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Research & Programming

Artificial Intelligence Impact Atlas (AIIA)

About Research Team

Overview

This project develops a novel methodological approach to empower business leaders, policymakers, and their constituents with easy-to-use tools to understand the impact of AI on the workforce and to help them prepare for the future.

The project team, including additional scientists and members of the Weldon Cooper Center, will

  1. develop an AI-assisted modeling and analytical platform to represent and analyze the rapidly changing labor, economic, and technological landscape and study the impact on job displacement, augmentation, and more broadly, the cascading impact of these changes;
  2. enhance the current user-friendly decision-support system;
  3. engage end users and carry out user studies; and
  4. publish policy documents detailing the progress.

Research Team

Headshot of Kemi Jona

2026-27 AI & Democracy Grant Recipient

Kemi Jona

Kemi Jona is the Vice Provost for Online Education and Digital Innovation at the University of Virginia, where he collaborates with internal and external partners to refine and implement the University’s digital education strategy and helps to shape UVA’s vision for online education and seamless, lifelong learning pathways for all learners. Dr. Jona has worked at the forefront of the learning sciences and learning technologies fields for over 25 years. He is a thought leader in applying insights from cognitive and learning sciences to the design of technology-mediated learning environments and in developing innovative partnerships and pathways to increase access to opportunity.

Full Profile

2026-27 AI & Democracy Grant Recipient

Madhav Marathe

Affiliations

  • Executive Director, Biocomplexity Institute
  • Distinguished Professor of Biocomplexity
  • Professor of Computer Science

Bio

Madhav Marathe is an endowed distinguished professor of biocomplexity, executive director of the Biocomplexity Institute, and a tenured professor of computer science at the University of Virginia. Marathe is a passionate advocate and practitioner of transdisciplinary team science. During his thirty year professional career, he has established and led many large transdisciplinary projects and groups. His areas of expertise include digital twins, network science, artificial intelligence, multi-agent systems, high-performance computing, computational epidemiology, biological and socially coupled systems, and data analytics.

His prior positions include professor of computer science and director of the Network Dynamics and Simulation Science Laboratory within the Biocomplexity Institute of Virginia Tech and a team leader of research and computing in the Basic and Applied Simulation Science Group, Computer and Computational Sciences Division at the Los Alamos National Laboratory. He is a fellow of the American Association for the Advancement of Science, Society for Industrial and Applied Mathematics, Association for Computing Machinery, and Institute of Electrical and Electronics Engineers. Marathe has published more than 500 articles in peer-reviewed journals, conferences, and workshops. Mentoring and training next-generation scientists has been his lifelong passion. He has mentored more than a dozen staff scientists, and (co)-advised more than thirty doctoral students, twenty MS students, and fifteen postdoctoral fellows.

Marathe and his team focus on developing the scientific foundations and the associated engineering principles to study large-scale biological, information, social, and technical (BIST) systems. His current interests span five broad themes: (i) methods to construct various BIST networks using partial and noisy data as well as procedural information; (ii) understanding the general form and structure of dynamical processes over BIST networks (e.g., key network/pathway properties and typical pathways that impact dynamics); (iii) algorithmic theory of optimization and control as it pertains to the dynamical processes, including methods to detect, enhance, arrest, and mitigate dynamics; (iv) general conceptual and algorithmic foundations to understand the co-evolution of the networks and dynamics; and (v) high-performance services-based computing solutions that can be delivered seamlessly to end users and policymakers.

Full Profile
Headshot of Anil Vullikanti

2026-27 AI & Democracy Grant Recipient

Anil Vullikanti

Anil Vullikanti is a professor in the department of computer science and Biocomplexity Institute at the University of Virginia. His interests are broadly in AI and machine learning, algorithms, optimization and distributed computing and their application to public health, social networks and sociotechnical systems.

Full Profile

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