Initiatives - LaCross AI Institute

LaCross AI Institute

Initiatives - LaCross AI Institute

Initiatives

The LaCross Institute is home to activities of many kinds that support our mission to make the world a better place through the responsible use of AI in business.  

LaCross Institute initiatives focus on faculty and students at Darden and across UVA, managers and leaders in business, and on the community and society at large.  Initiatives are the major activities that are formally supported by the Institute.  In addition to key these stakeholders, Initiatives also align with our focus areas and serve to ensure that the insight and expertise we develop on these key topics is shared with key audiences to enhance their knowledge of AI and their ability to develop and employ it ethically.  

For more about our major initiatives, explore the information below.

Fellowships in AI Research (FAIR) Program

The UVA Darden LaCross AI Institute invites applications from UVA faculty for the 2026 Fellowships in AI Research (FAIR) Program. 2026 Fellowships are expected to be awarded in January 2026.

The LaCross AI Institute was established in 2025 with the mission to make the world a better place through the responsible use of AI in business by developing leaders who can manage AI businesses and solutions, guided by ethics, values, and the advancement of human well-being.  As part of this mission, a key emphasis is on collaboration across disciplines, including to advance academic research and knowledge creation on timely and important topics in ethical AI in business where such collaboration may accelerate progress or lead to novel approaches and solutions.

The Fellowships in AI Research program, which originally launched under the Darden-Data Science Collaboratory (DCADS) in the fall of 2023, is now organized by the LaCross AI Institute.  It is the Institute’s primary vehicle to pursue and support collaboration in research. It is designed to support scholars, practitioners and UVA students who are, or intend to be, engaged in research that has beneficial practical outcomes and provides the foundation for substantive future work.  The FAIR Program is structured to provide initial funding for work that is conducted within the University of Virginia, as a collaboration among UVA faculty, staff and students, representing multiple disciplines.  The program is also open to others in Virginia provided the work is led by UVA affiliated faculty.

We invite all applications covering the broad spectrum of topics related to ethical AI in business. However, for 2026, we will give preference to proposals that align with one of the following topics of interest:

  • Bias and Misinformation: Exploring algorithms and data-intensive business practices that increase equity and promote truthfulness in business and in society using AI.
  • Analytical Leadership: Leading and managing individuals, teams, and organizations amidst the near ubiquity of data and technology that enable the use or misuse of AI, including organization structures and management approaches, performance measurement and evaluation, optimal worker/work alignment, agents and AI-human teaming, workforce and societal impacts, value realization, and more. 
  • Human ↔ AI Performance: Understanding and enhancing human performance using AI and machine learning, and evaluating and advancing AI performance using insights and understanding from the study of performance in humans.
  • Data privacy & Ethical AI: Understanding the role of data privacy and data ethics, and developing tools and management approaches to ensure they are prominent considerations in the development and deployment of ethical AI.
  • Value Chain of Ethical AI: Exploring the business and ethical issues that arise in the system of interrelated, stakeholders, businesses and capabilities that comprise AI - including data, models, applications, management, outcomes and the infrastructure and people that enable them - as well as the potential solutions and value that a systems perspective may unlock. 

To view more information about this fellowship, please review our PDF

*Applications for the 2026 cohort are now closed. 

 

FAIR Information

The fellowship will support a research project in ethical artificial intelligence of significance to scholars and practitioners in business. The ideal project is aligned with one of the above topics and involves collaboration among multiple disciplines to address a program or opportunity in a novel way. The intent is to highlight disciplines, develop or apply methods, and pursue approaches to ethical AI that may be unfamiliar or inaccessible in the individual disciplines that conduct research in ethical artificial intelligence. The goal os the FAIR Program is to produce output that demonstrates the efficacy of such collaboration in identifying novel solutions and unique pathways for continued future research. 

Fellowships may include UVA and non-UVA faculty as Faculty Fellows, current and new UVA students as Student Fellows, and non-academic practitioners and other experts as Practitioner Fellows.  Proposed projects must be led by a member of the UVA faculty serving as Principal Investigator.

FAIR Fellows will join and have recognized standing as part of the UVA Darden and UVA Data Science communities, and potentially others across UVA, during the Fellowship.  

The primary activities of the Fellows will be those research-related activities that are necessary for completion of the proposed project, including as originally defined and as subsequently modified by agreement during the Fellowship.  

Secondary activities may include participation in seminars, classes, meetings, etc. with faculty, students and staff at UVA Darden, UVA Data Science, and in the UVA community at large, including at other UVA schools and units that are usefully related to the proposed project.

Faculty Fellows will be responsible for overseeing the work of others involved in the proposed project, including Post-doctoral Fellows, Student Fellows (doctoral or graduate students, NOT including undergraduate), Practitioner Fellows (individuals from business or other experts, etc.) and associated research staff (e.g., research assistants or support) who may be hired using Fellowship funds.  

Fellows are not expected to be in residence at UVA on a continuous basis, but will be expected to spend 2-3 periods in Charlottesville during the duration of the Fellowship.  During the rest of the Fellowship, they must be accessible remotely as necessary to ensure the successful completion of the proposed project.  Additional residency in the Charlottesville, Virginia area may be proposed, but Fellowship funding is not available to cover further residency-related expenses.

Fellows are expected to complete the activities and produce the outputs as agreed upon in the project proposal.  

Fellows will be required to present their work/or conduct public and private workshops and participate in related events to further disseminate their work. They may include virtual and/or in-person engagements. Fellows should identify themselves as recipients of the UVA LaCross AI Institute Fellowship in AI Research (FAIR) Program during the timeframe of the fellowship. Fellows should identify their work within this program as supported by the UVA LaCross AI Institute Fellowship in AI Research (FAIR) Program or other language as appropriate to the setting. 

Fellows are expected to be aware of and to adhere to UVA policies and guidelines that are relevant to their work as Fellows of the LaCross AI Institute.

The proposed project must be led by a UVA faculty member. Additional team members may be affiliated with other academic institutions and/or businesses with a presence in Virginia.

Proposed projects must be new work and not previously completed or published.

Project outputs should include, at a minimum, a paper, article, presentation or other document that is suitable for dissemination to a scholarly audience, such as through a peer-reviewed journal in artificial intelligence, data science, or business, or another venue as proposed and agreed.

Work is expected to be sufficient in quality and other respects so as to be useful in subsequent proposals for funding from public or private sources.  

FAIR Fellowships are generally 18 months in duration, but the duration may be modified to fit the timeline of a proposed project.  All proposed activities and outputs are expected to be completed during the duration of the Fellowship.

The funds for the fellowships are provided by the LaCross AI Institute. Each fellowship will include a maximum of $100,000 in total funding. Of this amount, $75,000 must be used for student-related expenses, including funding Student Fellows such as existing or new student researchers (post-doc, Ph.D, masters), covering student travel, conference fees, etc. and providing necessary resources such as data, software, training, compute, storage, etc. In addition, applicable fringe will also be covered. The remaining $25,000 can be used for any project-related expense at the Principal Investigator's discretion. All funds must be utilized as described in the submitted and accepted fellowship proposal.

For Faculty: Any full-time faculty member from the University of Virginia with any school or department and of any academic rank. Faculty in the fields of artificial intelligence, ethics, data science or business will be given preference, as will collaborations between faculty representing multiple disciplines and/or UVA units.  

For Non-faculty: Experienced practitioners and other non-academic professionals with more than 10 years of experience in artificial intelligence, data science or business. UVA Darden and UVA Data Science alumni will be given preference. 

FAIR Fellowship recipients must meet UVA work eligibility requirements.

Note that LaCross AI Institute leadership (e.g., Directors, etc) and members of the selection committee are not eligible to participate. 
 

26 September 
10 October
24 October
7 November 
21 November
19 December
2 January

All information sessions start at 1 p.m. 
Information sessions are conducted through the Zoom link here.

Anyone may nominate candidate(s) for the FAIR Program, however nominations are optional.  Direct applications from qualified individuals are encouraged.

If you would like to nominate someone else for the FAIR Program, please email the following to fair@darden.virginia.edu:

1.       Your name and contact information,

2.       The name and contact information of the person you are nominating,

3.       A short statement (500 words max.) of why you are making this nomination and what you expect the nominee will contribute if he or she is selected for this Fellowship.

A LaCross AI Institute representative will review all nominations and invite qualified individuals to submit an application for the 2026 FAIR Program.

Nomination deadline: 30 November 2025

To apply for the 2026 FAIR Program, individuals must submit the following information using the Application link on the LaCross AI Institute website. Note that a nomination is not required.

  1. An abbreviated CV (3-pages maximum) for each Faculty member in the project proposal,
  2. A project proposal that addresses the following at a minimum (5 pages maximum)
    • An overview of your proposed project,
    • A summary of the plan, timing and approach that you intend to follow,
    • A preliminary list or table of the resources (e.g., students, research staff, data, computing, etc.) and associated budget that you require (note that requested budget may not exceed $100,000 but may be less),
    • What type of UVA student resources (e.g., Post-doc, PhD, Masters) you intend to use,
    • What role, work, and other activities you expect the student(s) to perform in the project,
    • Outputs and end-products that you will produce,
    • Potential avenues to disseminate your work,
    • Potential opportunities to extend or expand this work using other sources of funding in the future.
    • Note: References are not included in the page limit, and should be limited to only those that are essential for the committee to evaluate the proposal.
  3. A personal statement that addresses the following at a minimum (1 page maximum)
    • Why are you a compelling candidate for the FAIR Program and a strong fit with the LaCross AI Institute?
    • Why do this Fellowship and the LaCross AI Institute represent a uniquely compelling opportunity for you?
    • How does this Fellowship support your current and potential future professional activities?

Application deadline: 9 January 2026 *This is the extended deadline*

Successful candidates will be expected to provide a letter of support from their current school/unit/manager. They may be asked for professional references prior to the final awarding of the Fellowship.

Nominations Due

30 November 2025

Applications Due 

9 January 2026 *This is the extended deadline*

Fellowship Recipients Announced 

30 January 2026


Congratulations to the 2026 Fellowship in AI Research recipients!
 

Nur Yildirim

 

Nur Yildirim
Assistant Professor at UVA School of Data Science

Nur Yildirim is an assistant professor of data science at the University of Virginia. Her research program focuses on developing human-centered and participatory approaches throughout the AI development lifecycle to successfully translate these technologies into products and services that benefit people and society. Building on this practice-based research, she aims to create best practices and expertise to support practitioners in AI design, development, and evaluation. Previously, she worked at Google Research and Microsoft Research, where she contributed to designing several AI applications in healthcare. She is the recipient of a Digital Health Fellowship from the Center for Machine Learning and Health and was named an AI Rising Star by the Michigan AI Lab in 2023.

 

Luca Cian

Luca Cian
Professor of Business Administration at UVA Darden School of Business

Luca Cian is a full professor at the University of Virginia’s Darden School of Business, where he holds the Killgallon Ohio Art Chair and serves as Marketing Area Coordinator. A leading scholar in consumer behavior, his research focuses on psychological responses to artificial intelligence, visual persuasion, social identity, and biofeedback methods such as eye-tracking. He has published in top journals—including Journal of Marketing Research, Journal of Marketing, Nature Communications, and PNAS—and has received numerous awards, including the 2025 SPSP Cialdini Prize and the 2024 BSPA Publication Award. In addition to serving as an AI expert for the U.S. Department of Homeland Security and Associate Editor of the Journal of Marketing Research, he teaches MBA and EMBA courses at Darden and has been recognized by Poets & Quants as a “40 Under 40” outstanding professor. His work frequently appears in major media outlets such as The New York Times, NPR, and The Washington Post.

 

 

Christopher Gaskin

 

Christopher Gaskin, M.D.
Professor of Radiology and Orthopedic Surgery at UVA Health 

Christopher Gaskin, MD, is a professor of radiology and orthopedic surgery at UVA, serving as Interim Chair of Radiology and Chief Medical Imaging Information Officer at UVA Health. Clinically, he specializes in musculoskeletal imaging, including X-ray, CT, MRI, DEXA, ultrasound, and a wide range of image-guided interventional procedures. His administrative and leadership work focuses on advancing imaging informatics to improve efficiency and quality of care across UVA Health, with initiatives spanning multimedia radiology reporting, optimization of electronic health records, workflow prioritization, and clinical decision support for advanced imaging.

 

 

 

Tianhao

 

Tianhao Wang
Assistant Professor at UVA School of Data Science by Courtesy and Assistant Professor of Computer Science

Tianhao Wang is a data privacy and security researcher that joined the University of Virginia in 2022. He serves as an assistant professor in the Department of Computer Science and at the School of Data Science by Courtesy. He has extensive publications in top security and database conferences. His work about differentially private synthetic data generation won multiple awards in NIST’s competition. Prior to the University of Virginia, he obtained his Ph.D. from Purdue University in 2021 and held a postdoc position at Carnegie Mellon University.

 

 

JingJing

 

Jingjing Li
Associate Professor of Commerce and Director of M.S. in Business Analytics Program at UVA McIntire School of Commerce

Jingjing Li is the Andersen Alumni Associate Professor of IT and Innovation at the University of Virginia’s McIntire School of Commerce, where she serves as Academic Director of the M.S. in Business Analytics Program and Associate Director of the Center for Business Analytics. Her research focuses on the design and management of AI and data analytics systems, with applications in healthcare, marketing, platforms, and public policy, and is published in leading journals such as MIS Quarterly, Information Systems Research, Journal of Marketing, and Harvard Business Review. An award-winning scholar and Associate Editor at MIS Quarterly, she teaches AI and analytics across undergraduate, graduate, and executive programs and was named a Poets & Quants Best Undergraduate Professor in 2023. Before academia, she was a scientist at Microsoft developing large-scale AI and machine learning solutions.

 

 

Michael

 

Michael Albert
Associate Professor of Business Administration at UVA Darden School of Business

Assistant Professor Michael Albert teaches Data Analytics and Decision Sciences courses in Darden’s MBA program, and he has courtesy appointments in Systems Engineering and Computer Science in the School of Engineering and Applied Sciences (SEAS) at UVA. His research focuses on combining machine learning and algorithmic techniques to automate the design of markets. His work has appeared in leading artificial intelligence and machine learning venues such as the Association for the Advancement of Artificial Intelligence (AAAI) and the International Joint Conference on Artificial Intelligence (IJCAI) as well as leading operations research and business journals such as Operations Research (OR).

 

 

 

Rob

 

Robert Phillips
Professor of Business Administration at UVA Darden School of Business

Robert Phillips is a Professor of Business Administration in Strategy, Ethics, and Entrepreneurship at the University of Virginia’s Darden School of Business. A leading scholar in business ethics and stakeholder theory, he has published more than 50 articles in top journals such as Business Ethics Quarterly, Strategic Management Journal, and Academy of Management Review, and is the author of Stakeholder Theory and Organizational Ethics. Before returning to Darden, he held senior academic leadership roles at York University’s Schulich School of Business and taught at institutions including Wharton, Georgetown, and the University of Melbourne. He serves as Consulting Editor of the Journal of Business Ethics and has held prominent leadership positions in major academic societies, including serving as past president of the Society for Business Ethics.

 

 

David

 

David Danks
Professor of Philosphy, Artificial Intelligence and Data Science at UVA School of Data Science and School of Arts and Sciences

Danks’s research lies at the intersection of philosophy, cognitive science, and machine learning, addressing ethical, psychological, and policy issues surrounding artificial intelligence and robotics, with applications in areas such as transportation, health care, privacy, and security. He has also made significant contributions to computational cognitive science, including the development of novel causal discovery algorithms. Previously, he held professorships at UC San Diego and Carnegie Mellon University, and he has served on numerous national advisory boards related to AI and technology policy. His honors include a James S. McDonnell Foundation Scholar Award and an Andrew Carnegie Fellowship.


For Additional Information

Please contact FAIR@darden.virginia.edu.