Allen School professor Pedro Domingos has been selected as the 2019 recipient of the John McCarthy Award from the International Joint Conference on Artificial Intelligence (IJCAI). The award, which is named for one of the founders of the field of AI, recognizes established, mid-career researchers who have amassed a track record of significant research contributions that have been influential in advancing the field. Domingos is being honored by the IJCAI for his multiple contributions in machine learning and data science and for advancements in unifying logic and probability.
Domingos focuses on ways to enable computers to discover new knowledge, learn from experience, and extract meaning from data with little or no help from people. A prolific researcher and speaker on the topics of AI, machine learning, and data mining, he has authored more than 200 technical papers on these and other subjects. In 2015, Domingos published The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World, a book intended for a broad audience that explores in a comprehensive yet accessible way how developments in machine learning impact on people’s everyday lives and the potential — and potential pitfalls — of living in the “age of algorithms.”
Domingos himself is partly responsible for ushering in this exciting new era through a series of research projects that represents the state of the art. For example, he and former student Abe Friesen (Ph.D., ‘17) developed a new algorithm, known as Recursive Decomposition into locally Independent Subspaces (RDIS), that outperformed existing techniques for solving a broad class of nonconvex optimization problems. Their work, which earned the duo a Distinguished Paper Award at IJCAI-15, can be applied in a variety of domains, including computer vision, machine learning, and robotics. That same year, Domingos received the SIGKDD Test of Time Award, along with his collaborator and Allen School alumnus Geoff Hulten (Ph.D., ‘05), from the Association for Computing Machinery’s Special Interest Group on Knowledge Discovery and Data Mining for the Very Fast Decision Tree learner (VFDT), an algorithm for mining high-speed data streams. Originally published in 2000, the VFDT algorithm remained the fastest decision tree learner available 15 years after its release. Domingos and Hulten later expanded the VFDT algorithm into the Very Fast Machine Learning (VFML) toolkit for mining high-speed data streams and vast data sets.
In 2014, Domingos earned the SIGKDD Innovation Award — the highest award for technical excellence in the field of data mining and data science — for foundational contributions to data stream analysis, cost-sensitive classification, adversarial learning, Markov logic networks, and viral marketing and information integration. Among his early-career achievements recognized by SIGKDD were MetaCost, a novel method for cost-sensitive classification that can be applied to a wide array of data mining problems. MetaCost, which earned a Best Paper Award for Fundamental Research when it was released, offered an improvement over existing practices such as stratification or making individual algorithms cost-sensitive. In another contribution that also earned a Best Paper Award for Fundamental Research, Domingos explored Occam’s razor as it is applied to data mining and effectively dismisses one accepted interpretation — that simplicity leads to greater accuracy — while building a case for a refined alternative to simplicity as a goal in itself. In his refined interpretation, Domingos presents an argument for decoupling discovery of the most accurate model from the extraction of the most comprehensible approximation of it.
Domingos’ other pioneering contributions to the field include the first algorithm for solving the problem of adversarial classification — which spurred the growth of adversarial learning as a significant branch of machine learning research and practice — with then-students Nilesh Dalvi, Mausam, Sumit Sanghai, and Deepak Verma. Working with another former student, Hoifung Poon (Ph.D., ‘11), Domingos employed Markov logic to also produce the first unsupervised approach to semantic parsing for natural language processing.
Domingos will be formally recognized with the John McCarthy Award at IJCAI-19 in Macao, China next month.
The Allen School family is mourning the recent passing of Bob Ritchie, one of our founding faculty members who helped build the foundations of Computer Science & Engineering at the University of Washington as we know it today.
Originally from Alameda, California, Ritchie earned his bachelor’s from Reed College and his Ph.D. from Princeton University — both in Mathematics — before joining the faculty of Dartmouth College in 1960. He had a near escape when, two years later, he was nearly recruited by Bowdoin College before opting to return to the west coast and join the UW instead. Ritchie started out as a professor of Mathematics, before the existence of a distinct computer science program on campus. He later joined forces with six other faculty members to push for the creation of the Computer Science Group, which was the predecessor of the Department of Computer Science. That, in turn, became the Department of Computer Science & Engineering, and ultimately, the Paul G. Allen School.
Ritchie was among the original cadre of seven full-time faculty that comprised the early department and helped establish its reputation for excellence in theoretical computer science research and teaching. He became the second permanent department chair in 1977, succeeding interim chair Hellmut Golde after inaugural chair Jerre Noe stepped down. During his six-year term, Ritchie led the department to national prominence, earning a place among the top 10 programs in the country — and from there, we never looked back.
“Hellmut and Jerre established our culture. Bob established our external reputation,” said professor Ed Lazowska, who joined the faculty the same year Ritchie became chair. “A United Airlines ‘100,000 Miler’ plaque hung on the wall of Bob’s office — miles accrued flying around the country telling people that something exciting was happening in computer science at the University of Washington.”
Ritchie logged a lot of air miles touting UW CSE nationwide before retirement
While Ritchie’s impact in raising the reputation of the program was significant, his technical excellence and commitment to mentorship are equally important aspects of his legacy. Ritchie was an early pioneer in the creation of what is now called computational complexity: the theory of the time and storage needed to solve computational problems. He was among the first to examine classically defined computations from mathematical logic and show that they are equivalent to modern complexity classes defined in terms of time and storage, calling them “predictably computable functions.” As professor emeritus Richard Ladner recalled, Ritchie was keen to help other researchers branch out into theory.
“Bob Ritchie was my first mentor when I joined the Computer Science Group in 1971. We both had backgrounds in mathematics and had moved into computer science theory,” he said. “Bob supported my transition from mathematics to theory research. He pointed out which were the important conferences to attend, and advised me which journals I should publish in. My first NSF grants were joint with Bob.
“We met on a regular basis until I got on my own feet,” Ladner continued. “I will always be grateful for his early mentoring that helped me get off to a flying start as a teacher and researcher.”
Ritchie advised two of the early Ph.D. students produced by the then-fledgling Computer Science Group — John Baker and Richard (Dick) Hamlet (Ph.D., ‘71) — in addition to supervising graduate students in Mathematics, his original home at UW. One of these students, Francine Berman (Ph.D., ’79), fondly remembers Ritchie and the program he helped to create.
“Bob was one of my thesis advisors and he was always supportive and encouraging,” recalled Berman, who, like several students in those early days in the school’s history, was officially enrolled in another academic department but advised by Computer Science faculty. “I’m sure I am among many that he helped along the way. CS at UW was a very special place in those days, as it is now, and provided a place to nurture so many of us.”
The way they were: Former UW CSE chairs (left to right) Bob Ritchie, Jerre Noe, Ed Lazowska, David Notkin, and Jean-Loup Baer
Ritchie also had a reputation for being a steady leader and an astute negotiator of bureaucracy. According to professor emeritus Jean-Loup Baer, who arrived at UW in the second year of the Computer Science Group’s existence and would later go on to become department chair, Ritchie would remain “cool and composed” when faced with unexpected challenges.
“While our first chair, Jerre Noe, was building a strong faculty core, he relied heavily on Bob’s knowledge and influence in his dealings with the UW administration,” Baer explained. “Almost 10 years later, when Bob asked me to be his Associate Chair, I was able to witness first-hand how his brilliant mind dealt in creative and non-obvious ways with the intricacies of large organizations.
“Bob was an important participant in the negotiations that brought the first two large collaborative projects with industry: the creation and funding of the VLSI Consortium, and the contract with DEC for the development of the Pascal Compiler,” he continued. “I was Acting Chair while Bob was on sabbatical when we received the delivery of the VAX-11/780 as part of the Pascal Compiler deal. The only hitch was that it was a few months early, and the room where it was to be housed was not ready. I wish I had kept my email exchange with Bob — I know that mine contained the three words ‘panic, Panic, PANIC.’ Of course, Bob guided me to a solution and the VAX spent a few weeks, or months, in the campus surplus store. By watching Bob I learned that when dealing with academic administrations one has to be patient, calm, and creative and that the shortest path between point A and point B is not necessarily a straight line.”
Ritchie in one of his famous shirts
After completing his term as chair of CSE in 1983, Ritchie departed the UW to embark upon a second career in industry, holding positions in the research divisions of Xerox and Hewlett-Packard. But it is his influence on the emergence of UW as a powerhouse in computer science education and research that continues to be felt today.
“Bob propelled us to write the proposal that led to the first award in NSF’s Coordinated Experimental Research program, which put us on the map in computer systems. He also managed to wangle us a top-10 ranking in the 1982 National Academies assessment of doctoral programs,” noted Lazowska. “We remember him for his leadership, for his advocacy, for his friendship — and for his shirts.”
Ritchie is survived by his wife of 62 years, Audrey; daughter Lynne Gustafson; son and Allen School alumnus Scott Ritchie (B.S., ‘83); and five grandchildren: Katherine, Erin, Kelly, Callum, and Sean. We at the Allen School are keeping them in our thoughts as we celebrate Bob’s legacy to our program, our university, and our field.
The University of Washington today announced the appointment of Magdalena Balazinska as the next director of the Paul G. Allen School of Computer Science & Engineering. Former Dean of Engineering Michael Bragg and UW Provost Mark Richards selected Balazinska, a professor who co-leads the Allen School’s Database and Data Science research groups, to succeed current director Hank Levy, who has overseen 13 years of growth in the school’s size, stature, and impact.
“I am thrilled and deeply honored to work with students, faculty, staff and community stakeholders to advance computer science education and innovation,” Balazinska said in a UW News release. “Together, we have the opportunity to work on the most challenging problems of our time and develop groundbreaking new technology. I look forward to contributing to this goal as the new Allen School Director.”
For the past two years, Balazinska has served as director of the UW eScience Institute and, more recently, as the UW’s First Associate Vice Provost for Data Science. In that dual role, she has developed broad cross-campus partnerships to advance data-intensive discovery across a variety of disciplines and spearheaded the establishment of educational programs for students in the burgeoning field of data science. As Principal Investigator on a major IGERT grant from the National Science Foundation, Balazinska led the creation of the Data Science and Advanced Data Science Ph.D. options at UW, and later co-led the creation of the Undergraduate Data Science option. More than a dozen departments or schools on campus offer students a chance to combine their primary field of study with one or more data science options, from astronomy and oceanography, to genome sciences and psychology. Additional units are preparing to roll out the program in the future, opening up opportunities to students in a widening variety of fields to combine their major with the latest data science methods and tools.
“Magda has been an inspired and energetic leader of campus-wide data science education, research, and adoption,” said professor Ed Lazowska, Bill & Melinda Gates Chair in the Allen School. “She succeeded me as director of UW’s eScience Institute; she became UW’s first-ever Associate Vice Provost for Data Science; she served as Principal Investigator of the nation’s first NSF grant to develop a graduate data science curriculum; and she played an integral role in designing and implementing UW’s undergraduate data science curriculum. She really understands how to partner.”
Balazinska joined the Allen School faculty in 2006, the same year she completed her Ph.D. at MIT. A co-leader of the Database and Data Science groups and an affiliate faculty member in the UW Reality Lab, Balazinska’s primary research focus is in the field of database management systems. Her current research spans data management for data science, big data systems, cloud computing, and image and video analytics. With regard to the latter, Balazinska has recently turned her attention to the development of data management techniques for augmented and virtual reality systems because, as she put it, “Why should the computer graphics and vision people have all the fun?”
Balazinska has made multiple, enduring contributions to the field during her career. For example, her work on novel techniques for increasing fault tolerance in distributed stream processing — at the time, an emerging class of data-intensive applications deployed in an increasing number of domains that included computer networking, financial services, medical information systems, and the military — earned a Test of Time Award in 2017 from the Association for Computing Machinery’s Special Interest Group on the Management of Data (ACM SIGMOD). She also received a 10-Year Most Influential Paper Award from the Working Conference on Reverse Engineering (WCRE) in 2010 for her work on advanced clone analysis for automatically refactoring software code. In addition, Balazinska’s body of work in scalable distributed data systems inspired the Very Large Data Bases (VLDB) conference — the flagship international conference on database research — to honor her with the inaugural Women in Database Research Award. In addition to her own research, Balazinska has also contributed to efforts to build up the regional database research community, co-founding the Northwest Database Society (NWDS) to bring together scholars and practitioners focused on databases and database management systems in the Pacific Northwest.
“Magda brings to this new leadership position not just a wealth of experience, but the type of vision and ability to work with people that will help keep the University of Washington and our entire tech community on a successful path,” Microsoft President Brad Smith told GeekWire.
Previously, Balazinska received an NSF CAREER Award, which supports the most promising early-career scientists and engineers. She is also a past recipient of a Microsoft Research New Faculty Fellowship; an HP Labs Innovation Research Award; two Google Faculty Research Awards; and multiple best paper awards. Before enrolling in MIT’s graduate program in Computer Science, her bachelor’s and master’s degrees in Computer Engineering and Electrical Engineering, respectively, from the Ecole Polytechnique de Montréal.
“I feel really good about how far we have come as a school and the direction we are headed for the future. We have an outstanding organization and culture with tremendous potential,” said Levy, who holds the Wissner-Slivka Chair in the Allen School. “Magda is an accomplished leader, gifted researcher, and forward-thinking educator who understands how computing can have a significant, positive impact on the university and on society. I am excited to see the school thrive with Magda at the helm.”
Balazinska will assume her new role effective January 1, 2020, subject to approval by the UW Board of Regents. Read the UW News release here, and a related story in GeekWire here.
Brandon Lucia (right) accepts the 2019 Young Computer Architect Award from IEEE TCCA chair Josep Torrellas.
Allen School alumnus Brandon Lucia (Ph.D., ‘13) has been recognized by the IEEE Computer Society’s Technical Committee on Computer Architecture with the 2019 Young Computer Architect Award. This award recognizes an outstanding researcher who has completed their doctoral degree within the past six years and who has made innovative contributions to the field of computer architecture. Lucia, who completed his Ph.D. working with Allen School professor Luis Ceze and is now a faculty member in Electrical & Computer Engineering at Carnegie Mellon University, was recognized for “pioneering research in parallel debugging and intermittent computing.”
Lucia devoted his early research career to the development of novel approaches for concurrency debugging and failure avoidance for parallel and concurrent software such as shared-memory multi-threaded programs. Unlike sequential software, parallel and concurrent software relies on concurrent computations and an ordering of program events that varies with each execution. These qualities make pinpointing bugs a particularly challenging process. In response, Lucia and his collaborators developed a string of techniques that blended computer architecture and systems support to make it easier to find and fix concurrency bugs and minimize the risk of schedule-dependent failures that tend to erode system reliability. He was among the first researchers to devise mechanisms for automatically avoiding such failures ― typically the result of latent concurrency bugs discovered only after software is put into production ― without altering program semantics. His contributions include Atom-Aid, which capitalizes on the natural tendency for systems with implicit atomicity to prevent some schedule-dependent failures; ColorSafe, a scheme for applying colors to groups of data that makes it easier to avoid multi-variable atomicity violations in programs; and Aviso, a software system for automatically avoiding schedule-dependent failures by generating schedule constraints that disrupt the order of events based on historical failed executions.
Since his arrival at CMU, Lucia and his students in the Abstract Research Group have focused on the development of intermittent computing, including the design of software and hardware systems for addressing reliability issues and energy storage needs in battery-less devices. This rapidly growing area of research focuses on enabling computation, sensing, and communication with devices that harvest ambient energy to power their operations for a variety of real-world ― and out-of-this-world ― applications in potentially extreme environments. To advance this burgeoning technology, Lucia led a team of researchers in developing a new energy storage architecture, Capybara, that can be dynamically reconfigured in response to varied applications’ energy demand. Their work earned the Best Paper Award at ASPLOS 2018 and an Honorable Mention in IEEE MICRO’s Top Picks last year. Other contributions include Chinchilla, a compiler and run-time system for supporting the efficient, intermittent operation of energy-harvesting devices through adaptive dynamic checkpointing, and the Energy-Interference-Free Debugger (EDB), a tool for monitoring and debugging intermittent systems without adversely impacting their energy state that was selected as an IEEE MICRO Top Pick in 2017.
Lucia collected his latest accolade at the 46th International Symposium on Computer Architecture (ISCA 2019) this week in Phoenix, Arizona. He is not the first with an Allen School connection to earn the Young Computer Architect Award since its inception in 2011. Last year, fellow 2013 alumnus Hadi Esmaeilzadeh was recognized for his contributions to novel computer architectures in machine learning and approximate computing, and their mentor Ceze was recognized in 2013 for his work on improving multi-core programmability and correctness.
When someone’s heart stops beating during cardiac arrest, rapid administration of cardio-pulmonary resuscitation (CPR) can save that person’s life. However, a significant number of cardiac arrest incidents take place outside of a hospital setting where help may not be immediately at hand, with around 90% of those incidents resulting in death. An estimated 300,000 people in North America alone die from out-of-hospital cardiac arrests (OHCA) each year. The vast majority of these deaths occur in the person’s home, often in the bedroom where they may be out of sight and out of earshot of potential help. But now, users of Alexa and other smart devices who may be at risk can take heart from a new artificial intelligence system developed by researchers at the Allen School and UW Medicine.
A team led by professor Shyam Gollakota of the Networks & Mobile Systems Lab and Dr. Jacob Sunshine of the Department of Anesthesiology & Pain Medicine has developed a way to turn smart speakers and smartphones into contactless heart monitoring devices capable of detecting instances of agonal breathing — an indicator that someone is suffering a cardiac arrest — with the goal of immediately alerting family members or emergency services. The system employs AI to distinguish agonal breathing from other types of breathing in real-time within a bedroom environment, even in the presence of other sounds, with 97% accuracy. The team, which includes Allen School Ph.D. student Justin Chan, first author on the paper, and Dr. Thomas Rea of UW Medicine and King County Medic One, published their results in the Nature journal npj Digital Medicine.
Agonal breathing is a distinctive type of disordered breathing that arises from a brainstem reflex in a person suffering severe hypoxia, or oxygen deprivation. Often described as a person taking gasping breaths, agonal breathing is present in roughly half of cardiac arrest cases reported to emergency services dispatchers. With the proliferation of smartphones and smart speakers like the Amazon Echo and Google Home — projected to be in 75% of U.S. households by next year — the researchers saw an opportunity to combine the capabilities of these increasingly popular devices with a distinctive audible biomarker of a life-threatening medical emergency to enable early detection and intervention, even in cases where the patient may be completely alone. In addition to private residences, the system could be deployed in unmonitored health care settings such as hospital wards, nursing homes, and assisted living facilities.
“We envision a contactless system that works by continuously and passively monitoring the bedroom for an agonal breathing event, and alerts anyone nearby to come provide CPR,” Gollakota said in a UW News release. “And then if there’s no response, the device can automatically call 911.”
The research team, clockwise from top left: Justin Chan, Shyam Gollakota, Thomas Rea, and Jacob Sunshine
The team trained its AI to recognize the sound of agonal breathing using nine years’ worth of actual 911 calls to King County Emergency Medical Services. Those calls included 19 hours of recorded instances of agonal breathing, from which the researchers extracted 236 clips. To ensure the system would be practical in a real-world setting like someone’s bedroom, the team played the clips over distances between one and six meters, with and without the addition of ambient indoor and outdoor noises that might be picked up by a smart speaker during the night.
“We played these examples at different distances to simulate what it would sound like if it the patient was at different places in the bedroom,” Chan explained. “We also added different interfering sounds such as sounds of cats and dogs, cars honking, air conditioning, things that you might normally hear in a home.”
Since the researchers envision their system ultimately being used to not only detect signs of cardiac arrest but also to summon help, Chan and his colleagues needed to minimize the chances of false positives. To that end, they trained their system to distinguish between agonal and non-agonal respiration using 83 hours of audio recordings taken during polysomnographic sleep studies. Those recordings included examples of normal breathing, snoring, hypopnea, and central and obstructive apnea — all conditions that reasonably could be expected to be picked up by a smart speaker placed in a person’s bedroom.
In addition to accounting for practical considerations, the researchers also aimed to protect user privacy. According to Gollakota, the system is intended to be deployed as an app or Alexa skill in which the data is stored locally. “It’s running in real time, so you don’t need to store anything or send anything to the cloud,” he noted.
The system is currently in the proof-of-concept stage. The next step, Gollakota says, is to obtain more 911 call data from beyond the greater Seattle area in order to further refine the algorithm and ensure that it generalizes across a broader population. The team also notes in its paper that real-world implementation would require the addition of a user interface that provides the option to cancel any false alarm before activating an emergency medical response. The team plans to commercialize its system through Sound Life Sciences, Inc., a UW spinout that is also commercializing Second Chance, a contactless mobile app developed by some of the same researchers that detects signs of an opioid overdose.
On Friday, the Paul G. Allen School celebrated the Class of 2019 as the graduates embarked on the next stage in their academic or professional journeys. In addition to granting roughly 575 total degrees this year — including around 400 bachelor’s degrees — the Allen School celebrated the contributions of two outstanding alumni, Joe Heitzeberg and Tessa Lau, and welcomed speaker Maria Klawe, President of Harvey Mudd College, who sent the new graduates on their way with words of wisdom and inspiration.
As is tradition, Allen School Director Hank Levy opened the proceedings by welcoming the nearly 2,500 family and friends in attendance at the University of Washington’s Hec Edmundson Pavilion in the Alaska Airlines Arena. This year was especially poignant since it was Levy’s last at the helm of the program he has led for the past 13 years. When he turned the podium over to professor Ed Lazowska, Levy was asked to remain on stage while the latter paid tribute to what he has accomplished during his tenure — first as chair of the department, and then as the first-ever director of the school. Along the way, Levy presided over a tripling of the undergraduate student body and a doubling of our graduate program while overseeing the design and construction of a second building, the Bill & Melinda Gates Center, to enable the school’s continued expansion.
“Hank took us from being an excellent computer science program to an elite one,” Lazowska said, as Levy received a standing ovation from the assembled graduates, faculty, and guests.
Hank Levy (left) is honored by Ed Lazowska for his 13 years of leadership
Special guest Maria Klawe — the first woman President of Harvey Mudd College and previously, first woman Dean of Engineering at Princeton University — continued on that theme as she reminded the assembled graduates that “you are graduating from one of the very, very, very best computer science departments in the world.”
Klawe, who has made increasing diversity in science and engineering disciplines one of the hallmarks of her career, urged the graduates to speak up when it comes to supporting diversity in their field. When it comes to gender, race, sexual orientation, and income status, “These things should have absolutely nothing to do with whether you become a computer scientist,” she said. Noting that the field will never meet the demand for talent unless it recruits women and underrepresented minorities, she suggested there was an even more compelling reason for it to do so. “Diverse teams find better solutions,” she said, crediting the Allen School for being ahead of its peers when it comes to diversity.
Maria Klawe, President of Harvey Mudd College, tells graduates to believe that they can have impact in the world
Klawe also touched upon another topic that often comes up in conversations about diversity and belonging: imposter syndrome. Although she did not explicitly use the phrase, Klawe acknowledged that even she sometimes awoke with a “voice of failure” in her head. Her advice to graduates who experienced the same? “Don’t listen,” Klawe said. “Believe that you can have impact in the world. Believe that you can take on major challenges.”
“You are going to be amazing,” she concluded, “and I am so proud to be here at your commencement ceremony.”
To drive home the point, Lazowska retook the stage to announce the 2019 recipients of the Allen School Alumni Impact Awards. The award recognizes two alumni annually who are building on their Allen School education to change the world. The first honoree, Tessa Lau (Ph.D., ‘01), earned her degree working with professor Daniel Weld on machine learning with an emphasis on human-computer interaction and intelligent systems “before machine learning became cool and everybody started doing it,” as Lazowska put it. Lau spent 11 years at IBM Research before joining Willow Garage, where she developed simple interfaces for personal robots. Having once held the title of “Chief Robot Whisperer” at a company she co-founded, Savioke, that produced the world’s first hotel delivery robot, Lau is currently founder and CEO of Dusty Robotics. Her goal, as Lazowska put it, is to enable robots to do “real work, in the real world, alongside real people.”
Honoring our alumni (left to right): Ed Lazowska, Joe Heitzeberg (B.S., ’95), Tessa Lau (Ph.D., ’01), and Hank Levy
The second honoree, Joe Heitzeberg (B.S., ‘95), has had a varied and successful career in the startup world. Following his graduation from UW, Heitzeberg began his career as a software engineer at Paul Allen-backed StarWave. After returning to school to earn his MBA at MIT’s Sloan School of Business, he built a string of successful startups beginning with SnapVine, which was acquired by WhitePages, and MediaPiston, which was acquired by oDesk, before taking the helm at Madrona Venture Labs, a “startup studio” that builds startups from scratch and spins them out as independent companies. Heitzeberg’s latest venture is Crowd Cow, a company that he co-founded to connect farmers and consumers to help people access high-quality craft meat.
In addition to awarding degrees, the Allen School honored a number of students and faculty for academic excellence, mentorship, research, and service. Allen School advisers Crystal Eney and Raven Avery kicked off the proceedings by recognizing two graduating seniors with Service Awards: Aishwarya Mandyam and Alex Banh. Mandyam, who earned bachelor’s degrees in Computer Science and Philosophy with a minor in Neural Computation & Engineering, served as a member of the Allen School’s Diversity Committee and President of the UW chapter of the Association for Computing Machinery (UW ACM). Her passion for building an inclusive community for her peers previously earned her a place among the Husky 100. Banh, a Computer Science major, served as lead ambassador for the CSE Ambassadors program that engages thousands of pre-college students each year in computer science activities. He also served as the Allen School advising team’s first full-time summer outreach assistant.
Nearly 2,500 family and friends joined the celebration
The Best Senior Thesis Award went to Nelson Liu, who earned his degree in Computer Science and Linguistics working with professor Noah Smith of the Allen School’s Natural Language Processing Group. Liu completed his thesis on the use of recurrent neural networks in natural language processing that included a new discovery about the ability of RNNs to “remember” farther into the past if the data they are trained on has the properties of natural language. Liu’s work earned a Best Paper Award at the Association for Computational Linguistics’ Workshop on Representational Learning for NLP, and according to Smith, will change the way the NLP field thinks about RNNs — an example of Liu’s “high motivation to do things no one has done before,” he said. Liu will pursue a Ph.D. in Computer Science at Stanford University.
Five graduating students were recognized with Outstanding Senior Awards: Ryan Feng, Nelson Liu, Alison Ng, Mitali Palekar, and Hannah Werbel. Feng, who earned his bachelor’s in Computer Engineering, has excelled in the classroom and in the lab as an undergraduate researcher in the Networks & Mobile Systems Lab led by professor Shyam Gollakota and the Personal Robotics Lab led by professor Siddhartha (Sidd) Srinivasa. Liu was called to the stage a second time in recognition of his research that had earned him Best Senior Thesis as well as a Graduate Research Fellowship from the National Science Foundation. Ng, who majored in Computer Engineering, was previously recognized among the Husky 100 for her leadership on the Allen School’s Student Advisory Council and service to her fellow students as a peer adviser. Palekar, another Husky 100 honoree and Allen School peer adviser, earned her degree in Computer Science with interdisciplinary honors and served as President of the UW chapter of the Society of Women Engineers. Last but not least, Werbel, who graduated with a degree in Computer Science with interdisciplinary honors and minors in Mathematics and Physics, distinguished herself during her time at UW by earning both the President’s Freshman Medal and the Dean’s Medal from the College of Arts & Sciences.
Class of 2019 in software-developer speak
UW ACM Chair Armaan Sood announced lecturer Justin Hsia as the recipient of the 2019 ACM Teaching Award, which is presented to an outstanding faculty member on behalf of the student body. Hsia was cited for his commitment to making complicated (“or even dull”) topics interesting and engaging, and for encouraging students to provide feedback throughout his courses. He was also celebrated for his focus on improving the teaching assistant (TA) experience. It was fitting, then, that Hsia later returned to the stage to recognize some of those very TAs with the Bob Bandes Memorial Excellence in Teaching Awards. These awards honor outstanding TAs who devote themselves to promoting computer science education and giving back to the school community. The three winners were master’s graduate Joshua Fan, who TAed for multiple courses, primarily Foundations of Computing 2; Cherie Ruan, who served as TA coordinator for the school’s introductory programming courses while earning her bachelor’s in Computer Science and Informatics; and Robert Weber, a current Ph.D. student in the Theory of Computation group who has TAed for multiple courses related to data structures and algorithms. Honorable mentions went to Avidant Bhagat, a Computer Science graduate who TAed for Software Design & Implementation every quarter this year; Zachary Chun, who graduated with a bachelor’s in Computer Science after TAing for 10 quarters, including introductory programming and data structures courses; and Erik Hoberg, who TAed for nine quarters in a variety of courses, many geared toward non-majors.
After handing out diplomas and hooding the Ph.D.s, Levy closed his final Allen School graduation celebration with some parting words to the newly-minted graduates. “I’d like to say one more thing to our students,” he said. “You’re part of the Allen School CSE community, and we want to continue to be an active part of your lives. Basically, you’re stuck with us forever!”
Congratulations to the Class of 2019 — and thank you, Hank, for 13 years of outstanding leadership, service, and friendship to the Allen School community!
“I’m biased, but I like to say that there’s never been anything like computer science. I don’t think in history there’s been anything that’s been on an exponential growth curve for 50 years without stop. And that gives you some remarkable things.” – Hank Levy, Director of the Allen School & Wissner Slivka Chair in Computer Science & Engineering
After 13 years at the helm of the University of Washington’s Computer Science & Engineering program — first as department chair, and then the first-ever director of the Paul G. Allen School — professor Hank Levy will step down at the end of June. In a wide-ranging conversation with reporter Todd Bishop, Levy reflected on the change he has witnessed in the field of computing, in how we educate the next generation of computer scientists and engineers, and in the size and reach of the local technology community in the latest GeekWire podcast.
Allen School senior Hannah Werbel is among four undergraduates to earn the prestigious Dean’s Medal from the University of Washington’s College of Arts & Sciences. Werbel, who will receive her bachelor’s in Computer Science with minors in Physics and Mathematics this month, was named a Dean’s Medalist in the Natural Sciences category for her academic excellence, leadership, and service.
From the moment she stepped on campus, Werbel has distinguished herself through a rigorous program of study and her participation in a variety of extra-curricular and volunteer activities. In her sophomore year, she earned the Freshman Medal as part of the UW President’s Medalist Awards in recognition of her high academic standing and campus involvement. Outside of the classroom, Werbel has played the piccolo as part of the Husky Marching Band for the past four years, frequently volunteering her time and talents for smaller alumni and charity functions in addition to her regular band duties. Her efforts earned her the Bill Bissel Memorial Award last year, which recognizes the student who most embodies the band’s “touch of class” motto.
Werbel, who is legally blind, has made accessibility a centerpiece of her campus engagement. She has served as president of the Washington Association of Blind Students since her freshman year and also worked as a student assistant for the DO-IT Center, which focuses on empowering people with disabilities to succeed through education and technology. In that role, Werbel planned events for high school students participating in the center’s summer college preparatory program and spoke at a variety of events about accessibility in higher education and the STEM (science, technology, engineering, and mathematics) fields. In 2017, Werbel was selected to participate in the Lime Connect Fellowship Program, which offers professional and leadership development opportunities to outstanding juniors with disabilities.
In addition to being an accomplished student, accessibility advocate, and musician, Werbel excelled in research. Even before her arrival on campus, Werbel completed a summer research internship in the UW BioRobotics Lab during her junior year of high school. As part of her internship, she programmed software modules in MATLAB to analyze data generated from experiments with brain-computer interfaces. The research team was so impressed with Werbel’s work, she was invited to continue working in the lab after her internship ended. Werbel also spent two quarters as a teaching assistant for the Allen School’s introductory computer science class, CSE 142. She was recognized with the Outstanding Female Engineer Award from the UW chapter of the Society of Women Engineers in 2017.
“Hannah’s time at UW has been marked by interdisciplinary academic excellence and leadership inside and outside of the classroom,” said Hank Levy, Director of the Allen School and Wissner-Slivka Chair. “She is humble, intelligent, hard-working, and inspirational. Hannah joined our undergraduate program as an interest-changer after her sophomore year, and she has only reached the beginning of her potential in the field of computer science. She likely doesn’t quite know how special she is and how far her talent will take her, and I hope this recognition pushes her to even greater heights.”
Alternately described as “dedicated,” “selfless,” and “an ambassador for the University,” Werbel has helped make the campus community a better place than when she found it. Following her graduation from the Allen School, Werbel will spend the summer as a research intern with Microsoft Quantum Computing before joining Facebook full-time as a software engineer.
What makes Grover so effective at spotting fake news is the fact that it was trained to generate fake news itself.
When we hear the term “fake news,” more often than not it refers to false narratives written by people to distort the truth and poison the public discourse. But new developments in natural language generation have raised the prospect of a new potential threat: neural fake news. Generated by artificial intelligence and capable of adopting the particular language and tone of popular publications, this brand of fake news could pose an even greater problem for society due to its ability to emulate legitimate news sources at a massive scale. To fight the emerging threat of fake news authored by AI, a team of researchers at the Allen School and Allen Institute for Artificial Intelligence (AI2) developed Grover, a new model for detecting neural fake news more reliably than existing technologies can.
Until now, the best discriminators could correctly distinguish between real, human-generated news content and AI-generated fake news 73% of the time; using Grover, the rate of accuracy rises to 92%. What makes Grover so effective at spotting fake content is that it learned to be very good at producing that content itself. Given a sample headline, Grover can generate an entire news article written in the style of a legitimate news outlet. In an experiment, the researchers found that the system can also generate propaganda stories in such a way that readers rated them more trustworthy than the original, human-generated versions.
“Our work on Grover demonstrates that the best models for detecting disinformation are the best models at generating it,” explained Yejin Choi, a professor in the Allen School’s Natural Language Processing group and a researcher at AI2. “The fact that participants in our study found Grover’s fake news stories to be more trustworthy than the ones written by their fellow humans illustrates how far natural language generation has evolved — and why we need to try and get ahead of this threat.”
Choi and her collaborators — Allen School Ph.D. students Rowan Zellers, Ari Holtzman, and Hannah Rashkin; postdoctoral researcher Yonatan Bisk; professor and AI2 researcher Ali Farhadi; and professor Franziska Roesner — describe their results in detail in a paper recently published on the preprint site arXiv.org. Although they show that Grover is capable of emulating the style of a particular outlet and even writer — for example, one of the Grover-generated fake news pieces included in the paper is modeled on the writing of columnist Paul Krugman of The New York Times — the researchers point out that even the best examples of neural fake news are still based on learned style and tone, rather than a true understanding of language and the world. So, that Krugman piece and others like it will contain evidence of the true source of the content.
“Despite how fluid the writing may appear, articles written by Grover and other neural language generators contain unique artifacts or quirks of language that give away their machine origin,” explained Zellers, lead author of the paper. “It’s akin to a signature or watermark left behind by neural text generators. Grover knows to look for these artifacts, which is what makes it so effective at picking out the stories that were created by AI.”
The research team, top row from left: Rowan Zellers, Ari Holtzman, Hannah Rashkin, and Yonatan Bisk. Bottom row from left: Ali Farhadi, Franziska Roesner, and Yejin Choi.
Although Grover will naturally recognize its own quirks, which explains the high success rate in the team’s study, the ability to detect evidence of AI-generated fake news is not limited to its own content. Grover is better at detecting fake news written by both human and machine than any system that came before it, in large part because it is more advanced than any neural language model that came before. The researchers believe that their work on Grover is only the first step in developing effective defenses against the machine-learning equivalent of a supermarket tabloid. They plan to release two of their models, Grover-Base and Grover-Large, to the public, and to make the Grover-Mega model and accompanying dataset available to researchers upon request. By sharing the results of this work, the team aims to encourage further discussion and technical innovation around how to counteract neural fake news.
According to Roesner, who co-directs the Allen School’s Security and Privacy Research Laboratory, the team’s approach is a common one in the computer security field: try to determine what adversaries might do and the capabilities they may have, and then develop and test effective defenses. “With recent advances in AI, we should assume that adversaries will develop and use these new capabilities — if they aren’t already,” she explained. “Neural fake news will only get easier and cheaper and better regardless of whether we study it, so Grover is an important step forward in enabling the broader research community to fully understand the threat and to defend the integrity of our public discourse.”
Roesner, Choi and their colleagues believe that models like Grover should be put to practical use in the fight against fake news. Just as sites like YouTube rely on deep neural networks to scan videos and flag those containing illicit content, a platform could employ an ensemble of deep generative models like Grover to analyze text and flag articles that appear to be AI-generated disinformation.
“People want to be able to trust their own eyes when it comes to determining who and what to believe, but it is getting more and more difficult to separate real from fake when it comes to the content we consume online,” Choi said. “As AI becomes more sophisticated, a tool like Grover could be the best defense we have against a proliferation of AI-generated fake news.”
The Bottomline team, left to right: Lukas Joswiak, Elton Carr, Mitali Palekar, Adam Towers, and Mayank Maheshwari (Not pictured: Jeremy Peronto).
Bottomline, a startup co-founded by students in the Allen School and Foster School of Business at the University of Washington, earned third place at the recent Dempsey Startup Competition hosted by the UW Foster School’s Buerk Center for Entrepreneurship. The company provides data analytics that empowers job candidates and employers in the technology sector to evaluate the value and competitiveness of multiple job offers. Bottomline was co-founded by Allen School seniors Lukas Joswiak and Mitali Palekar, sophomore Adam Towers, professional master’s student Elton Carr, and Mayank Maheshwari and Jeremy Peronto of the Foster School’s evening MBA program.
Working under the motto “no two offers are created equally,” the team behind Bottomline focused on bringing more transparency and equity to technology recruitment and compensation practices. To that end, they developed a service that breaks down the various components of complex job offers to enable candidates to compare their relative value. The resulting “bottom line” for each offer accounts for variables that contribute to a candidate’s overall compensation, including base salary, stock options, bonuses, benefits, and more. Candidates can adjust the comparison to account for external factors, such as regional cost of living and local taxes, to understand how these will affect their take-home pay.
The same data that helps individual candidates to assess the value of each offer received can also be used by recruiters, hiring managers, and businesses interested in analyzing how their company’s compensation packages measure up to those of their peers. With the help of Bottomline, employers are able to gauge how their offers compare to the rest of the industry and stay abreast of compensation trends to ensure they remain competitive in the quest for talent. The service is also useful for ensuring that companies are offering fair and equitable compensation across their workforce.
“Given the increasing focus on hiring, promotion and compensation practices across the tech industry, the concept behind Bottomline couldn’t be more timely,” noted Allen School professor Ed Lazowska. “Not only that, but the team executed on that idea in a way that benefits those on both sides of the interview table, bringing more clarity and transparency to what can be a fraught — not to mention opaque — process. It is great to see our students take on this challenge and come up with a service that will not only empower job seekers and inform recruiters, but also encourage equitable practices across the industry as a whole.”
Bottomline grew out of a class project for the Allen School’s entrepreneurship course, CSE 599, taught by Lazowska and Greg Gottesman, Managing Director of Pioneer Square Labs. The course, which is open to students in the Allen School, Foster School MBA program, Human-Centered Design & Engineering master’s program, and Interaction Design program, provides a hands-on, team-based experience in what it takes to build a company, from startup to exit. Along the way, students learn how to validate an idea with potential customers, assess potential financing strategies, hone their investor pitch, develop a product as well as a go-to-market and operating plan, and deal with legal issues associated with launching a new business. Those lessons would prove invaluable to the Bottomline founders as they progressed through the competition.
“We would not have been anywhere without this class,” said Palekar, one of Bottomline’s student co-founders who will graduate from the Allen School this month. “Throughout the quarter, we iterated week after week on our idea based on feedback from experienced entrepreneurs, whose insights helped us understand what would and wouldn’t work. Moreover, we received an immense amount of constructive criticism and guidance in terms of our pitch as well as our business models — things that had previously not been our strong suit. We are immensely grateful for this class for giving us the platform to come up with an idea, refine our product, and create a sustainable business over the long term.”
The class instructors were just as impressed with the team’s work ethic and entrepreneurial spirit. “I love this team, it’s just a perfect mix of computer science students and MBAs,” said Gottesman. “The interesting part of the Bottomline story is how entrepreneurial they were as a team. The compensation and offer-analytics idea was not even the first one they worked on in the class — they killed an earlier project based on customer feedback and pivoted to this new space, because several of the team members had direct experience comparing multiple offers. They then executed on the product like rabid dogs.”
The Dempsey Startup Competition, formerly known as the Business Plan Competition, attracted a total of 113 submissions from teams at 16 schools across the Pacific Northwest and British Columbia. Bottomline advanced through the first stage of competition in April, when it was among 36 teams chosen to compete for a “sweet 16” spot and earn a shot at being among the finalists last month. The students’ third-place finish was the highest of any UW competitor, earning them the “Friends of the Dempsey Startup” Prize and a check for $7,500. Brennan Colberg, a sophomore in the Allen School, contributed to the team in the early stages of the competition.
