Northwestern Network for Collaborative Intelligence Announces Strategic Leaders
Experts will focus on three pillars of AI and data science: Research, Education and Infrastructure
This past summer, the Northwestern Network for Collaborative Intelligence (NNCI) was launched with the goal of advancing responsible, high-impact, world-class research and education in data science and artificial intelligence at Northwestern. Now, NNCI is pleased to announce the appointment of five impactful leaders from across the University who will helm NNCI’s three strategic pillars — Research, Education and Infrastructure — and guide human‑centered AI innovation across Northwestern.
The Education Pillar will be co-led by Jeremy Gilbert (Medill) and Sara Owsley Sood (McCormick). The Research Pillar will be co‑led by Scott Budinger (Feinberg) and Chris Wolverton (McCormick). The Infrastructure Pillar will be guided by Joseph Paris (Northwestern IT).
“This is a group that brings wide‑ranging expertise, from pedagogy and curriculum design to materials science, clinical research, enterprise technology and AI governance,” said NNCI founding co-director V.S. Subrahmanian.
“Their collective leadership will help NNCI strengthen interdisciplinary collaboration, foster responsible AI practices and support innovative teaching and research across Northwestern,” said NNCI founding co-director Abel Kho.
Shaping Northwestern’s approach to AI‑infused teaching and learning
“AI presents a transformational moment for higher education,” said Gilbert, the Knight Professor in Digital Media Strategy at Medill. His goal is to empower faculty, create new AI‑related degrees and certificates, share best practices, expand equitable access to AI tools and position Northwestern as a leader in AI‑enabled pedagogy.
As associate chair for undergraduate education at McCormick, Sood brings extensive experience in computer science education, cross‑school curriculum design and the development of scalable applied AI learning opportunities.
“It is critically important to help our students both gain deep expertise in AI and meaningfully integrate AI tools into their academic work across disciplines,” Sood said.
Together, Gilbert and Sood will help the University navigate both the structural and cultural shifts required to teach effectively in an AI‑driven world.
Lowering barriers to collaboration while advancing Northwestern’s research mission
As chief of pulmonary and critical care in the Department of Medicine at Feinberg, Budinger brings exceptional leadership in translational clinical research.
“I am motivated by the many opportunities we have to unite clinicians, engineers and data scientists around shared data platforms, ethical data‑sharing ecosystems and high‑impact projects — all to address pressing biomedical challenges,” he said.
As the Frank C. Engelhart Professor of Materials Science and Engineering, Wolverton brings deep expertise in AI‑accelerated scientific discovery, including work in computational materials science, high‑throughput simulations and the development of large‑scale materials data resources. He envisions Northwestern as a global leader in interdisciplinary AI research, “where teams integrate domain knowledge with algorithmic innovation to accelerate discovery.”
Together, Budinger and Wolverton aim to lower barriers to collaboration, strengthen research infrastructure and support ideas that advance Northwestern’s research mission.
Building a cohesive and accessible infrastructure ecosystem
As associate vice president of Northwestern IT, Paris brings experience centered on alignment across units, integrated services, adaptability to emerging technologies and strong partnerships with Northwestern’s research and education units. He will develop the technical and organizational foundations that make AI research and education sustainable and responsible.
“Northwestern’s research and academic communities benefit from a cohesive and accessible infrastructure ecosystem,” he said. “Our shared aim is to ensure that faculty, students and researchers have clear pathways to computing resources, data environments, AI tools and the expert support needed to use them effectively.”