Grand Challenges Cohort

The Grand Challenges seed grant provides up to $200,000 for two fiscal years to support activities that develop large-scale interdisciplinary programs across the university. Projects must target a high-impact issue and include a plan to sustain the program for 5-10 years beyond the seed funding period.

Deadline: Anticipated Spring 2026

Kadi
Hudson Project

Development of Novel Screening Strategies and Drugs to Target Pathogenic Nematode and Protozoal Infections in Humans and Commercial Crops

Lead PI: Martin Hudson

Team: Martin Hudson, Soon Goo Lee, Whitney Preisser

Project Summary: Infectious diseases caused by parasites such as nematodes and malaria-causing protozoa have an incredible burden on global health. In addition, nematodes species that parasitize agricultural crops create an additional global burden. Drug resistance against parasitic nematode infections is evolving, demonstrating an unmet need for novel chemotherapy treatments. To address this, we have used bioinformatic tools to identify novel chemotherapy targets against nematodes, to validate them, and to utilize these as a platform to identify next-generation anti-nematode treatments for human, veterinary, and crop protection applications. To date we have generated X-ray crystal structures of a novel enzyme required for nematode viability, identified a short-list of candidate drugs that inhibit this enzyme, and begun to develop in vivo screening platforms to validate candidates for anti-nematode efficacy. 

Hopscotch

Hopscotch 4-All: Leveraging AI to Enhance Research Literacy in High School AP Research

Lead PI: Iv谩n Jorr铆n Abell谩n

Team: Iv谩n Jorr铆n Abell谩n, Nasrin Dehbozorgi, Mei-Lin Chang, Anete V谩squez, Xinyue Zhang, Olga Koz, Parandoosh Sadeghinia

Project Summary: Hopscotch 4-All is an innovative initiative aimed at transforming Advanced Placement (AP) Research education by making research literacy more equitable, accessible, and engaging. This open-access AI-powered recommender system leverages Large Language Models (LLMs) to guide high school students鈥攅specially those from underrepresented backgrounds鈥攖hrough the complexities of research design. 

By offering personalized and adaptive learning experiences, H4-All equips students with the skills and confidence to succeed in research and thrive in college-level academic environments. The project not only supports AP Research students but also enriches undergraduate education by bridging the gap between high school and college research expectations. 

MULISA

MULISA : mHealth-Enabled User-Friendly Light-Based Stroke Screening and Assessment in Pediatric Sickle Cell Disease

Lead PI: Paul Lee

Team: Paul Lee, Monica Swahn, Nazmus Sakib, Sangsun Choi

Project Summary: Stroke is a major risk for children living with sickle cell disease (SCD), and timely detection is critical for prevention. Our KSU-led project, MULISA is developing a portable, non-invasive device that uses light to monitor brain health and detect early signs of stroke risk. Powered by cutting-edge optical technology and supported by a mobile health (mHealth) platform, this low-cost tool can be used at the bedside, in schools, clinics, and community health settings, making stroke screening more accessible for both children with SCD and broader populations at risk. With support from the KSU Grand Challenge Seed Grant, our team has built and begun testing a working prototype. This research could transform how stroke is detected and prevented in everyday healthcare settings and showcases how KSU innovation is addressing real-world health challenges. 

Spoletini

SANDRApp - Supporting Adults Needing Direct Relationships App

Lead PI: Paola Spoletini

Team: Paola Spoletini, Maria Valero, Luisa Valentina Nino de Valladares, Israel Sanchez-Cardona

Project Summary: Stroke is a major risk for children living with sickle cell disease (SCD), and timely detection is critical for prevention. Our KSU-led project, MULISA is developing a portable, non-invasive device that uses light to monitor brain health and detect early signs of stroke risk. Powered by cutting-edge optical technology and supported by a mobile health (mHealth) platform, this low-cost tool can be used at the bedside, in schools, clinics, and community health settings, making stroke screening more accessible for both children with SCD and broader populations at risk. With support from the KSU Grand Challenge Seed Grant, our team has built and begun testing a working prototype. This research could transform how stroke is detected and prevented in everyday healthcare settings and showcases how KSU innovation is addressing real-world health challenges. 

Xu

Privacy Enhanced Embedded Deep Learning Module Design for Real-Time Drone-Aided Building Damage Reconnaissance

Lead PI: Honghui Xu

Team: Honghui Xu, Da Hu, Adeel Khalid

Project Summary: At 麻豆传媒社区, our research team is developing a privacy-enhanced, AI-powered drone system to rapidly assess building damage after natural disasters. Using aerial imagery collected by drones, our embedded deep learning model detects and classifies damage in real time鈥攅liminating the need for slow and risky manual inspections. This system not only speeds up emergency response but also protects sensitive visual data using certified differential privacy techniques. Seed grant funding has allowed us to build the first prototype, collect critical field data from recent disasters in Georgia and Kentucky, and prepare for multiple high-impact research publications. Our work supports safer, faster, and smarter disaster recovery efforts for communities nationwide.