The University of Massachusetts Amherst
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Dynamic Duo Publishes Groundbreaking Papers in Nature Research Journals

Joshua Yang (left) and Qiangfei Xia (right)

Yang (l) and Xia (r)

A wave of media coverage is only the latest accomplishment in an amazing two years of productivity for research collaborators Qiangfei Xia and Joshua Yang of the Electrical and Computer Engineering (ECE) Department. Media stories by Science & Technology Research News and other outlets topped off a 2018 campaign in which the two ECE professors published eight pioneering articles in major Nature research journals, following a productive 2017 when they published six papers in those journals.

However, both Xia and Yang prefer to downplay their publications and highlight all the beneficial research represented by their papers. (See articles about three of their previous papers in Nature publications: A provable key destruction scheme based on memristive crossbar arrays, Capacitive neural network with neuro-transistors, Efficient and self-adaptive in-situ learning in multilayer memristor neural networks.)

In one recent publication, an ECE research team led by Xia and Yang developed a promising building block for the next generation of nonvolatile, random-access memory, artificial neural networks and bio-inspired computing systems. The team says the memristor crossbar arrays they have built are “to the best of our knowledge, the first high-density electronic circuits with individually addressable components scaled down to 2 nanometers dimension built with foundry-compatible fabrication technologies.” The results appeared in Nature Nanotechnology, and the paper is titled Memristor crossbar arrays with six-nanometer half-pitch and two-nanometer critical dimension.

Despite this kind of publishing feat, and many others like it, Xia and Yang always stress the societal impact of their research. As Xia explains, “We work hard to deliver high-impact research, which naturally leads to publications in high-profile journals, if we are lucky. But the ultimate goal is the impact of the work, which hopefully will change the world.”

Xia and Yang bring this issue up for a number of good reasons. “First,” Xia says, “I do not want to mislead our community, especially our students and postdocs, that our final goal in research is to publish papers. We solve hard problems, care about the quality and long-term impact of the work, and do not just go for low-hanging fruits to publish papers.”

Secondly, as Xia notes, “Rome is not built in one day. All the efforts and time invested in earlier years have contributed significantly to our recent 'spurt' of great papers. Earlier work at the fundamental level, such as the development of two fundamental memristive devices and the integration of large-scale crossbar arrays, are critical to our recent achievements.”

The last reason why it is important to emphasize the research process over the publishing itself is that for Xia and Yang “collaboration is our secret sauce. Some just see our many papers published in Nature journals, but what they may not see is our close collaboration for over a decade. With complementary expertise and a common goal, we do have some advantages over some peers; i.e., we have faith in our collaboration.”

The bumper crop of Nature publications by Xia and Yang isn’t even finished yet, because they are scheduled to publish a few more, including an article booked for publication on January 7, 2019, to help launch Nature Machine Intelligence, a new Nature research journal covering a wide range of topics in machine learning, robotics, and artificial intelligence.

With the paper appearing in Nature Machine Intelligence, Xia and Yang will cap off two years of almost unprecedented success publishing in some of the most prominent journals in the world. But both Xia and Yang would prefer to talk down that accomplishment and take a more panoramic vision, one that focuses on all of the good their extensive research can create for the world at large. (January 2019)