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Tuskegee University announced recently that Dr. Chitra Nayak, associate professor in Tuskegee University’s College of Arts and Sciences department of physics, has been awarded a leadership fellowship to help increase researcher participation in artificial intelligence.

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The National Institutes of Health’s Artificial Intelligence/Machine Learning (AI/MIL) Consortium to Advance Health Equity and Researcher Diversity program, awarded the $50,000 grant to focus on underrepresented communities using AI/MIL to achieve health equity through mutually beneficial partnerships.

According to the Artificial Intelligence/Machine Learning Consortium to Advance Health Equity and Researcher Diversity (AIM-AHEAD) website, the lack of diversity of both data and researchers in the AI/ML field runs the risk of creating and perpetuating harmful biases in its practice, algorithms, and outcomes, thus fostering continued health disparities and inequities.

Dr. Nayak’s research will investigate the bias in some deep learning due to discrimination in the algorithm and or lack of training data sets representing different races.

The project is titled “Investigation of the Spatial Transcriptomic Deep Learning Algorithms using Histological Images for Possible Bias Depending on the Training Data Sets.”

“I would like to thank my colleagues, Drs. Channa Prakash, Clayton Yates, and Qazi as they each have been instrumental in the program’s introduction and the funding,” Dr. Nayak said in a statement. “The work I have been doing with Dr. Yates trying to use AI to train tissue classifiers helped me immensely while preparing the application.”

In addition to the year-long fellowship, Dr. Nayak will have access to Consortium Cores, targeted training, and courses specific to AI/ML and Health Equity education. She will benefit from workshops and seminars on leadership principles, strategies, and case examples.

Dr. Nayak is a scholar in Health Disparity Research Education Award Certificate Program. She expects to leverage her interest in artificial intelligence/machine learning and her role as an educator to attract students from underrepresented communities in AI, minimizing the existing bias in this field.

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