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Two student Amazon Fellows and five faculty-led projects supported by the Amazon-Virginia Tech Initiative for Efficient and Robust Machine Learning for the 2024-25 academic year were named at a retreat held on the Blacksburg campus.

The initiative, launched in 2022 to advance research and innovation in artificial intelligence (AI) and machine learning, is funded by Amazon, housed in the College of Engineering, and directed by researchers at the Sanghani Center for Artificial Intelligence and Data Analytics on Virginia Tech’s Blacksburg campus and at the Virginia Tech Innovation Campus in Alexandria. 

Fellowships are awarded to Virginia Tech doctoral students recognized for their scholarly achievements and potential for future accomplishments. They must be enrolled in their second, third, or fourth year and interested in and currently pursuing educational and research experiences in AI-focused fields. In addition to receiving funding for their work, the fellowship includes an opportunity to interview for an Amazon internship intended to provide them with a greater understanding of industry and use-inspired research.

The initiative’s faculty awards support machine learning sponsored research that works toward revolutionizing the way the world uses and understands this field of modern technology.

Read full story here.

The Amazon–Virginia Tech Initiative for Efficient and Robust Machine Learning will support two Amazon Fellows and five innovative research projects led by Virginia Tech faculty in the 2023-24 academic year that further the initiative’s mission of advancing innovation in machine learning. 

The initiative, launched in 2022, is funded by Amazon, housed in the College of Engineering, and directed by researchers at the Sanghani Center for Artificial Intelligence and Data Analytics on Virginia Tech’s Blacksburg campus and at the Virginia Tech Innovation Campus in Alexandria. 

An open call for fellowship nominations and faculty projects went out across the Virginia Tech campuses. An advisory committee of Virginia Tech faculty and Amazon researchers selected two Amazon Fellows from 27 nominations — more than double what was received last year — and five faculty projects from 17 submitted proposals. Read full story here.

Virginia Tech and Amazon gathered for a Machine Learning Day held at the Virginia Tech Research Center — Arlington on April 25 to celebrate and further solidify their collaborative Amazon–Virginia Tech Initiative for Efficient and Robust Machine Learning.  

Announced last year, the initiative — funded by Amazon, housed in the College of Engineering, and directed by researchers at the Sanghani Center for Artificial Intelligence and Data Analytics on Virginia Tech’s campus in Blacksburg and at the Innovation Campus in Alexandria — supports student- and faculty-led development and implementation of innovative approaches to robust machine learning, such as ensuring that algorithms and models are resistant to errors and adversaries, that could address worldwide industry-focused problems. Read full story here.

Assistant Professor Ruoxi Jia in the Bradley Department of Electrical and Computer Engineering and core faculty at the Sanghani Center for Artificial Intelligence and Data Analyitics at Virginia Tech has received an National Science Foundation (NSF) Faculty Early Career Development (CAREER) award to investigate fundamental theories and computational tools needed to measure the value of data. Read full story here.

Ruoxi Jia, who joined the Bradley Department of Electrical and Computer Engineering at Virginia Tech as assistant professor in 2020, is the newest faculty member at the Sanghani Center for Artificial Intelligence and Data Analytics.

Jia’s research interest broadly spans the areas of machine learning, security, privacy, and cyber-physical systems. Her recent work focuses on building algorithmic foundations for data markets and developing trustworthy machine learning solutions. Towards that end, she and her group work on a range of projects, including data valuation and quality management, data privacy, active data acquisition, adversarial machine learning, and explainable machine learning.  

Jia is teaching a course on “Trustworthy Machine Learning” this semester and is looking for postdocs and Ph.D., master’s, and undergraduate students to join her group. Because of the limitations of personal contact due to COVID-19, she is happy to work with them remotely. (Interested students should click here for more information.)

“We extend a warm welcome to Ruoxi,” said Naren Ramakrishnan, the Thomas L. Phillips Professor of Engineering in the Department of Computer Science and director of the Sanghani Center. “Her work in privacy and security aspects of machine learning can complement a range of work happening at the center.”

“I am excited to join the Sanghani Center and look forward to collaborating with the other faculty members and students to push the frontiers of data science and unleash the power of data in a trustworthy, responsible way,” said Jia.

Jia earned a bachelor of science degree from Peking University in 2013 and a Ph.D. in electrical engineering and computer sciences from the University of California Berkeley in 2018. 

She is the recipient of several fellowships, including the Chiang Fellowship for Graduate Scholars in Manufacturing and Engineering, the 8108 Alumni Fellowship, and the Okamatsu Fellowship. In 2017, she was selected for Rising Stars in EECS.

Prior to joining Virginia Tech she served as a postdoc in the Computer Science Department at University of California, Berkeley.

Her work has been published at professional conferences and featured in multiple media outlets, including MIT Technology Review, IEEE Spectrum, and Synced.