Tyler O'Neal, Staff Editor APPLICATIONS

UVA tapped to create graduate course that advances public interest technology

Cyber Innovation and Society Institute receives inaugural 'Network Challenge' grant

A multidisciplinary team of computer science, law, and public policy faculty at the University of Virginia have earned a national grant to establish a course aimed at teaching graduate students to deeply examine the complex ethical, legal, and policy implications of new technologies.

The Public Interest Technology University Network, which is part of Washington, D.C.-based think tank New America, awarded the grant as a way to cultivate academic initiatives that prepare the next generation of lawyers, policymakers, and technologists to design, build, and govern new technologies that advance the public interest.

UVA, through the Office of the Provost, is the only Virginia university that is a founding partner of the Public Interest Technology University Network. The $90,000 grant, one of 27 awarded across the country, will be led by Jack Davidson, a professor of computer science and an internationally renowned cybersecurity researcher at UVA's School of Engineering who also leads the University's Cyber Innovation and Society Institute. Davidson is collaborating with Thomas Nachbar, UVA law professor and senior fellow at the Law School's Center for National Security Law, and Philip Potter, UVA associate professor of politics and public policy and director of the National Security Policy Center. {module In-article}

The graduate course they are creating will be called Innovation in the Public Interest. The course will be offered for the first time in the spring of 2020.

"I am so pleased that a UVA team was recognized with one of the inaugural awards from the network," said Louis P. Nelson, vice provost for academic outreach at the University of Virginia. "Our faculty recognize the need for cross-disciplinary partnerships between policy specialists, technologists, and experts in the humanities for solving global technological challenges. The collaborations we see at UVA -- not to mention our mission --position us to be leaders in using technology to benefit society, with the team's course development as an ideal example."

The award highlights a long-standing strength at UVA for research and teaching that analyzes the implications of technology for society, particularly through UVA Engineering's Department of Engineering and Society. The Cyber Innovation and Society Institute, which UVA launched in 2018, brings faculty together from technical and humanities fields across the University to understand the impact of cyber systems on society, especially how they affect human values such as privacy, freedom, democracy, and individual autonomy.

The institute adopts an anticipatory approach, addressing political, ethical, and data ramifications before they emerge. In the process, the institute carries out multidisciplinary research and education initiatives that focus on the complex technical, social, and policy challenges posed by emerging cyber innovations to ensure that cyber technology benefits all of society equally, fairly, and dependably.

"As cyber technologies become pervasive, anticipating the impact these technologies have on society and developing policies that guide their interaction with society becomes critical," Davidson said. "A major focus of this new public interest technology course is on creating cyber innovations that are in the public interest and ensure an ethical evolution."

Innovation in the Public Interest will provide students with a structured experience in the development of public interest technology. The course will be offered through UVA's schools of engineering, law, and politics. It will create hands-on, real-world, problem-solving challenges across each week of the course.

Davidson, Nachbar, and Potter are working with government and industry partners who have posed the problems. Teams of diverse students from the different schools will be assigned those problems. They then will conduct team "sprints" designed to quickly engineer a solution that incorporates ongoing stakeholder input throughout the process. Each team also will make a formal presentation of its designed solution to the stakeholders.

This interactive class structure is intended to emulate the process of "agile development." Used by large corporations and start-ups alike, the agile process accelerates timelines on the delivery of better technology products. But the process can fall short in the age of big data, with so many social implications involved due to the ubiquitous nature of technology and the amount of information being gathered.

Unfortunately, agile development does not commonly consider legal requirements, policy ramifications or social implications of the new technologies. "That can result in serious problems down the road," Davidson said. "The idea of the course is to introduce a new mindset about the current process and how it can work better with regards to the public interest. Better social outcomes can be reached by including diverse viewpoints from the very first stages of development."

As the first course of its kind in UVA Engineering's Department of Computer Science, the curriculum also reflects the Engineering School's focus on diversity and multidisciplinary initiatives for better research outcomes. "Studies have shown that diverse groups come up with better solutions," Davidson said. "In alignment with UVA's 2030 strategic plan, a major impetus for offering the course is to expose our students to the rewarding possibilities of harnessing technology for the public good."

Nachbar said, "By integrating technology, policy, and law in our course, we are matching how this area is developing. There is not a single discipline that determines how public sector innovation takes place and affects our society. Our course, which brings together faculty and students from the three disciplines to solve actual problems that are provided by public agency sponsors, reflects that reality."

"Policy students need to learn to operate in multidisciplinary spaces," Potter added. "The really hard national security policy problems facing the United States are nearly always also technical and legal problems. By bringing together three UVA schools, we are preparing students to face that reality."

Innovation in the Public Interest course materials -- the syllabus, lectures, readings, assignments, and project descriptions -- will also be made publicly available for other universities that are interested in building a similar pipeline of public interest technology students.

Harvard Medical School's Church listens in to how proteins talk; learning their language

Tyler O'Neal, Staff Editor APPLICATIONS

Machine learning accelerates the design of synthetic proteins with desired functions, facilitating future therapeutic, diagnostic and biotechnology applications

Synthetic biologists have taken the evolution of proteins into their own hands by changing some that occur in nature or even by synthesizing them from scratch. Such engineered proteins are used as highly efficacious drugs, components of synthetic gene circuits that sense biological signals, or in the production of high-value chemicals in ways that are more effective and sustainable than petroleum-based methods.

To engineer them, they use two very different approaches. In "directed evolution", they randomly vary the linear sequence of amino acid building blocks encoding a natural protein and screen for variants with the desired activity; or they use "rational design" to model proteins based on their actual 3D structures to identify amino acids that likely will impact protein function. However, directed evolution can only cover a small part of the enormous space of possible protein sequences, while rational design approaches are limited by the relative scarcity of painstakingly resolved 3D protein structures. CAPTION Wyss Institute researchers have created an approach to engineer proteins that uses deep learning, and moves a lot of laborious laboratory experiments to the computer. CREDIT Klinsley Stocum{module In-article}

Now, a research team led by George Church, Ph.D. at Harvard's Wyss Institute for Biologically Inspired Engineering and Harvard Medical School (HMS) has created a third approach to engineering proteins that uses deep learning to distill the fundamental features of proteins directly from their amino acid sequence without the need for additional information. The approach robustly predicts the functions of both natural and de novo designed proteins, and moves a lot of laborious laboratory experiments to the computer, achieving up to two orders of magnitude cost reduction compared to existing approaches. The study is published in Nature Methods.

Church is a Founding Core Faculty member of the Wyss Institute and Lead of its Synthetic Biology platform. He also is the Robert Winthrop Professor of Genetics at Harvard Medical School and Professor of Health Sciences and Technology at Harvard University and the Massachusetts Institute of Technology (MIT).

"Instead of extensively characterizing proteins to understand their design principles, we used a neural network to learn those rules in an unbiased way, by systematically looking for patterns in a vast trove of raw protein sequences in public databases," said Surojit Biswas, one of the three co-first authors on the study who is a graduate student in Church's group. "The neural network learned a lot of the rules that we as humans have previously come to know through many painstaking studies, and beyond that, it also discovered new features in proteins."

The neural network approach, which the researchers named "unified representation" (UniRep), can be likened to learning a language where the learner builds a semantic understanding of how complex sentences are constructed from strings of letters and words. In protein language, UniRep was trained to predict the next amino acid in a protein sequence starting from its first one by exploring all the possibilities in protein sequences contained in public databases. Importantly, while proceeding through the remainder of the protein, one amino acid at a time, UniRep makes and draws on an internal "summary" of the sequence it has seen so far in the protein, which the team calls its "hidden state", to take into account its sequence and structural features. Feeding that information, and results from many other proteins, back into its algorithm, UniRep gradually revises the way it constructs hidden states, which improves its predictive capabilities over time. In the language analogy, the learner will be able to predict the next word of a sentence he is reading with increasing likelihood, based on a constantly improving understanding of syntax and choice of words.

"We trained UniRep on about 24 million protein sequences for roughly 3 weeks to enable it to predict sequences and their relationship to features like protein stability, secondary structure, and accessibility of internal sequences to surrounding solvents within proteins it had never seen before," said Grigory Khimulya, who was a student at Harvard College and is also a co-first author along with Biswas and Ethan Alley. "UniRep accurately described these features in proteins from very different protein families whose structures had been well-characterized in previous studies, even in synthetic proteins that don't have a counterpart in nature."

The team took UniRep a step further and used it as a tool to predict how single amino acid substitutions impact the function of proteins. The neural network robustly quantified the effects of single amino acid mutations in eight different proteins with diverse biological functions including enzyme catalysis, DNA binding, molecular sensing. Also, using the Aequorea victoria green fluorescent protein (GFP) as a model, they tasked UniRep to analyze 64,800 variants of the protein, each carrying 1-12 mutations, which demonstrated that it could accurately anticipate how the distribution and relative burden of mutations changed the protein's brightness.

"Compared to other strategies, our data-driven approach reaches state-of-the-art or superior performance in predicting multiple properties of proteins at costs much lower than other methods," said Church. "This makes it a truly empowering tool for protein engineers in many areas."

"This new deep-learning-based computational approach to protein engineering has the potential to accelerate the design of synthetic proteins with functions tailored for any desired application, whether it before for therapeutics, diagnostics, biomanufacturing, biocatalysis, or any other application. It literally can change the way we carry out molecular design in the future," said Wyss Founding Director Donald Ingber, M.D., Ph.D., who is also the Judah Folkman Professor of Vascular Biology at HMS and the Vascular Biology Program at Boston Children's Hospital, as well as Professor of Bioengineering at Harvard's John A. Paulson School of Engineering and Applied Sciences.

Strathclyde quantum technology partnership secures £4.6 million

Tyler O'Neal, Staff Editor APPLICATIONS

A University of Strathclyde-led quantum technology partnership, which is aiming to develop some of the world's most powerful computers, has secured funding worth a total of £4.6 million.

Researchers at Strathclyde and photonics and quantum technology company M Squared are collaborating to develop advanced computing technology, which could strengthen banking security, enhance traffic management and support aerospace security. The partners aim to work with fintech and aerospace businesses to deliver significant advancements in the UK's quantum capabilities.

The research has gained £2.6 million in Prosperity Partnership funding from the Engineering and Physical Sciences Research Council (EPSRC) as part of UK Research and Innovation, while M Squared has invested a further £1.7 million, and Strathclyde has contributed £300,000.

Future applications of the technology developed in this partnership include accelerated drug design for improved healthcare, novel materials for aerospace and manufacturing and the speed-up of optimization problems including scheduling and logistics for enhanced traffic management or improved efficiency in energy distribution across the National grid.{module In-article}

Prosperity Partnership grants are awarded to projects that build links between the UK's research base and leading industry partners. The project will complement the work of the UK-wide Quantum Technology Hubs, which explore the properties of quantum mechanics and how they can be harnessed for use in technology. Strathclyde is the only university that is a partner in all four of the hubs.

Strathclyde's lead in the Prosperity Partnership project is Dr. Jonathan Pritchard, a Research Fellow in the University's Department of Physics.

He said: "We are excited to have secured significant funding to develop this new experimental platform, which is currently not supported within the quantum technology hubs but which offers the potential to be truly disruptive in its ability to scale in future to extremely large numbers of qubits.

"This is a great opportunity, both for Strathclyde and for the UK as a whole, to establish new capability by working directly with global leaders in supplying commercial laser systems to quantum computing activities.

"This project will develop a new platform for quantum computing, based on scalable arrays of neutral atoms, and will work together with partners from industries including security and defense, aerospace and fintech to establish applications where this new quantum computer can deliver an advantage."

Dr. Graeme Malcolm, CEO, and founder at M Squared said: "This partnership with the University of Strathclyde is a demonstration of the scientific community harnessing the enormous benefits of collaboration between world-leading research institutions and advanced industry in the quest to develop frontier technologies.

"At M Squared we are thrilled to be at the heart of this groundbreaking work which the new funding will help to accelerate. Cross-sector investment is proving critical for progressing the UK's quantum computing capabilities, and we are extremely proud to be at the forefront.

"Glasgow has all the requisite components to pioneer the coming quantum era on the world stage and play a globally significant role in shaping the future of these defining years for the trajectory of this technology."

Business Secretary Andrea Leadsom said: "Cyber-attacks can have a particularly nasty impact on businesses, from costing them thousands of pounds in essential revenue to reputational harm.

"Cyber-criminals operate in the shadows, with the severity, scale, and complexity of breaches constantly evolving. It's critical that we are ahead of the game and developing new technologies and methods to confront future threats, supporting our businesses and giving them peace of mind to deliver their products and services safely.

"Investing in our world-leading researchers and businesses to develop better defense systems makes good business and security sense."

UK Research and Innovation Chief Executive, Professor Sir Mark Walport, said: "Our citizens and businesses must be able to access digitally secure products and services that are not vulnerable to cyber threats.

"The investments announced today will help to ensure the UK has a robust system in place to withstand cyber threats and create a safer future online, increasing trust and productivity in our economy."

EPSRC Executive Chair Professor Lynn Gladden said: "By combining expertise from across academia and industry, the Prosperity Partnerships will break new ground in areas of fundamental research that also provide major commercial opportunities.

"The partnerships announced today demonstrate the critical role that collaboration between UK researchers and industry partners will play in developing the revolutionary technologies of tomorrow."

Where more conventional computers operate on a binary system of zeroes and ones, quantum computers work on a system of qubits, which can be zeroes and ones simultaneously. As the number of qubits increases, the power of these computers rises dramatically, with each additional atom doubling the capacity of the computer. The new project is targeting 100 qubits, offering more computational power than even the largest available supercomputer.