Ohio State AI X Hub ignites cross-disciplinary discovery and real-world solutions

Ohio State launches AI (X) Hub across 15 colleges

On September 29, 2025, The Ohio State University announced the AI (X) Hub, a university-wide initiative spanning 15 colleges. The hub connects AI with six strategic pillars: foundations, health, engineering and sciences, agriculture, cybersecurity, and trustworthy AI. The effort supports President Walter "Ted" Carter Jr.'s Education for Citizenship 2035 plan and raises the bar for academic excellence.

The goal is clear: move ideas from hypothesis to validated systems faster and with greater reliability. The hub backs faculty, researchers, and students with shared compute, curated data, and cross-college collaboration focused on deployments that deliver public benefit.

What the AI (X) Hub provides

• Build a brain trust for AI: A collaborative research space where domain experts and AI scientists tackle complex problems and produce high-impact work.
• Shared, scalable infrastructure: Data/model commons integrated with high-performance computing clusters for broad access across medicine, science and engineering, social sciences, and the humanities.
• A connected AI ecosystem: Faster collaboration with entrepreneurs and industry to shorten the path from discovery to deployment.
• AI-driven solutions: Products and services from medical diagnostics to sustainable agriculture that create economic value and lasting societal benefits.

Six strategic pillars (X)

• AI foundations
• Health
• Engineering and sciences
• Agriculture
• Cybersecurity
• Trustworthy AI (governance, safety, fairness, reliability). See the NIST AI Risk Management Framework for reference: NIST AI RMF.

Leadership and direction

President Walter "Ted" Carter Jr. has made leadership in AI a core pillar of the Education for Citizenship 2035 strategy. Executive Vice President and Provost Ravi V. Bellamkonda notes the hub will connect faculty, staff, and students while accelerating innovation with clear ethical guardrails.

The hub is led by Ness Shroff, Ohio Eminent Scholar and internationally recognized expert in AI and networking. His mandate: link foundational research with use-driven projects-from decoding disease to resilient autonomous systems-so breakthroughs translate into measurable outcomes.

Why this matters to researchers

• Access to shared compute and data reduces redundant infrastructure and shortens experiment cycles.
• Data/model commons encourage reproducibility, baselines, and shared benchmarks across disciplines.
• Cross-college teams mean better problem framing, richer datasets, and clearer paths to deployment.
• Industry collaboration and translational support help move prototypes into clinics, fields, and factories.

How to engage (practical steps)

• Map your project to one pillar and define target outcomes (e.g., clinical metric, yield gain, security improvement).
• Prepare datasets with documentation: provenance, consent/IRB status, and intended-use notes.
• Plan evaluation up front: baselines, statistical tests, ablations, and error analysis.
• Adopt trustworthy AI practices (risk controls, monitoring, and bias audits). Reference: NIST AI RMF.
• Define translation-to-practice: pilots, regulatory pathway (where relevant), and post-deployment monitoring.
• Identify partners early: clinicians, growers, engineers, security teams, or public-sector agencies as needed.

Talent development: AI Fluency

Ohio State's AI Fluency initiative embeds AI education into the core undergraduate experience. Students across majors learn to use, question, and innovate with AI-building a talent pipeline that strengthens labs, startups, and public-sector projects.

Bottom line for PIs and research leads: If you're ready to move from papers to working systems, the AI (X) Hub offers the infrastructure, collaborators, and translation pathways to do it with speed and rigor.

If you are upskilling teams in data analysis with AI, see this concise, practical certification: AI Certification for Data Analysis.