When Computer Science major Mitali Palekar graduates next month, she can start a new chapter as a software engineer at LinkedIn knowing that she has made a difference in the community she has called home for the past four years. An accomplished student researcher, mentor and campus leader, Palekar has combined her love of programming and a passion for diversity to elevate the voices of students around her and help build a more welcoming and inclusive community within the field of computing.
A 2019 Husky 100 honoree and former TUNE House scholar, Palekar was most recently featured as GeekWire’s Geek of the Week for her many achievements during her time as a University of Washington student. These include serving as a past president and adviser to the UW chapter of the Society of Women Engineers, peer adviser and mentor for students in the Allen School, College of Engineering, and Interdisciplinary Honors Program, and a research assistant in the Allen School’s Security and Privacy Research Lab. She has also taken multiple opportunities to apply what she has learned through internships at Facebook, LinkedIn, Uber, and Stripe, and as a contributor to Bottomline, a compensation analytics startup that advanced to the Sweet 16 of the regional Dempsey Startup Competition hosted by the UW’s Buerk Center for entrepreneurship.
While she enjoys tackling technical challenges and exploring entrepreneurial opportunities, Palekar is particularly eager to use her position and experience to smooth the way for others. “I hope to play my role in improving representation, inclusion and belonging of underrepresented minorities in technology, ensuring that we continue to hone different sorts of talent and perspectives in tech,” Palekar told GeekWire. “Computer science can be for everyone.”
Palekar goes on to say that she draws inspiration from her parents for their hard work coupled with kindness, and from the “strong, fearless and passionate young women” among her friends, roommates and fellow technologists. They would, no doubt, be eager to return the compliment.
Lee was recognized for his research in theoretical algorithms, convex optimization, convex geometry, spectral graph theory, and online algorithms — work that Microsoft Research considers among some of the most exciting areas of computer science research today. “While I devote my energy on theoretical algorithmic research such as how to solve some decades- or even centuries-old problems faster, I am often surprised how much these ideas can be used to solve difficult modern problems,” Lee told the company. “Theoretical computer scientists are like particle physicists, instead of understanding the limits of physics, we understand the limits of computation. Although it looks impractical for outsiders, it often leads to important useful results.”
This focus on advancing the theoretical underpinnings of computation with real-world applications has been a recurring theme in Lee’s early work. Since joining the University of Washington faculty three years ago, Lee has earned earned a Best Paper Award at the Conference on Neural Information Processing Systems (NeurIPS 2018) for presenting new algorithms for achieving optimal convergence rates for optimizing non-smooth convex functions in distributed networks, and a CAREER Award from the National Science Foundation for his work on more efficient algorithms for solving convex and other optimization problems. As part of that project, Lee aims to advance the scientific community’s understanding of the relationship between convex geometry and optimization algorithms and improve upon current optimization techniques, the results of which will have broad impact across the sciences and in many other fields. Last summer, Lee collected the A.W. Tucker Prize from the Mathematical Optimization Society for his Ph.D. thesis exploring how to combine and improve upon existing optimization techniques to produce faster algorithms for solving a range of problems underpinning the theory and practice of computing.
The Faculty Fellowship comes with an unrestricted annual gift of $100,000 for two years to enable recipients like Lee to pursue their breakthrough research. Lee and his fellow honorees were selected as part of a rigorous, multi-tier process based on their pursuit of cutting-edge research, a demonstrated ability to communicate complex concepts, and the skills required to turn their ideas into impact. Past fellowship winners include Allen School faculty members Shwetak Patel (2011), Luis Ceze (2009), and Magdalena Balazinska (2007).
The Allen School family is mourning the loss of our friend and colleague Hellmut Golde, who passed away earlier this month after a brave battle against cancer. As one of the founding members of the Computer Science Group at the University of Washington and leader of the team that developed the wildly successful VAX Pascal compiler, Golde’s legacy includes the emergence of the Paul G. Allen School of Computer Science & Engineering as an education and research powerhouse and the emergence of the Seattle region as a hub of computing innovation.
Golde, who grew up in Germany, joined the UW faculty in 1959 as a professor in the Department of Electrical Engineering after earning his Ph.D. from Stanford University. He was one of the founders of the Computer Science Group in 1967, the precursor to the Department of Computer Science, formed in 1974, which evolved into the Department of Computer Science & Engineering in 1989 and eventually into the Paul G. Allen School in 2017. In those early days, Golde played a crucial role in establishing the culture for which the Allen School is widely known — one of friendship, support, and community.
A few years after he helped lead the creation of the Computer Science Group, Golde became director of the Computer Science Laboratory, the research and educational facility that hosted a couple of aspiring computer scientists, Paul Allen and Bill Gates, in the days before they set out to put a computer on every desktop. Back then, the pair would sneak into the lab and “borrow” computer time, as Gates would later describe it. Golde would cement his place in campus lore by famously expelling Allen and Gates from the lab.
Delivering his rebuke via a polite yet sternly worded letter, Golde directed Allen to “turn in your keys and terminate your activities” owing to offenses such as “you removed the acoustic coupler from Dr. Hunt’s office without authorization and without leaving at least a note.” At the celebration of the naming of the Allen School more than 40 years later, Allen astonished Golde and the rest of the audience by pulling out the letter and reading it in its entirety as he reminisced about his long-standing affection for UW. Allen subsequently framed two copies of Golde’s letter as mementos for the school and for Golde, while we attempted to make amends for the decades-old rebuke by gifting Allen an acoustic coupler purchased on eBay.
Professor emeritus Richard Ladner, who joined the department in 1971, fondly recounted the ease with which Golde bridged the divide in their academic interests and became not only a colleague but lifelong friend. “Hellmut was one of the first people I met when I interviewed for a faculty position at the University of Washington. We were miles apart in terms our academic interests, me a mathematician and he an electrical engineer,” Ladner recalled. “Nonetheless, we hit it off because of his infectious sense of humor and overall kindness. Some of my fondest memories of days with Hellmut are skiing with him and his family at Alpental, Mount Baker, Stevens Pass, and Big Sky. It was always hard for me to keep up with him on the slopes.”
Golde later stepped in to serve as acting chair of the department from 1976 to 1977. It was a period of transition for our program, and Golde wasn’t given much of a choice in the matter — the first department chair, his dear friend Jerre Noe, had declared himself a sabbatical after coming to the realization that if he didn’t leave town, he might wind up being chair for life. At the time, the department had a grand total of 11 faculty and had graduated 25 students.
As Golde was completing his time as chair, Ed Lazowska arrived to join the UW faculty one week after completing his Ph.D. — and just one week before the start of the school year. His new colleagues tried to reassure him that he didn’t need to worry, because “the course you’ve been assigned has been taught for many years by Hellmut Golde. He’s the best teacher in the department. Ask him for his notes.” Unfortunately for Lazowska, “Hellmut was such a good teacher that those ‘notes’ consisted of a single page, with a single line for each day of the course specifying the topic to be covered that day,” Lazowska laughed. “Let’s just say that my course evaluations were not as good as Hellmut’s had been.”
Although Golde’s time at the helm was short-lived, he had an outsize impact on the program beyond the recruitment of Lazowska and Ladner — each of whom went on to have an outsize impact of their own on the growth of our program and on our emergence as a leader in accessible computing, respectively. In October 1977, Digital Equipment Corporation (DEC) introduced the VAX-11/780 computer, which became the mainstay of many computer science departments and companies nationwide. UW managed to acquire an early VAX on the understanding that Golde and a group of graduate students would write a VAX compiler for the Pascal programming language, which was widely used for introductory programming.
“DEC was willing to give Hellmut a portion of sales for the VAX Pascal compiler because they greatly underestimated the demand for Pascal and the market for the VAX computer in education,” explained Allen School Director Hank Levy, who was a member of DEC’s VAX design and development team at the time. “Partly as a result of the compiler that Hellmut and his team built, the VAX become highly successful in educational institutions, resulting in more than $1 million in royalties flowing from DEC to the department — a not insignificant sum in those days. These funds were crucial in allowing the department to grow during difficult financial times on campus. It was Hellmut’s foresight, technical acumen, and generosity which allowed the department to preserve its momentum — and later, to climb into the ranks of the top 10 computer-science programs in the nation.”
The VAX-11/780 computer on display in the Allen Center atrium stands as a monument to those days, when this single computer could support the entire department’s computing needs.
As Ladner noted, Golde enjoyed a good joke — even if it came at his own expense. He was particularly amused at people’s inability to reckon with the pronunciation of his German name. “Hellmut used to display on his office door a montage of address labels from letters people sent him on which his name had been butchered,” recalled Lazowska. “He would say ‘Hellmut Golde’ on the phone, and often the person on the other end wouldn’t get it quite right. My personal favorite was the time someone addressed a letter to ‘Hal McGoldy.’”
Always a leader and forever a friend, Hellmut retired from UW as emeritus professor in 1992 but remained actively engaged with his Allen School family. We miss him greatly.
Four Allen School undergraduates are among the 2019 class of the Husky 100, a program that recognizes students from across the University of Washington’s three campuses who are making the most of their Husky Experience — both inside and outside of the classroom. This year’s honorees from the Allen School exemplify a commitment to academic excellence, campus leadership, and service to the community that are the hallmarks of a Husky 100 student.
Caleb Ellington is originally from Austin, Texas but proclaims he “couldn’t be more proud to be a Husky” as he looks to apply his talents at the intersection of biology and computing in developing communities.
After he graduates with degrees in Bioengineering and Computer Science next year, Ellington hopes to build on his past experience as a biomedical engineering ambassador to hospitals across Nepal by helping to develop emergency services in that country. Having completed internships at Boulder, Colorado-based Muse Biotechnology and at Amazon in Seattle during his studies, Ellington is also interested in pursuing entrepreneurial opportunities focused on therapeutics manufacturing.
“I came to UW with a mission to improve health care and medicine using tools available to everyone,” Ellington said.
Alison Ng of Woodinville, Washington will graduate this year with a degree in Computer Engineering. A leader inside the Allen School as well as out, Ng chairs the CSE Student Advisory Council, which represents the undergraduate and master’s student voices within the school, and serves as an officer of the UW chapter of the Society of Women Engineers, an organization that aims to expand educational and career opportunities for women in technical fields.
Ng also represents her fellow students as a member of the Allen School Diversity Committee and serves as a peer adviser helping to guide other CSE majors and prospective students toward academic success. She is currently in her second quarter as a teaching assistant for the Allen School’s Introduction to Digital Design course.
“The University of Washington has provided me with the opportunity to explore my passion for computer engineering and to develop the technical skills necessary to thrive in the industry,” Ng said.
Eugene Oh of Federal Way, Washington is pursuing degrees in Computer Science, with a concentration in Data Science, and Social Work.
During his time at UW, Oh has assisted current and prospective CSE majors as a peer adviser and also served as a teaching assistant for the Allen School’s Freshman Direct Admit seminar — in which he focused on the topic of social good — and Computer Science Principles course. When he is not honing his technical skills at a local technology company or as undergraduate research assistant, Oh devotes himself to volunteer service at the Roots Young Adult Shelter and mentoring students at Kent-Meridian High School through the UW Dream Project.
“My time at the UW has taught me to continually push my growing edge in all the spaces that I occupy,” said Oh. “I move forward from the UW hoping to combine my interests in education and technology to work toward empowering the youth of tomorrow.”
Mitali Palekar will graduate this year with a Computer Science degree with Interdisciplinary Honors. Palekar, who hails from Cupertino, California, describes her Husky Experience as one of transformation from “naive freshman” into an engineer, leader, and advocate.
In addition to serving as an Allen School peer adviser helping her fellow students navigate their own Husky Experience, she has been active in the UW chapter of the Society of Women Engineers as a senior adviser and past president. Palekar has also taken the opportunity to apply her technical skills as an undergraduate research assistant in the Allen School’s Security and Privacy Research Lab and through internships with multiple technology companies in Seattle and Silicon Valley.
“I have developed a passion for building products and communities that uplift the voices of people around me,” Palekar said.
“Through the Husky Experience, students discover their passions in life and work,” said UW Provost Mark Richards. “They become independent thinkers and leaders. They gain the skills they need to prepare for rewarding careers in industry, community and in life. That’s exactly what each of these 100 students is doing.”
This is the fourth year the UW has recognized students through the Husky 100 program. Past honorees from the Allen School include 2018 recipients Amanda Chalfant, Aishwarya Mandyam, Melissa Medsker (Galloway), and Kimberly Ruth; 2017 recipients Camille Birch and Kelsie Haakenson; and 2016 recipients Krittika D’Silva, Victor Farkas, Karolina Pyszkiewicz and Sarah Yu.
Congratulations to Caleb, Alison, Eugene, and Mitali on this well-deserved recognition — and thank you for devoting your time and talents to helping your fellow students and the community!
Throughout her studies, Goldner has often focused on theoretical problems that have real-world applications across multiple domains. She launched her research career by focusing on revenue maximization within mechanism design. In one high-profile project, Goldner tackled the so-called FedEx Problem, which deals with determining how to sell a variety of shipping options in order to maximize revenue for FedEx while meeting the expectations on the part of the customer in terms of service quality and cost. The Fedex Problem is a fundamental one that has implications in multiple market sectors, from shipping, to internet service, to cloud computing. Goldner and her collaborators designed the optimal revenue-maximizing auction for situations in which prior information on consumer values are known, contributing new algorithmic techniques and a greater understanding of mechanism design beyond single-parameter settings.
With algorithms playing an increasingly prominent role in systems that impact people’s day-to-day lives, Goldner became interested in algorithmic mechanism design for social good. She is particularly keen to explore how the techniques she honed on classic theoretical problems can be applied in domains such as health care and labor markets to maximize outcomes for both society and individuals — despite participants acting in their own self-interest. Such systems have tangible, sometimes high-stakes effects on people’s physical well-being and economic prospects, as well as on the welfare of society as a whole, via the allocation of resources, the setting of policies, and the regulation of activities to achieve certain outcomes. For instance, the goal of a health care system would be to align providers’ incentives with the dual (and sometimes dueling) goals of minimizing costs while maximizing patient health. Online job recruiting systems should be geared toward identifying optimal employer-employee matches while mitigating discriminatory hiring practices. Goldner aims to bring mathematical formality to these and other pressing social issues, applying her expertise in algorithmic mechanism design and game theory to develop new theoretical approaches for meeting objectives that are motivated by the social good.
To this end, Goldner has also been sharing her vision with the research community. In the fall of 2016, she co-founded the Mechanism Design for Social Good (MD4SG) initiative. That effort spawned a collection of events that Goldner also has co-organized — including an annual workshop, an online research group, and more — and inspired industry-funded grants on the topic. In December 2017, she delivered an invited tutorial on mechanism design for social good at the Conference on Web and Internet Economics.
“Since her arrival at the Allen School, Kira has done outstanding research, for example, studying problems like the FedEx Problem that are helping to advance our understanding of theoretical principles with real-world implications. She is currently tackling problems in health care and labor markets using the tools of algorithmic mechanism design; here the work has the potential to contribute directly to the well-being of society,” said Karlin. “Kira has repeatedly demonstrated outstanding technical expertise in tackling very interesting — and difficult — problems. Other qualities that particularly stand out are her creativity and vision in defining new and interesting research questions and the enthusiasm and thoughtfulness with which she questions standard assumptions.”
For the past three years, researchers in the Molecular Information Systems Laboratory (MISL) have been on a mission to store the world’s digital data in DNA. A partnership between the University of Washington and Microsoft, the lab has already sparked the imagination of artists, archivists, scientists, and the public with its vision to move beyond traditional data storage media, inspired by the very building blocks of life — what Allen School professor Luis Ceze refers to as “nature’s own perfected storage medium.”
Now the team, co-led by Ceze and Microsoft Principal Researcher Karin Strauss, is ramping up the innovation — and the scientific “wow” factor — with a series of new projects that have opened up exciting new avenues for exploration at the intersection of biology and computer science. One of those projects, described in detail in a new paper published in the journal Nature Communications last week, may be the clearest indicator yet that a DNA-based storage system is not only an intriguing option for solving the world’s data crunch, but also a practical one.
“Once we outlined a DNA storage system, we began contemplating the practical considerations,” said Strauss, who is also an affiliate professor in the Allen School. “The first milestone was figuring out random access within a single pool of DNA molecules mixed together, to retrieve only the data we want and avoid the time and expense of sequencing what we don’t. Our next challenge was to figure out how to take full advantage of DNA’s incredible density and resiliency while automating as many stages of the process as possible. Our latest step shows how to physically organize multiple DNA pools and retrieve them with liquid droplets controlled digitally.”
In their latest paper, Strauss and her colleagues presented a system for achieving high-density data storage in synthetic DNA. By “high-density” they mean one full terabyte of data — the equivalent of 1,000 gigabytes — in a single spot of dehydrated DNA one millimeter in diameter, or roughly the size of a pinhead. Although the information density of DNA molecules is theoretically much higher than that, the team wanted to ensure the ability to retrieve specific data from a particular pool without having to sequence the entire pool.
The team arranged the spots of DNA on glass cartridges, with each cartridge capable of storing up to 50 terabytes based on current DNA storage techniques. Multiple glass cartridges can then be stacked in a space-saving vertical configuration — akin to the approach taken with existing magnetic tape or hard drive-based storage systems to conserve room, albeit much more compact.
“DNA must be in liquid form for sample preparation and sequencing, but isolating liquid samples can be a cumbersome process and requires separate vessels — which would sacrifice a significant amount of density,” explained lead author Sharon Newman, an alumna of UW Bioengineering who is currently pursuing a Ph.D. at Stanford University. “Our dry storage architecture enables us to store data with much higher density compared to other approaches, and allows for physical isolation and data retrieval without risking contamination from other samples.”
To retrieve the data, the researchers rehydrate the DNA with a droplet of water using a digital microfluidics (DMF) device. Newman and her colleagues took a keen interest in DMF technology, which is capable of manipulating liquids in very small quantities with higher precision than humans. By automating biological and chemical protocols with DMF, researchers can scale up the processes involved in implementing DNA data storage. The devices are particularly suited to DNA storage processing, but they have their limitations: not only do DMF platforms tend to be prohibitively expensive, but they are also inflexible, error-prone, and difficult to program.
“Most of the work on microfluidics has focused on automating individual protocols, in which the device is given a fixed set of inputs, and manipulates them in a specified way to produce an output,” explained Allen School Ph.D. student Max Willsey. “Although this is an important component of wet-lab research, it limits the role of DMF to that of a microcontroller. We envision a more expansive and dynamic system that enables scientists to program complex protocols in Python or another language of choice while providing real-time error correction.”
Puddle’s dynamic approach to resource management sets it apart from existing techniques, which take a more static approach to microfluidic programming. Puddle is an application programming interface (API) that purposefully maximizes expressiveness and ease of use, in exchange for sacrificing some efficiency and ahead-of-time guarantees. This trade-off gives Puddle more flexibility, allowing both the system and the user to react to data from the fluidic domain. These data-driven decisions fall into three categories: protocol-level decisions, such as automatic replenishment of a liquid that has evaporated during an experiment; application-level decisions based on the protocol output, such as what experiment to run next; and execution-level decisions, such as error detection and correction. To enable the latter, the team employed computer vision and a small camera mounted on top of the DMF device. The camera functions as a multi-purpose sensor for detecting the location and volume of droplets to help Puddle decide if an error has occurred.
The built-in error detection enables the robust execution of the system on relatively cheap hardware, meaning the researchers could prioritize simplicity and accessibility in designing the PurpleDrop device. In addition to the camera, PurpleDrop features a Raspberry Pi 3B single-board computer, instead of a microcontroller, to drive the electronics, which enables it to function as a self-sufficient microfluidics platform. Costing about$300 assembled — orders of magnitude less than most fluidics systems — the design is also simple enough for many labs to put together on their own, without requiring access to a clean room.
“Cost considerations are one of the main sticking points when it comes to microfluidics,” noted Allen School research scientist and co-author Ashley Stephenson. “So as we look for ways to expand the capabilities, we want to ensure that scientists and practitioners will be able to access these innovations. This work can be used to advance not just DNA data storage but also many other areas of research, such as medicine.”
Because cost and complexity are probably the two biggest barriers to widespread adoption of DNA as a storage medium, it comes as no surprise that automation has emerged as a recurring theme in MISL’s work. Last month, the world said “hello” to the first fully automated, end-to-end system for storing digital data in synthetic DNA. Lab members took those five letters, represented by five bytes of data, and ran them through a fully functioning prototype incorporating the equipment required to encode, synthesize, pool, sequence, and read back the data — the majority of which, like PurpleDrop, was built using inexpensive, off-the-shelf components. And it performed the cycle without human intervention, which as senior research scientist Chris Takahashi pointed out, will be an advantage when it comes to DNA data storage in the wild.
“You can’t have a bunch of people running around a data center with pipettes,” pointed out Takahashi, lead author of a related paper published in Nature Scientific Reports. “It’s too prone to human error, too costly, and the footprint would be too large.”
Takahashi and his colleagues did not set out to demonstrate speed or even affordability at this stage; rather, they built the machine to show that end-to-end automation was possible. The team’s ultimate goal is to develop a system that resembles any other cloud-based storage service, to which end users would be able to upload their data to a storage center. The difference is, instead of staying in digital form, a customer’s data would be converted to the As, Ts, Cs, and Gs of DNA until it is needed again.
“We are developing an entirely new way of storing digital data from scratch, which means building all new hardware, platforms, and techniques,” said Ceze. “There is a lot more to it than solving the technical challenges related to converting those 0s and 1s to DNA molecules, and we have made significant progress in the last three years. With these latest results, we are building a bridge between computation and molecular biology and introducing exciting new capabilities that will benefit both fields.”
When the team began working on SUPPLE, even the most promising solutions for dealing with this challenge could not sufficiently handle the growing array of display sizes and types of interactions available. Many were unable to cope with situations in which the device constraints could not be anticipated in advance or cases in which the functionality had to be generated dynamically. Often, these tools required interface designers to hand-craft templates or explicitly and painstakingly identify which widgets to use and under what constraints — making the process both time-consuming and expensive. And none of them were geared toward addressing the needs of the user, especially the many people with physical disabilities who struggle to use interfaces crafted for an imaginary “average” user.
Gajos and Weld opted to define interface generation as a constrained decision-theoretic optimization problem. They then set about creating a model-driven solution capable of dynamically generating the “optimal” interface for each user given their physical capabilities and constraints such as device capabilities. Rather than specifying how certain features should be presented by an interface from the start — the approach followed by most existing tools — the team preferred to specify what functionality was intended by the interface and leave the decision on how it should be presented to the SUPPLE algorithm.
As it became clear that the algorithm might provide revolutionary benefits to users with physical disabilities, Gajos and Weld teamed up with Jacob Wobbrock, a professor of human-computer interaction in the UW Information School and adjunct faculty member in the Allen School. Together, they added methods for quickly and automatically characterizing physical capabilities, and this enabled SUPPLE to generate one interface for a user with muscular dystrophy and a very different one for a person with cerebral palsy, because it learned that the former user had low strength and couldn’t move the pointing device more than small distances while the latter had impaired dexterity and required larger targets for accurate selections. The team’s studies showed that SUPPLE could dramatically increase the speed of users with motor impairments while simultaneously decreasing their error rate.
“We wanted every person, regardless of their physical abilities, to be able to easily manipulate computer interfaces,” explained Gajos, who is now a member of the faculty of Harvard University. “One can view the project as advancing the notion of Ability-based Design. This is important because the prevalent one-size-fits-all methodology inevitably leads to some form of discrimination.”
“Our initial objective with SUPPLE was to provide a consistent user experience across a range of online platforms and services, regardless of physical location or the type of device,” said Weld, a member of the Allen School’s Artificial Intelligence group. “By approaching interface generation as an optimization problem, we were able to move beyond generic design, instead creating personalized interfaces for people with different preferences and physical abilities.”
The system automatically selects the optimal elements to display in a particular interface from multiple widget libraries. In this case, the “optimal” SUPPLE rendering not only satisfies functional and device constraints, but also requires the least amount of user effort expressed as a cost function. To compute estimated cost of user effort, the team employed a trace-driven approach to model users’ typical interactions in addition to their tool for quickly eliciting performance profiles for users with physical disabilities.
To highlight the lasting value of the team’s contributions, IUI organizers invited an expert panel to reflect on the impact of SUPPLE on the intelligent user interface community at the 2019 conference. The panelists included Henry Lieberman of MIT CSAIL, Jeffrey Nichols of Google, and Simone Stumpf of the Centre for HCI Design at City, University of London.
University of Washington professor Shwetak Patel has been named the recipient of the 2018 ACM Prize in Computing from the Association for Computing Machinery. Patel, who holds a joint appointment in the Paul G. Allen School and the Department of Electrical & Computer Engineering and also leads a team at Google, is being honored by the ACM for “contributions to creative and practical sensing systems for sustainability and health.” The ACM Prize in Computing recognizes early or mid-career computer scientists whose research has had fundamental impact and broad implications and is among the highest honors bestowed in computer science — second only to the A. M. Turing Award, which is widely regarded as the “Nobel Prize of computing.”
“Despite the fact that he is only 37, Shwetak Patel has been significantly impacting the field of ubiquitous computing for nearly two decades,” ACM President Cherri M. Pancake said in a press release. “His work has ushered in new possibilities in many applications of ubiquitous computing for sustainability and health.”
Patel began his research career as an undergraduate at Georgia Tech, where he had the opportunity to work on the “Aware Home,” a project that aimed to envision the connected home of the future. The experience inspired Patel to focus his career on developing low-power sensing capabilities that transformed how we view technologies old and new — from the humble U-bend under your sink, to the basic electrical wiring in your home, to the latest smart devices. Even as an undergraduate, Patel knew that he wanted to make his mark as a faculty member in academia, where he would have the freedom to pursue his research interests without the constraints of working in industry. Only later would he discover the extent to which he could combine the two to great effect.
“Academic life is my intellectual playground,” Patel said. “Computing has so much potential to have a positive impact on society and I’ve been fortunate to be able to try new things through my research. I’m also passionate about getting the technology out there by working closely with industry and through commercialization.”
The first industry Patel helped build was whole-home sensing for sustainability. Patel, whose work on the Aware Home led him to become a plumber and electrician in addition to a computer scientist, recognized that home systems such as the electrical wiring and plumbing could reveal fine grained information about power and water usage — so fine-grained, in fact, that he and his students figured out how to combine signal processing and machine learning to measure electricity usage at the individual device level, including televisions, lights, dishwashers, and more.
Patel and his students noted that each device places distinct “noise” on the home’s electrical system. This noise makes it possible to determine which device is in use and how much power is being consumed. Patel and his students applied a similar principle to monitor the home plumbing system by measuring pressure waves in the home’s plumbing as each faucet or fixture is turned on and off. “Your noise is our signal,” Patel would often say about this work.
Beyond the significance of the research findings, Patel demonstrated that sustainability sensing could be practical, too. His system required only a single device to be plugged into an outlet or connected to the plumbing in order to gather data on the entire system. Patel co-founded a startup company, Zensi, to commercialize this work — the first of several startups he would establish to push his research out into the marketplace. Zensi was subsequently acquired by Belkin, which opted to open its new WeMo Labs in Seattle with Patel serving as Chief Scientist in addition to his faculty position at UW.
As it turned out, Patel discovered that a home’s electrical system could be used to reveal a lot more than whether someone left the television on. That same system could be used like a whole-home antenna to transmit a variety of other data points that could provide an early indication of home hazards, such as elevated moisture levels inside the walls that indicate an appliance malfunction or leak. Patel and his collaborators developed a platform known as Sensor Nodes Utilizing Powerline Infrastructure, or SNUPI for short, that leveraged a network of ultra-low-power sensors deployed throughout the home to wirelessly transmit data, via the electrical circuit, to a base station.
“Sensors can collect information in real time, enabling a homeowner to get ahead of an issue. But if you put sensors throughout the home, you don’t want to have to keep replacing batteries,” Patel noted. “Our home monitoring sensors were designed to be embedded into the wall and last for decades — essentially enabling people to ‘set it and forget it.’”
As before, Patel co-founded a company, the aptly-named SNUPI Technologies, to commercialize the team’s results. SNUPI released a consumer product, WallyHome, that was later acquired by Sears.
By that time, Patel had already begun turning his focus from sensor systems covering an entire building to ones that fit into the palm of a hand. “I began noticing how people are constantly interacting with their phones, which contain increasingly sophisticated sensing capabilities through their cameras, microphones, accelerometers, and other features,” Patel recalled. “And I started wondering how we could use these touch points to monitor health and get ahead of conditions that would otherwise require more time-consuming, potentially invasive interactions.”
One of the first projects he worked on was designed to turn a mobile phone into a handheld spirometry device for measuring lung function. SpiroSmart and a related tool, SpiroCall, enabled people to use their phones to measure their lung function at home or on the go by simply blowing into the microphone. Patel and his students demonstrated that their tool, which like the home sensing systems combined signal processing with machine learning, could achieve acceptable medical standards for accuracy compared to commercial spirometry devices — without the time and expense of an in-person doctor’s visit. They also made use of the built-in camera to develop a series of apps to screen for a variety of medical conditions, including BiliCam for detecting infant jaundice; BiliScreen for detecting adult jaundice (known to be an early symptom of pancreatic cancer); and HemaApp for measuring hemoglobin levels in the blood to detect anemia and other conditions. And these are just a few examples of what Patel has been working on. He also commercialized some of these technologies, which were acquired by Google where he now leads a team.
“That device in your pocket or hands has so much potential, and we’ve only just begun to tap into what it can do for individuals and communities,” observed Patel. “I’ve begun thinking about mobile technologies in the context of not just domestic health, but global health. What can this technology do for communities where no landline infrastructure exists, or where a significant percentage of the population is illiterate? Mobile phones are the most ubiquitous computing platform in the world.”
Patel has begun to see the opportunity in action in collaboration working with local communities and the Bill & Melinda Gates Foundation. He and his team have deployed SpiroSmart and SpiroCall in clinics in India and Bangladesh, for example, while another tool developed in his lab, CoughSense, is being used to track the spread of tuberculosis in South Africa. Meanwhile, providers in Peru are using HemaApp as a non-invasive alternative to traditional blood tests to screen children for anemia. Patel is hopeful that these and other tools will soon be available to health care providers, government and non-profit agencies, and individual users across the globe.
Academia may be his playground — a place where he can test off-the wall ideas and collaborate with students and peers to push the boundaries of what technology can do — but Patel acknowledges that it’s his forays into industry that have enabled him to realize the impact of his research at scale. The time spent working on his startups has also made him a better researcher, he says, by broadening his view of what questions he could address through his work.
“Being an entrepreneur has helped me to identify research problems I wouldn’t have previously considered solely as an academic,” Patel explained. “That experience opened up opportunities for me to venture down research paths I wouldn’t have otherwise thought about.”
“Shwetak is an exceptional innovator who combines an insatiable curiosity with an unrelenting drive to produce research that has real-world impact,” said Hank Levy, Director of the Allen School. “Thanks to his technical excellence, breadth, and vision, we can now do things with sensors and smartphones that were unthinkable outside the confines of science fiction only a short time ago. Shwetak not only has expanded our understanding of what technology can do, but also created new companies and given rise to entirely new industries. And he has undertaken this amazing work all while staying true to our mission as educators and mentors of the next generation of computer scientists. I cannot think of anyone more deserving of this honor.”
This marks the first time a UW faculty member has received the ACM Prize in Computing, but not the first with a UW connection. Previous winners include Allen School alumni Jeff Dean (Ph.D., ‘96), a senior fellow at Google, and Stefan Savage (Ph.D., ‘02), a faculty member at the University of California, San Diego. The ACM Prize comes with a cash award of $250,000 from an endowment furnished by Infosys. Patel will be formally honored at the ACM’s annual awards banquet coming up on June 15th in San Francisco, California.
“I’m honored and humbled to be recognized by the ACM and my peers in this way,” Patel said. “My hope is that this award and the body of work it represents will inspire students to think broadly about the impact that they can have as computer scientists on people’s everyday lives and in the quest for solutions to our greatest public challenges. I would also like to acknowledge my hard working students whose dedication and passion really enabled all of this.”
In yet another example of how computation is transforming biology and medicine, Allen School researchers have developed a machine learning-based system that improves upon a widely used technique for analyzing interactions between DNA and the proteins that regulate gene expression. In a paper published in Nucleic Acids Research, Ph.D. students Nao Hiranuma and Scott Lundberg and professor Su-In Lee demonstrate how their system, AIControl, is more cost-effective — and yields more accurate results — than current practices for increasing our understanding of genetic factors regulating the onset of disease and other biological processes.
AIControl is designed to be used in conjunction with chromatin immunoprecipitation and DNA sequencing (ChIP-seq), a vital tool in molecular biology for determining the location and function of transcription factors that govern gene expression. ChIP-seq enables researchers to map the binding sites of a specific regulatory protein to DNA across the human genome. While ChIP-seq is one of the most advanced and popular techniques available, it is not without its shortcomings; in addition to being a costly experiment to run, the data generated by immunoprecipitation (IP) contains background signals that can lead to false positives.
To compensate, researchers are advised to generate an additional control dataset in addition to their target dataset. While the IP target dataset captures actual protein binding signals, the control captures potential biases in the data. The results of both are then subjected to a process known as “peak calling,” in which algorithms compare the two datasets and separate out the peaks, which indicate the presence of true protein binding signals, and minimize false positives stemming from background noise. It is these peaks that researchers are interested in exploring, as they indicate the site of DNA-protein interactions that influence biological processes.
Due to the time and expense associated with generating that second dataset, many users opt to rely on an existing control pulled from a public database or forego the recommended control altogether. As an alternative, the Allen School team developed a machine-learning framework, AIControl, that replaces the need for the additional control dataset by estimating it in silico using multiple, publicly available controls.
AIControl works by systematically determining the most appropriate combination of control datasets to be applied to the target experiment, then estimates the distribution of unwanted background signals based on those datasets to identify the true binding peaks. With AIControl, researchers are able to rely on efficient and cost-effective computation, rather than expensive biological experiments, to generate more accurate ChIP-seq results.
“By making use of existing datasets on a large scale, AIControl can save researchers time and expense while offering a more comprehensive and accurate peak analysis of their target dataset,” explained Hiranuma. “Because our system is capable of leveraging information from a large number of control experiments in a public database, AIControl captures potential biases in the data that might be missed using a single control — or using no control at all.”
While existing peak calling techniques require the user to decide which control datasets to apply, AIControl alleviates that burden by automatically integrating and weighing multiple datasets that are most relevant to the target dataset. The system draws upon data from 440 publicly available controls, encompassing more than 100 cell types, to infer the distribution of background signals for the peak calling comparison. Hiranuma and his colleagues evaluated their system by applying AIControl to 410 IP datasets from the ENCODE ChIP-seq database spanning five major cell types.
AIControl outperformed existing peak calling methods in identifying putative binding sites, including in cases where control datasets of the same cell type were removed. This suggests that AIControl will be capable of reliably estimating background signals in conjunction with ChIP-seq analyses performed on new cell types. According to Lee, the team’s findings have already generated interest among biotechnology companies eager to replace a costly process for generating new data with an AI-driven solution.
“Locating the binding sites of regulatory proteins on DNA is a central problem in molecular biology that will enable us to more fully understand the interplay between genetic factors and disease,” Lee said. “With AIControl, we have shown that machine learning can be used in place of expensive biological experiments to generate results with greater speed and accuracy than standard approaches. Our hope is that this will advance our understanding of genetic factors that influence disease and, ultimately, lead to better outcomes for people.”
The University of Washington community mourns the loss of our friend and colleague, Vikram Jandhyala, a committed educator, innovator, and entrepreneurial leader who made a lasting impact on our campus culture and the community. In addition to his teaching and research, Jandhyala left his mark through his tireless efforts to mentor faculty and students and help translate research into real-world impact via UW CoMotion. He will also be remembered for his enthusiastic leadership of new and innovative partnerships such as the Global Innovation Exchange (GIX) in collaboration with Microsoft and Tsinghua University in China.
Jandhyala began his UW career in 2000 as a professor in what was then known as the Department of Electrical Engineering (EE). He was Founder & Chief Technologist of UW spin-out company Nimbic (formerly Physware), which developed high-speed, 3D electromagnetic simulation solutions used in hardware design that was subsequently acquired by Mentor Graphics. Jandhyala served as Department Chair of EE from 2011 to 2014, during which time he also served as the founding director of the joint UW and Pacific Northwest National Laboratory Northwest Institute for Advanced Computing. He stepped down from his role as Chair to become the UW’s Vice President for Innovation Strategy and Executive Director of CoMotion.
“Vikram played many different roles and was a friend to the Allen School in each of them,” said Hank Levy, Director of the Allen School. “As chair of Electrical Engineering, he worked with us to develop a joint faculty hiring program, the Experimental Computer Engineering Lab (ExCEL), which has been incredibly successful in attracting world-class engineering faculty to UW; as head of CoMotion, he helped us to multiply the impact of our technology; and as director of GIX, he built a unique and creative international educational institution. We will miss his positive and collaborative attitude, his vision, and his enthusiastic support for the work of our faculty and students.”
In the nearly five years Jandhyala led CoMotion, he molded it into more than a technology transfer and commercialization office; under his stewardship, it became the entrepreneurial hub for the entire university community. He brought the same collaborative spirit and entrepreneurial zeal to GIX, serving as Co-executive Director since 2015 and celebrating its first graduating class of 37 students from 11 countries last year. According to UW President Ana Mari Cauce, both CoMotion and GIX “will stand as testaments to Vikram’s legacy.”
Jandhyala was joined on the GIX leadership team by his faculty colleague, Shwetak Patel, who led the interdisciplinary faculty group that helped craft the GIX curriculum and serves as its Director and Chief Technology Officer. As director of the Ubicomp Lab, Patel has taken inspiration from Jandhyala to made entrepreneurial leadership a cornerstone of his teaching and mentorship. He has started multiple companies with students and colleagues since his arrival at the UW, including residential water and energy monitoring company Zensi, which was acquired by Belkin in 2010, and SNUPI Technologies, develop of the WallyHome wireless home sensing platform that was acquired by Sears in 2015. He worked directly with Jandhyala and his team on the acquisition of his most recent startup, mobile health sensing company Senosis, by Google in 2017. Patel credits Jandhyala for helping to convince him to come to Seattle and for supporting his career trajectory melding innovative research with entrepreneurial impact.
“Vikram built an infrastructure and culture around supporting an entrepreneurial spirit that cut across the entire University,” said Patel, who holds a joint appointment in the Allen School and the Department of Electrical & Computer Engineering (ECE). “He laid the groundwork for companies like Senosis to succeed by enabling us to leverage commercialization gap funding, incubation, and other programs that flourished under his leadership.
“On a personal note, Vikram was not only a colleague, but also my mentor and friend,” Patel continued. “He demonstrated through his own work and deeds that you could think big about the future of innovation and play leadership roles that help move an organization into new directions, while remaining grounded in your work with students and faculty.”
Joshua Smith, who is also a professor in both the Allen School and ECE and directs the UW’s Sensor Systems Laboratory, recalled Jandhyala’s vision and generosity in helping Smith to launch a startup company, Proprio, to commercialize a new machine-learning enabled visualization tool for surgical teams.
“Vikram selflessly catalyzed the formation of Proprio by introducing me to Dr. Sam Browd, an entrepreneurial doctor who had identified a medical need,” Smith said. “I will miss his positive, enthusiastic, and generous spirit.
“I first worked with Vikram when I was a researcher at Intel, and we collaborated on an NSF-funded research project,” Smith continued. “He went on to become faculty coordinator of EE’s Professional Master’s Program — a role I now have the privilege of filling — followed by department chair, head of CoMotion, and head of GIX. Vikram was a visionary leader and role model in all of these positions, and I marvel at how much he accomplished and how many lives he changed for the better in the short time he was here.”
Smith worked with Jandhyala on the successful spin-out of another two companies — wireless robot charging company Wibotic and Jeeva Wireless. The latter, which Smith co-founded with a team that included Allen School professor Shyam Gollakota, aims to transform the way we power the Internet of Things by enabling battery-free communication using backscatter technology. After spinning out from the UW, the company raised $5 million in venture capital, grants, and project funding. Gollakota also worked with Jandhyala on a deal with ResMed to commercialize the technology behind ApneaApp, which detects signs of sleep apnea, and the spin-out of health-oriented mobile sensing company Sound Life Sciences, which is commercializing the Second Chance opioid detection app. Both of those apps were developed in conjunction with UW Medicine — two more examples of the interdisciplinary innovation in service to big ideas that was a hallmark of Jandhyala’s leadership.
“Vikram made CoMotion a kind and supportive place that encourages researchers to take the big risks of entrepreneurship. I knew CoMotion was in safe hands because he was at the helm,” said Gollakota. “His smile and enthusiasm were extremely infectious. His death is a huge loss for the university and the Seattle tech community, and a very sad development for all of us.”
“Vikram had a huge positive impact on education, on research, and on innovation at the University of Washington and far beyond,” said professor Ed Lazowska, who holds the Bill & Melinda Gates Chair in the Allen School. “Under his leadership, CoMotion completed UW’s transformation from ‘licensing’ to ‘commercialization’ to ‘innovation.’ And the Global Innovation Exchange combined technology, design, and entrepreneurship in a project-based, global context.
“Vikram was a visionary, a friend, and an inspiring leader,” Lazowska continued. “I — and all of us in the Paul G. Allen School — are among the many who understood and appreciated the work that he did to make us all better. We will miss him terribly.”
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