2024-2025 USC - Capital One Center Call for Fellowship Nominations

USC and Capital One have created a joint research center focused on the development of new approaches to responsible AI for decision making in finance. The Center housed at the USC Viterbi School of Engineering, will support USC and Capital One researchers in the development of novel approaches to AI with potential applications to finance.

Each year, through a competitive process, the Center will provide support for several research projects focused on the development of new methodologies for AI with potential applications to solving complex financial problems. The Center will also provide annual fellowships to doctoral students working in this research area, enabling them to advance research frontiers. Fellowship recipients will be named as Capital One Fellows in recognition of their promise and achievements. In addition to funded research projects and annual fellowships for doctoral students, the collaborators will host an annual joint public research symposium to share their knowledge with the machine learning and AI communities.

We hereby invite USC faculty to nominate qualifying Ph.D. students for year 2025 Capital One Fellows‍

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Eligibility

• USC Ph.D. students who will be in their 2nd, 3rd, or 4th year of their Ph.D. studies in 2024-2025
• The thesis (or research area) of the nominated student should be within the AI and Machine Learning Area with potential application to financial problems

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Required Nomination Materials and Submission Procedure

• Student’s CV (two-page max)
• A research statement written by the student (1-page max, 11-point font or larger, with no
  less than 0.5-inch page margins)
• Two recommendation letters

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Required Nomination Materials and Submission Procedure

• The fellowships will be for one year (2025)
• About 3-6 fellowships are expected to be awarded
• Each fellowship consists of $50,000 gift funding (no overhead)

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The nomination package (compiled in a single-file PDF format) should be sent via email to,
Administrative Program manager Ariana Perez (arianape@usc.edu), by 5 pm PT on
9/20/2024.

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Some of the research topics of interest to CREDIF are listed below. It is expected that PhD Fellowships will involve PhD students whose research thesis has some relevance to the
topics below:

1. Robust AI in the face of noisy data and labels: To train AI/ML models in the presence of noisy and imperfect data, we are interested in the development of a Robust AI framework with focus on enhancing resiliency and accuracy of the AI system that can be
   built with data anomalies, inconsistencies, collection bias, and under representation of multiple data groups. The robust AI framework should include advanced methodologies for data cleaning, noise reduction, bias detection, and dealing with data drift and data
   imbalance.
2. Synthetic data generation with an emphasis on generation of structured/tabular data: How might we leverage GenAI to synthetically generate structured (tabular) data retaining the characteristics of real-world data as much as possible, either for the purposes of augmenting training data or for safely releasing proxy datasets with the right characteristics (while preserving privacy) to enable research community involvement in our problems of interest
3. Explainability framework that improves transparency and interoperability in LLM
based systems (particularly in the presence of multiple agents): Unique challenges in explainability in multi-agentic workflow and possible methodologies to enable users to understand the decision-making process inside a complex agentic environment with
   humans in the loop.
4. Integration of graph knowledge representations with AI: Providing accurate and relevant information is key to the success of Generative AI systems. However, standard methods often fall short when dealing with complex questions that require information from various sources. With potential application to financial services, we're interested in methods that leverage graph-based knowledge representation to address these limitations
   and improve the quality of AI-generated responses.

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For any other questions, please contact Administrative Program manager, Ariana Perez via email (arianape@usc.edu).

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