  • Lead PI: Mrinal Kumar (College of Engineering)
  • Co-PIs:  Gil Bohrer, Sandip Mazumder (College of Engineering); Roger Williams (College of Food, Agriculture, and Environmental Sciences) 
  • Project description: This proposal will transform operational wildfire prediction models. Operational models will be regionally adapted using novel, multimodal field-data collected during prescribed burns, and high-fidelity multiscale simulations of combustion and radiation processes.

 Data Infrastructure for Video Analysis of Political Speech 

  • Lead PI: Skyler Cranmer (College of Arts and Sciences)
  • Co-PIs:  Swati Padhee, John Paparrizos (College of Engineering) 
  • Project description: This proposal has two key components of merit: the creation of a robust and open-source pipeline for the gathering and processing of video data and the creation of a comprehensive corpus of 21st-century video speeches delivered by heads of state.

 Digital Transformation of CRC Screening: Revolutionizing Access and Saving Lives

  • Lead PI: Aldenise Ewing (College of Public Health)
  • Co-PIs:  Subhankar Chakraborty, Emre Sezgin (College of Medicine) 
  • Project description: This project targets low CRC screening rates by adapting CARES into a digital platform. Collaborative co-design and usability testing will ensure a user-centered intervention. This project paves the way for a future R01, advancing the goal of reducing CRC disparities with digital health solutions.

 Transforming watermelon rinds into a functional food

  • Lead PI: Yael Vodovotz (College of Food, Agriculture and Environmental Sciences)
  • Co-PIs: Osvaldo Campanella (College of Food, Agriculture, and Environmental Sciences); Thomas Knobloch (College of Public Health) 
  • Project description: This transdisciplinary team is proposing to ferment watermelon rind followed by extrusion processing to transform this waste product into a highly nutritious functional food while diverting this waste from the landfill. The process will be modeled by Triple Bottom Line to assure sustainable practices

 Treatment-Related Cardiotoxicity Prevention in Breast Cancer Patients in Active Treatment: Patients Journey Map and Their Interaction with A Smart Speaker-Based Voice Assistant

  • Lead PI: Weidan Cao (College of Medicine)
  • Co-PIs:  Jingbo Meng (College of Arts and Sciences); Daniel Addison (College of Medicine) 
  • Project description: There is a critical need to define early detection and prevention strategies to reduce the cardiotoxic events due to anti-cancer therapies. This team will conduct a patient journey map among breast cancer patients and conduct an explorative study on the patients’ interaction with a smart speaker.

 Utilizing a mitochondria-targeting small molecule as a therapeutic for neuronal restoration and protection in neurodegenerative disease 

  • Lead PI: Russell Lonser (College of Medicine)
  • Co-PIs:  Luis Bonet-Ponce, Anthony Otero, Victor Van Laar (College of Medicine) 
  • Project description: There is a clinical need for a disease-altering therapy in neurodegenerative Parkinson's that can address disease throughout the body.      This team has identified a potential candidate, a small molecule that targets the mitochondria that exhibits neuroprotective properties, that will be evaluated.

 Artificial Intelligence for Pre-operative Prediction of Prolonged Air Leak After Pulmonary Resection

  • Lead PI: Peter Kneuertz (College of Medicine) 
  • Co-PIs:  Christopher Davis, Robert Merritt (College of Medicine)
  • Project description: This multidisciplinary study involves Thoracic Surgery, Radiology and Computer Science to tackle a common clinical problem. The team aims to develop a novel prediction model for postoperative air leaks after lung surgery leveraging artificial intelligence trained imaging analysis using routine CT scans.