News

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.

Considering the millions of research papers and reports from open domains such as biomedicine, agriculture, and manufacturing, it is humanly impossible to keep up with all the findings.

Constantly emerging world events present a similar challenge because they are difficult to track and even harder to analyze without looking into thousands of articles. 

To address the problem of relying on human effort in situations such as these, Lifu Huang, an assistant professor in the Department of Computer Science and core faculty at the Sanghani Center for Artificial Intelligence and Data Analytics, is researching how machine learning can extract information without relying on humans.  Read the full story here.

A team of four graduate students at the Sanghani Center for Artificial Intelligence and Data Analytics is one of nine international university teams selected to compete in the Alexa Prize SocialBot Grand Challenge 5 sponsored by Amazon.com Services LLC. Each participating team will receive up to a $250,000 research grant to build a skill that can help Alexa converse with users on popular topics and current events for at least 20 minutes while achieving a user rating of at least 4.0/5.0. Top finishing teams will also be eligible for various prizes. Read more here.

A Virginia Tech team from the Sanghani Center for Artificial Intelligence and Data Analytics is one of 10 finalists chosen to compete in the Alexa Prize SimBot Challenge. The challenge focuses on advancing the development of next-generation virtual assistants that continuously learn and gain the ability to perform common sense reasoning to help humans complete real-world tasks.

“The SimBot should be able to understand the intention of a task as well as any instructions or feedback it receives from a user and interpret the environment to correctly predict what action is needed to complete it,” said Lifu Huang, assistant professor of computer science and faculty at the Sanghani Center.  Click here to read more about how the team will tackle this challenge.

The Discovery Analytics Center continually brings together computer scientists, engineers, and statisticians to meet the research and workforce needs of today’s data-driven society. This Fall, DAC welcomes new faculty member Lifu Huang. He has joined the Virginia Tech Department of Computer Science as an assistant professor, having earned his Ph.D. in computer science at the University of Illinois Urbana-Champaign.

Huang’s primary research interests are in the fields of natural language processing, machine learning and artificial intelligence. He is specifically interested in building efficient models and benchmarks that can encourage machines to perform human-level intelligence.

His current projects include extracting structured knowledge with limited supervision; natural langue understanding and reasoning; natural language generation and representation learning.

As a graduate student, he was a research intern at Microsoft Research Asia; IBM Watson Research; U.S. Army Research Center; and Allen Institute for Artificial Intelligence (AI2), where he was recipient of the 2019 AI2 Fellowship.

Huang received a bachelor’s degree in software engineering from Northwestern Polytechnical University, China, in 2011 and a master’s degree in computer science from Peking University in 2014.