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MATRIX AI Consortium, Xilinx award inaugural class of fellows

MATRIX AI Consortium, Xilinx award inaugural class of fellows

APRIL 5, 2021 — The MATRIX AI Consortium at UTSA is pleased to announce the inaugural class of Xilinx-MATRIX AI Fellows. Funded by a generous gift from Xilinx’s Women in Technology (WIT) Programs, the award includes funding to support stipends for the initial class of fellows, along with state-of-the-art hardware to be used within MATRIX’s newly-established AI DIY space located in the North Paseo Building.

Xilinx’s WIT programs fund university efforts seeking to increase the representation, participation, and entrepreneurial skills and abilities of women in technology-focused careers.

Fellows will participate in a variety of programming this spring semester, including the MATRIX AI seminar series and workshops intended to build collaborative mentorship relationships with female AI scientists.


“MATRIX is committed to reducing the barriers faced by minority groups entering into AI fields.”



Additionally, the fellows will complete an AI-related research immersion experience within a MATRIX core member’s lab.

The fellows are:

  • Tomisin Adebayo; advisor: Amina Qutub, biomedical engineering

  • Nour Alharki; advisor: Qutub, biomedical engineering

  • Raquel Britto; advisor: Jiannan Cai, construction science

  • Lilianna Gutierrez; advisor: Debaditya Chakraborty, construction science

  • Jenelle Millison; advisor: Amanda Fernandez, computer science

  • Van Ngo; advisor: Yongcan Cao, electrical and computer engineering

  • Tiffany Tran; advisor: Dhireesha Kudithipudi, electrical and computer engineering

“MATRIX is committed to reducing the barriers faced by minority groups entering into AI fields,” explained Kudithipudi, director of the MATRIX AI Consortium, the Robert F. McDermott Endowed Chair in Engineering, and a professor in the departments of Electrical and Computer Engineering, and Computer Science at UTSA. “We are incredibly grateful that Xilinx has chosen to support our initial efforts to broaden and strengthen the gender diversity of the AI workforce pipeline.”

Sarah Hada



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