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Allen School professors Tadayoshi Kohno and Rajesh Rao named IEEE Fellows for pioneering new directions in computing research

Allen School professor Tadayoshi Kohno has devoted his career to advancing security, privacy and safety in multiple industries, from cars to cardiac defibrillators, while also advancing thoughtful and inclusive approaches to technology design. Meanwhile, his colleague Rajesh Rao contributed to the progress of brain-computer interfaces from science fiction to actual science by demonstrating their very real potential to help people with neurological injury or disease. What they both have in common is the honor of being named a 2023 IEEE Fellow by the world’s largest technical professional association focused on advancing technology to benefit humankind.

Tadayoshi Kohno: Putting the brakes on security and privacy threats

Portrait of a smiling Tadayoshi Kohno wearing a light blue polo shirt standing on warm-toned wooden stairs with metal and glass railings
IEEE Fellow Tadayoshi Kohno’s contributions to security and privacy span multiple domains, from the automobile and medical device industries, to electronic voting and mixed reality.

IEEE honored Kohno for “contributions to cybersecurity” — an apt reference to Kohno’s broad influence across a variety of domains. As co-director of the Allen School’s Security and Privacy Research Lab and the UW Tech Policy Lab, Kohno has explored the technical vulnerabilities and societal implications of technologies ranging from do-it-yourself genealogy research, to online advertising, to mixed reality. 

His first foray into high-profile security research, as a Ph.D. student at the University of California San Diego, struck at the heart of democracy: security and privacy flaws in the software that powered electronic voting machines. What Kohno and his colleagues discovered shocked vendors, elections officials, and other cybersecurity experts.

“Not only could votes and voters’ privacy be compromised by insiders with direct access to the machines, but such systems were also vulnerable to exploitation by outside attackers as well,” said Kohno. “For instance, we demonstrated that a voter could cast unlimited votes undetected, and they wouldn’t require privileged access to do it.”

After he joined the University of Washington faculty, Kohno turned his attention from safeguarding the heart of democracy to an actual heart when he teamed up with other security researchers and physicians to study the security and privacy weaknesses of implantable medical devices. They found that devices such as pacemakers and cardiac defibrillators that rely on embedded computers and wireless technology to enable physicians to non-invasively monitor a patient’s condition were vulnerable to unauthorized remote interactions that could reveal sensitive health information — or even reprogram the device itself. This groundbreaking work earned Kohno and his colleagues a Test of Time Award from the IEEE Computer Society Technical Committee on Security and Privacy in 2019.

“To my knowledge, it was the first work to experimentally analyze the computer security properties of a real wireless implantable medical device,” Kohno recalled at the time, “and it served as a foundation for the entire medical device security field.”

Kohno and a group of his students subsequently embarked on a project with researchers at his alma mater that revealed the security and privacy risks of increasingly computer-dependent automobiles, and in dramatic fashion: by hacking into a car’s systems and demonstrating how it was possible to take control of its various functions.

“It took the industry by complete surprise,” Kohno said in an article published in 2020. “It was clear to us that these vulnerabilities stemmed primarily from the architecture of the modern automobile, not from design decisions made by any single manufacturer … Like so much that we encounter in the security field, this was an industry-wide issue that would require industry-wide solutions.” 

Those industry-wide solutions included manufacturers dedicating new staff and resources to the cybersecurity of their vehicles, the development of new national automotive cybersecurity standards, and creation of a new cybersecurity testing laboratory at the National Highway Transportation Safety Administration. Kohno and his colleagues have been recognized multiple times and in multiple venues for their role in these developments, including a Test of Time Award in 2020 from the IEEE Computer Society Technical Committee on Security and Privacy and a Golden Goose Award in 2021 from the American Association for the Advancement of Science. And most importantly, millions of cars — and their occupants — are safer as a result. 

Kohno has journeyed into other uncharted territory by exploring how to mitigate privacy and security concerns associated with nascent technologies, from mixed reality to genetic genealogy services. For example, he and Security and Privacy Research Lab co-director Franziska Roesner have collaborated on an extensive line of research focused on safeguarding users’ security and privacy in augmented-reality environments. The results include ShareAR, a suite of developer tools for safeguarding users’ privacy while enabling interactive features in augmented-reality environments. They also worked with partners in the UW Reality Lab to organize a summit for members of academia and industry and issue a report exploring design and regulatory considerations for ensuring the security, privacy and safety of mixed reality technologies. Separately, Kohno teamed up with colleagues in the Molecular Information Systems Lab to uncover how vulnerabilities in popular third-party genetic genealogy websites put users’ sensitive personal genetic information at risk. Members of the same team also demonstrated that DNA sequencing software could be vulnerable to malware encoded into strands of synthetic DNA, an example of the burgeoning field of cyber-biosecurity. 

Kohno’s contributions to understanding and mitigating emerging cybersecurity threats extend to autonomous vehicle algorithms, mobile devices, and the Internet of Things. Although projects exposing the hackability of cars and voting machines may capture headlines, Kohno himself is most captivated by the human element of security and privacy research — particularly as it relates to vulnerable populations. For example, he and his labmates recently analyzed the impact of electronic monitoring apps on people subjected to community supervision, also known as “e-carceration.” Their analysis focused on not only the technical concerns but also the experiences of people compelled to use the apps, from privacy concerns to false reports and other malfunctions. Other examples include projects exploring security and privacy concerns of recently arrived refugees in the United States, with a view to understanding how language barriers and cultural differences can impede the use of security best practices and make them more vulnerable to scams, and technology security practices employed by political activists in Sudan in the face of potential government censorship, surveillance, and seizure. 

“I chose to specialize in computer security and privacy because I care about people. I wanted to safeguard people against the harms that can result when computer systems are compromised,” Kohno said. “To mitigate these harms, my research agenda spans from the technical — that is, understanding the technical possibilities of adversaries as well as advancing technical approaches to defending systems — to the human, so that we also understand people’s values and needs and how they prefer to use, or not use, computing systems.”

In addition to keeping up with technical advancements that could impact privacy and security, Kohno is also keen to push the societal implications of new technologies to the forefront. To that end, he and colleagues have investigated a range of platforms and practices, from the development of design principles that would safeguard vulnerable and marginalized populations to understanding how online political advertising contributes to the spread of misinformation, to educate and support researchers and developers of these technologies. He has also attempted to highlight the ethical issues surrounding new technologies through a recent foray into speculative and science fiction writing. For example, his self-published novella “Our Reality” explores how mixed reality technologies designed with a default user in mind can have real-world consequences for people’s education, employment, access to services, and even personal safety.

“It’s important as researchers and practitioners to consider the needs and concerns of people with different experiences than our own,” Kohno said. “I took up fiction writing for the joy of it, but also because I wanted to enable educators and students to explore some of the issues raised by our research in a more accessible way. Instead of identifying how a technology might have gone wrong, I want to help people focus from the start on answering the question, ‘how do we get this right?’”

Rajesh Rao: Engineering new possibilities through brain-computer interfaces

Portrait of a smiling Rajesh Rao wearing wire-rimmed eyeglasses and a dark grey suit jacket over a pale grey button-up shirt, with concrete and brick features and catwalk lighting in the Paul G. Allen Center atrium visible in the background.
IEEE Fellow Rajesh Rao is a pioneer in brain-computer interfaces and computational modeling for advancing neuroscience and artificial intelligence.

Rao was elevated to IEEE Fellow for “contributions to brain-computer interfaces and computational modeling.” As a holder of the Cherng Jia and Elizabeth Yun Hwang Professorship in the Allen School and UW Department of Electrical & Computer Engineering, director of the Neural Systems Lab and co-director of the Center for Neurotechnology, Rao has been instrumental in advancing the fields of computational neuroscience and neural engineering over the past decade while helping to bring BCIs into the mainstream.

Rao’s early research focused on the application of Bayesian modeling to understand prediction and learning in the brain. In 1999, he and his Ph.D. advisor, Dana Ballard, introduced predictive coding, a hierarchical neural network model of how the visual cortex is constantly predicting and learning a model of the world by minimizing prediction errors. As the first to explain the phenomenon known as “endstopping” — the scenario in which a neuron ceases responding to a stimulus once it has extended beyond the neuron’s classical receptive field — the duo’s work has been highly influential in both neuroscience and artificial intelligence (AI), anticipating the importance of prediction in recent AI models such as transformers. 

Rao subsequently built upon that work by developing models for attention, planning as inference, robotic imitation learning, and more. He was the first to apply approximate Bayesian inference for an arbitrary hidden Markov model in a recurrent neural network commonly used to model the cerebral cortex. Using an orientation discrimination task and a visual motion detection task, Rao demonstrated that his approach produces neural dynamics that emulate the response of decision-making neurons in the brain. He later combined Bayesian inference and the theory of partially observable Markov decision processes (POMDPs) with temporal difference learning algorithms to produce a model of decision-making under uncertainty — akin to how animals choose when to switch from information gathering to overt action to maximize future expected reward in the face of incomplete knowledge. For a well-known motion discrimination task, Rao demonstrated that his model neurons exhibited responses similar to those of the primate lateral intraparietal cortex.

“Predictive coding and Bayesian modeling of brain function are just two examples of the extremely fruitful ways in which computer science can help advance neuroscience and vice versa, leading to synergistic interactions between the two fields,” Rao said. “Another way is coupling computers directly to brains using brain-computer interfaces or BCIs.”

Leading a multidisciplinary research team at CNT with fellow Hwang Professor and co-director Chet Moritz, Rao helped develop new bi-directional BCIs — implantable devices that can both interpret brain signals and use this information to stimulate areas of the brain and spinal cord to help people regain function lost due to spinal cord injury, stroke, or other neurological conditions. Such devices also have the potential to promote neuroplasticity in regions of the brain or spinal cord that have been damaged — essentially assisting the networks of neurons in these regions to repair themselves.

“When Christopher Reeve sustained a spinal cord injury due to a fall from his horse, his brain circuits were still intact and able to form the intention to move, but unfortunately the injury prevented that intention from being conveyed to the spinal cord,” Rao explained to UW News in 2015, citing the original Superman actor’s paralysis as an example of how those connections are severed. “Our implantable devices aim to bridge such lost connections by decoding brain signals and stimulating the appropriate part of the spinal cord to enable the person to move again.”

In addition to advancing technologies that would restore the connections between an individual’s brain and their limbs, Rao has also explored techniques for creating new connections between multiple people’s brains. In 2013, he and another UW colleague, Andrea Stocco, a professor in the UW Department of Psychology and researcher in the Institute for Learning & Brain Sciences, offered the first demonstration of human brain-to-brain communication over the internet. During the experiment, Rao directed Stocco via brain signals to move his finger to hit a target on a video game from the other side of the UW campus. Their method of remote communication involved a non-invasive combination of electroencephalography, which recorded Rao’s silent instruction, and transcranial magnetic stimulation, which transmitted that instruction to Stocco’s brain.

A year after achieving this milestone, the researchers replicated their demonstration — this time involving multiple pairs of participants. Alluding to the Vulcan mind-meld from Star Trek and the premise of the movie Avatar, “we realized that we had all the equipment we needed to build a rudimentary version of this technology,” the duo wrote in Scientific American. “Along with other scientists, we are now learning to bypass traditional modes of communication and swap thoughts directly between brains.”

There were limitations to their initial proof of concept; it was restricted to communication between two people, and the second could only passively receive information. In 2019, Rao and his collaborators addressed that problem head-on with BrainNet, which expanded the capabilities of their brain-to-brain interface to enable a group of people to collaborate remotely to solve a task — in this case, a Tetris-like game — by both sending and receiving information.

“Humans are social beings who communicate with each other to cooperate and solve problems that none of us can solve on our own,” Rao said in a UW News release at the time. “We wanted to know if a group of people could collaborate using only their brains. That’s how we came up with the idea of BrainNet: where two people help a third person solve a task.”

In a series of experiments, participants averaged 81.25% accuracy in completing the task set for them, with the receiver learning to trust the instructions from the more reliable sender. The work pointed to the potential for humans to engage in collaborative problem-solving via a “social network” of brains.

Recently, Rao has returned his attention to his earlier, career-defining research to take advantage of new developments in the field while continuing his research in BCIs. 

“This is an exciting time to be working at the intersection of computer science and neuroscience,” said Rao. “Inspired by recent advances in AI, my group is currently working on new versions of predictive coding, called dynamic and active predictive coding, to better understand brain function while also suggesting new brain-inspired AI models. In the area of BCIs, we have proposed a new type of BCIs called brain co-processors that use artificial neural networks to interact with biological brains to restore or augment human function.”

Rao and Kohno are among four University of Washington professors elevated to the status of IEEE Fellow for 2023. They are joined by Uri Shumlak, a professor in the William E. Boeing Department of Aeronautics & Astronautics who was recognized for “research of sheared flow stabilization of the Z pinch for fusion energy,” and Yinhai Wang, a professor in the Department of Civil & Environmental Engineering who was recognized for “contributions to traffic sensing, transportation data science, and smart infrastructure systems.”

Learn more about the IEEE Fellow program here. Congratulations to Yoshi, Raj and all of the honorees!