The Allen School has a proud tradition of nurturing undergraduate student researchers whose work has the potential for real-world impact. This year, three of those students — Jerry Cao, Mike He and Yu Xin — earned honorable mentions from the Computing Research Association (CRA) as part of its 2022 Outstanding Undergraduate Researcher Awards competition for their contributions in health sensing and fabrication, programming languages and machine learning, and building robust computer systems.
Jerry Cao
The CRA recognized senior Jerry Cao, who is majoring in computer science and applied mathematics, for his research in health sensing and fabrication. Advised by professors Jennifer Mankoff and Shwetak Patel, his work aims to apply computing and fabrication to improve individuals’ quality of life. To reduce the burden of health monitoring and make it easier for users to prototype custom tools that fit their personalized needs, Cao is creating a wearable device in compression sleeve-form for the leg that records changes in the blood volume in the body’s superficial tissue. This can help predict the onset of adverse symptoms throughout the day for conditions such as Postural Orthostatic Tachycardia Syndrome (POTS) where blood flow is improperly regulated throughout the body.
Cao is also working on a project to rapidly prototype physical objects. He aims to reduce the number of iterations — currently requiring several to reach the final product — by reconfiguring a model to support real-time iteration. He is developing a pipeline to take a parametric model and produce a reconfigurable prototype where each parameter can be adjusted up to a specified and allowed range. Users can more easily change the size of the physical model this way and record all the necessary measurements to fabricate a final version. For example, when building a cabinet, builders must ensure it fits in its designated space. The reconfigurable prototype will limit the iterations and allow users to explore different configurations of the object, then create the final version using actual materials.
Mike He
Mike He, a senior studying computer science, was acknowledged for his work in programming languages, formal verification, compilers and machine learning systems. Advised by professor Zachary Tatlock, He worked with the Allen School’s PLSE group on Dynamic Tensor Rematerialization (DTR), an algorithm that trains deep learning models under constrained memory budgets. Since deep learning models use up a lot of GPU memory while training, He and his colleagues created DTR to train these models under restricted memory budgets. DTR removes restrictions on classic compilers and when memory fills up, DTR evicts the oldest, stalest, cheapest-to-recompute tensor to make room for the next allocation. If the training loop later tries to access a previously evicted tensor, DTR recomputes it on demand by tracking operator dependencies.
In addition to his contributions to DTR, He led the push to develop new flexible accelerator matching compiler techniques to easily target new hardware accelerators in deep learning frameworks. To do so, the team is enabling devices to be more easily incorporated into an existing DL framework and, in principle, for formal functional verification down to the hardware implementation. The project, 3LA, has a built-in pattern-matching algorithm that can find accelerator supported workloads in deep learning models using equality saturation. The project addressed the mapping gap between deep learning models represented in high-level domain-specific languages and specialized accelerators using instruction-level abstraction as the software-hardware interface.
Yu Xin
Yu Xin, a senior studying computer science and applied and computational mathematical science, was honored by the CRA for his work with Allen School professor Arvind Krishnamurthy in building effective and robust computer systems. In particular, Xin worked to develop a scheduler for serving deep learning inference tasks. Applications using cloud-based deep learning models, when deployed on a large scale, tend to flood data center GPU clusters, slowing down the time it takes to respond and causing delays and extra expense. To help with the cost and speed, Xin and his collaborators created Symphony, a centralized dispatcher to satisfy requests within a latency bound, ensuring load-balance across GPUs and maximizing their efficiency by using appropriate dynamically-sized batches of inference requests. By loading dozens of deep learning models on each GPU, Symphony enables burst amortization across models and has the potential to eliminate the need for overprovisioning. Enabling multiple dispatchers for better scalability, Xin designed an algorithm to partition the model space into many disjoint subsets in which each dispatcher handles one of the models. The algorithm finds the partitioning scheme that minimizes the deviation between partitions in terms of total request rates and model sizes by generating and solving a Mixed Integer Linear Programming (MILP) problem.
Xin’s previous work includes developing tools for analyzing images of proteins generated from a cryo-electron microscope. For example, filtering out high-frequency noises by generating an artificial image based on a mathematical model and comparing it against every patch of the image to see if there is a match and then output all the matched results. This approach saves researchers time while increasing their effectiveness by directing their attention to the most relevant sites.
During their time at the Allen School, recent alumni Maarten Sap (Ph.D., ‘21) and Ivan Evtimov (Ph.D., ‘21) tackled some of the thorniest issues raised by emerging natural language processing and machine learning technologies — from endowing NLP systems with social intelligence while combating inequity and bias, to addressing security vulnerabilities in the convolutional neural networks that fuel state-of-the-art computer vision systems. Recently, the faculty honored both for their contributions with the William Chan Memorial Dissertation Award, which was named in memory of the late graduate student William Chan to recognize dissertations of exceptional merit. Evtimov earned additional recognition for his work from the Western Association of Graduate Schools and ProQuest as the recipient of the WAGS/ProQuest Innovation in Technology Award, which recognizes distinguished scholarly achievement at the master’s or doctoral level.
Sap — who is currently a postdoctoral/young investigator at the Allen Institute for AI (AI2) — worked with Allen School professors Yejin Choi and Noah Smith. His dissertation, “Positive AI with Social Commonsense Models,” advanced new techniques for making NLP systems more human-centric, socially aware and equity-driven.
“Maarten’s dissertation presents groundbreaking work advancing social commonsense reasoning and computational models serving equity and inclusion. More specifically, his work presents technical and conceptual innovations that make deep learning methods significantly more equitable,” said Choi and Smith, both of whom are also senior research managers at AI2. “Maarten’s research steers the field of NLP and its products toward a better future.”
One example is ATOMIC, a large-scale social commonsense knowledge graph Sap and collaborators created to help machines comprehend day-to-day practical reasoning about events, causes and effects. To create equity-driven NLP systems, he also helped develop PowerTransformer, a controllable text rewriting model that helps authors mitigate biases in their writing, particularly biases related to how the public describes people of different genders. Sap also tackled the problem of detecting biases and toxicity in language by identifying issues with the current hate speech detectors that lead to racial biases. His work introduced Social Bias Frames, a linguistic framework for explaining the biased or harmful implications in text. The papers supporting this, The Risk of Racial Bias in Hate Speech Detection and Social Bias Frames: Reasoning about Social and Power Implications of Language were nominated for a Best Short Paper Award by the Association for Computer Linguistics in 2019 and won the Best Paper Award at the West Coast NLP Summit in 2020, respectively. Sap was also a member of the team that won the first Amazon Alexa Prize for a conversational chatbot called Sounding Board that engages with users about current topics.
Evtimov’s dissertation, “Disrupting Machine Learning: Emerging Threats and Applications for Privacy and Dataset Ownership,” makes significant contributions to the security of adversarial machine learning. His research as a member of the Allen School’s Security & Privacy Research Lab focused particularly on the vulnerabilities of convolutional neural networks (CNN) that allow maliciously crafted inputs to affect both their inference and training. Evtimov said that understanding new technologies in terms of security and privacy is important in order to think ahead of adversarial actors.
“Ivan’s dissertation is highly innovative, and contributed significant results to the field of real-world attacks against computer vision algorithms. His work is of fundamental importance to the field,” Allen School professor and lab co-director Tadayoshi Kohno said. “Computer vision is everywhere — in autonomous cars, in computer authentication schemes, and more. Ivan’s dissertation helps the field develop secure computer vision systems and also provides foundations for helping users protect their privacy in the face of such systems.”
Evtimov’s work shows that the vulnerabilities of CNNs exhibit a duality when it comes to security and privacy. For example, he found the computer algorithms for cameras reading traffic signs in autonomous cars could be tricked by an object as simple as a sticker on a stop sign. The sticker could fool the cameras into reading the stop sign as a speed limit sign. In the case of autonomous driving, it is critical to identify anything that could be exploited by malicious parties in such a safety-critical setting. Machine learning, Evtimov found, can also be used in an unauthorized manner. Take, for example, a search engine for facial recognition. To protect privacy, Evtimov studied the conditions in which people could flood a database full of photos gathered from the public without permission with decoys. He proposed FoggySight, a tool that involves community users uploading modified photos — for instance, labeling photos of Madonna as photos of Queen Elizabeth — to poison the facial search database and throw off searches in it. He also found ways to protect visual data released for human consumption from misuse through machine learning, including developing a protective mechanism that can be applied to the information contained in datasets before public release to prevent unauthorized parties from training their own models using the data.
Mohit Shridhar, a Ph.D. student working with Allen School professor Dieter Fox, has been named a 2022-2023 NVIDIA Graduate Fellow for his research in building generalizable systems for human-robot collaboration. Shridhar’s work is focused on connecting language to perception and action for vision-based robotics.
Shridhar aims to use deep learning to connect abstract concepts to concrete physical actions with long-term reasoning to develop robot butlers. The Fellowship will help him continue his work in building robots that learn through embodied interactions rather than from static datasets. Using his own creation CLIPort, a language-conditioned imitation-learning agent, will advance precise spatial reasoning and learning generalizable semantic representations for vision and language. Shridhar’s framework combines two-streams with semantic and spatial pathways, where the semantic stream uses an internet pre-trained vision language model to bootstrap learning. This end-to-end framework can solve a variety of language-specified tabletop tasks, from packing unseen objects to folding clothes with centimeter-level precision.
“Mohit’s CLIPort work is the first to show the power of combining general language and image understanding models with fine-grained robot manipulation capabilities,” said Fox, who leads the Allen School’s Robotics & State Estimation Lab and is senior director of robotics research at NVIDIA..
In order to communicate with the butlers, Shridhar developed the Action Learning From Realistic Environments and Directives dataset (ALFRED). This is a dataset for agents to learn mapping from natural language instructions and egocentric vision to sequences of actions for household tasks. ALFRED consists of 25,000 natural language directives, including high-level instructions like “rinse off a mug and place it in the coffee maker” and lower-level language directions like “walk to the coffee maker on the right.” Tasks given to ALFRED are more complex in terms of sequence length, action space and language than previous vision-and-language task datasets.
Taking the next step beyond communicating tasks to the robots, Shridhar wants the robots to think about long-term actions without directly dealing with the complexities of the physical world. An example he gives is telling an agent to make an appetizer with sliced apples. Without any physical interactions, ALFWorld, a simulator that enables agents to learn abstract, “textual” policies in an interactive TextWorld, will train the robot to check the fruit bowl for apples and look in the drawers for a knife to make the appetizer. Before ALFWorld, agents did not have the infrastructure necessary for both reasoning abstractly and executing concretely.
Shridhar intends to deploy ALFRED-trained models in household environments where a mobile manipulator can be commanded to perform tasks such as putting two plates on the dining table.
“I hope to build collaborative butler robots that aid and better human living,” Shridhar said.
Before coming to the Allen School, Shridhar received his Bachelor’s in Engineering from the National University of Singapore. He has interned at Microsoft Research, NVIDIA and an augmented reality startup.
Shridhar is only one of 10 students recognized by the Graduate Fellowship Program based on their innovative research in Graphics Processing Unit (GPU) computing. Previous Allen School recipients of the NVIDIA Fellowship include Anqi Li (2020) and Daniel Gordon (2019).
As the world watched COVID-19 grow from a mysterious virus in far-off places to a planetary pandemic, news outlets worked hard to keep the world informed on how, where and why it was spreading. At the start of the outbreak, Matthew Conlen, a Ph.D. student in the Allen School’s Interactive Data Lab, was working as a graphic/multimedia editor for the New York Times helping with their elections forecasting application, also known as “The Needle.” He switched gears to contribute to the paper’s coverage of the novel coronavirus as it enveloped the globe — work that contributed to stories that earned the New York Times a Pulitzer Prize in Public Service for, in part, filling “a data vacuum that helped local governments, healthcare providers, businesses and individuals to be better prepared and protected.”
Conlen’s forte is creating interactive data visualizations that do precisely that: help the public to comprehend what is happening in the country and throughout the world. In this particular case, he led a data collection effort on COVID-19 in nursing homes, and he also worked with epidemiologists and modelers to give readers an understanding of what could happen in different scenarios when schools reopened, as the vaccine rolled out and when the U.S. could reach herd immunity.
“Data journalism can provide a valuable perspective on our world, complementing traditional narrative reporting with additional context, more comprehensive accounts and increased audience engagement,” Conlen’s advisor and Allen School professor Jeffrey Heer said. “Interactive visualizations rank among the most visited and revisited pieces published by major news outlets. Though data visualization on the web has largely ‘come of age,’ a major remaining challenge is empowering more journalists — as well as educators and others — without an extensive technical background to author and collaborate on interactive articles.”
Conlen’s work, Heer said, leads on all of these fronts: publishing data-driven news at multiple major outlets and via Parametric Press, which Conlen co-founded, while simultaneously researching at the Allen School, which has resulted in new open-source languages and tools that make these articles easier to create.
“It’s a virtuous cycle of research and practice,” Heer said.
After earning dual bachelor’s degrees in computer science and applied mathematics, Conlen began working on a big data analytics platform at an advertising technology, or ad tech, company. Despite interesting technical challenges, he found more fulfilling work in journalism, using digital news tools at the Huffington Post, FiveThirtyEight, The New Yorker and NASA’s earth science communications team. He became interested in data visualization because it combines math and statistics with tough programming challenges and a creative design aspect. This combination of technical and creative elements is, he notes, hard to come by in other fields.
In the “The Beginner’s Guide to Dimensionality Reduction,” hovering over an image will display one of 800 works of art from the Metropolitan Museum of Art. Click on the image to explore.
“I’m interested in computer science generally because I think computers can be tremendously empowering tools,” Conlen said. “I want to develop systems that enable people to do things that were otherwise out of reach. It’s like giving someone superpowers but all you have to do is write some code.”
He said he saw his pursuit of a Ph.D. as the next phase of a career oriented around data visualization and digital publishing.
“Within the world of academic research I can spend more time understanding how people learn from data visualizations and interactive graphics and what makes certain designs effective, and I can engage with rich fields like human-computer interaction, or HCI, to better understand how to build effective digital tools for journalists and others.”
Combining his journalism and research, Conlen could see that visual forms are effective for communicating complex data sets. As a journalist, he understands the real-world constraints that HCI needs to account for in order to be useful in practice. He and Heer created Idyll, a toolkit that reduces the amount of effort and custom code required to make it easier to author and publish interactive articles, based on the challenges Conlen observed in the newsrooms in which he worked. The interactive capabilities of Idyll are seen in Unraveling the JPEG by graphics programmer Omar Shehata. Conlen explained that by using the interactive capabilities of Idyll, Shehata constructed a narrative walkthrough of the JPEG compression algorithm that connected with a big audience online — an audience that might not be interested to learn about that topic if not for the graphics that he made.
“It wouldn’t have been possible to create this system without the practical knowledge that I gained as a journalist or without the space and time to think deeply and build ambitious research systems that the Allen School affords,” Conlen said.
Using Idyll, this graphic was created to show how the eye works. Users hover over a part of the eye to identify the part and learn what it does. Click on the image to try. Created by the Explorable Explanations Game Jam.
“I’m regularly impressed by the resilience of my students,” Heer, who leads the Interactive Data Lab said. “Matt’s ability to bridge the worlds of professional journalism and academic research is a standout example, animated by Matt’s commitment to a more just and better-informed society.”
“Think Microsoft Word but you can create documents that are dynamically driven by databases and include interactive visualizations and graphics,” Conlen said.
Conlen defended his dissertation last week and is currently working on a short-term contract with the New York Times. In early 2022 he will continue his work on the Idyll ecosystem — the open source project received a donation from venture capitalist Albert Wegner that will allow Conlen to put more time into improving the core project and refining Idyll Studio. He will continue doing data journalism and building tools to support that work.
To view more of Conlen’s work combining journalism and data visualization, check out his collection of published articles on his website.
Earlier this month, the Allen School held a virtual celebration showcasing efforts to increase diversity in computing and honoring members of our community who have demonstrated their commitment to diversity, excellence and leadership. An annual tradition, the event this year also offered Allen School leaders an opportunity to share highlights from its five-year strategic plan to increase diversity, equity, inclusion and access (DEIA), spanning curriculum and programs, professional development, policies and procedures, internal community engagement, external outreach and budget. Allen School professor and director Magdalena Balazinksa had the happy task of introducing two undergraduate scholarship winners: senior Nayha Auradkar, recipient of the Allen AI Outstanding Engineer Scholarship for Women and Underrepresented Minorities from the Allen Institute for Artificial Intelligence (AI2), and senior Caiwei Tian, recipient of the Lisa Simonyi Prize.
Auradkar, who is enrolled in the Allen School’s B.S./M.S. program, exemplifies the goal of the AI2 scholarship to encourage students from underrepresented groups to excel in computer science and engineering and become leaders and role models in their fields. Finding a passion for machine learning and human computer interaction, Auradkar used it to conduct accessibility research in the Make4All lab with Allen School professor Jennifer Mankoff. As an undergraduate she published two papers, one aimed at analyzing the features of personal protective equipment in response to the pandemic and the other focused on automating the process of creating complex textured knitting objects to make it easier for people with mobility-related disabilities to knit. Auradkar said that as someone with a disability, accessibility research has deep personal value to her and enables her to use her skills to help other people with disabilities.
Auradkar isn’t focused solely on academics, though; she’s determined to make a difference on campus through leadership, too. She is the chair of the ACM-W, founded and leads the Allen School affinity group Ability, founded and leads Huskies Who Stutter and served as the outreach director for the Society of Women Engineers. In these roles she teaches middle school girls introductory engineering, cultivates a strong community of women in tech, promotes disability community and accessibility awareness and supports other UW students who stutter.
“This scholarship will enable me to learn from and collaborate with top research scientists, which will allow me to grow my research skills as I transition in my graduate degree,” Auradkar said. “It will also provide me with extra support in my DEIA work.”
The Lisa Simonyi Prize was established by longtime Allen School supporters Lisa and Charles Simonyi. The couple created the scholarship to recognize and support students who exemplify excellence, leadership, and diversity. This year’s recipient, Tian, is a double major in computer science and applied and computational mathematical sciences. She added the former after a data structure and algorithm course inspired a newfound interest in using programming as a tool to turn complex ideas into practice and discussing algorithms and the tradeoff between runtime and memories. Tian works in the Allen School’s UbiComp Lab with professor Shwetak Patel on developing a generalized deep learning model that uses video signals from smartphones to measure blood oxygen saturation (SpO2) levels, a crucial test in modern medicine. This work focuses on building a unified platform-agnostic model that works on all major smartphone systems.
Tian also has worked as a software development engineering intern at Amazon, a research assistant in the Make4All Lab and a research assistant at Fred Hutch. Tian co-founded a Chinese student choir group, MotE, a 50-member group that performs at festivals. She also assisted underprivileged students and provided academic support and encouragement as a math and science tutor for students at Licton Spring K-8 Public School.
“I’m really excited and honored to get this scholarship,” Tian said. “Knowing nothing about computer science before coming to UW and now graduating with this award, I think it is an evidence of my hard-work and my growth at the Allen School. It also encourages me to go further and keep learning.”
Thanks to AI2 and the Simonyis for supporting diversity and excellence, and thanks to everyone who logged on to celebrate the people who are making our school and our field a more welcoming destination for all. And congratulations to Nayha and Caiwei!
For more about the Allen School’s efforts to advance diversity in computing, please visit our website.
Researchers affiliated with the Allen School took home all three Best Paper Awards at the Association for Computing Machinery’s 28th Symposium on Operating Systems Principles (SOSP). Current Ph.D. student Jacob Van Geffen, recent alumnus James Bornholt (Ph.D.,’19), former postdoc and incoming professor Simon Peter and affiliate professor Daniel Berger contributed to the winning papers that presented new advances in debugging, distributed computing and caching.
Focused on building automated mechanisms to help engineers ensure the correctness of every change they make, ShardStore was developed to employ techniques like property-based testing and model checking with far lower overhead than traditional provable correctness. According to the team, this lightweight formal method prevented a number of issues like crash consistency and concurrency problems, before reaching production. The team plans to continue improving their techniques for cloud-based data storage.
Peter Simon
Peter, who is currently a professor at the University of Texas, Austin and will join the Allen School faculty in January, co-authored “LineFS: Efficient SmartNIC Offload of a Distributed File System with Pipeline Parallelism,” about fitting the high demands of a distributed file system (DFS) onto smart network interface cards (SmartNICs). In the paper, the team presents LineFS, a SmartNIC-offloaded, high-performance DFS with support for client-local persistent memory. LineFS moves CPU-intensive tasks to a SmartNIC, improving latency in LevelDB — a fast, key-value store — up to 80%. Korea Advanced Institute of Science and Technology researchers Jongyul Kim, Insu Jang, Jaeseong Im and Youngjin Kwon, along with Waleed Reda and Dejan Kostic from the KTH Royal Institute of Technology and Emmett Witchel also at UT Austin, contributed to the paper.
Daniel Berger
In “Kangaroo: Caching Billions of Tiny Objects on Flash,” Berger, a researcher at Microsoft and UW, and his co-authors present a new flash cache that enables more efficient caching of tiny objects — often in social media and IoT services — called Kangaroo. Kangaroo overcomes challenges in existing flash cache designs such as minimizing main memory usage, which is expensive and energy hungry, and reduces load on back-end storage systems. Additionally, Kangaroo reduces flash memory wear out, extending flash cache lifetimes by multiple years. This also helps cost and sustainability. The paper was written with Carnegie Mellon University researchers Sara McAllister, Benjamin Berg, Julian Tutuncu-Macias, Juncheng Yang, Nathan Beckman and Gregory Ganger and Facebook researchers Sathya Gunasekar and Jimmy Lu.
Professor Joshua R. Smith, who holds a joint appointment in the Allen School and the Department of Electrical & Computer Engineering, was elected into the 2021 class of Fellows of the National Academy of Inventors for his impactful creations in the fields of wireless power, communication, sensing and robotics. Smith, who leads the Sensor Systems Lab, is one of only five University of Washington faculty members to have received this prestigious award that highlights the prolific spirit of innovation in academic inventors. The NAI Fellows program was created to recognize inventors and their contributions to society, which stimulate the economy, improve and save lives, and make the world a better place. It is the highest professional distinction given solely to academic inventors.
The NAI Fellow selection process considers inventions that have been licensed or commercialized. Smith holds 48 U.S. patents and 16 international patents, 44 of which are licensed by companies. His inventions have led to hundreds of millions of dollars in product revenues, bolstering the economy and the creation of approximately 70 full-time jobs, according to Suzie Pun, a professor in the Department of Bioengineering and another UW faculty member who is an NAI Fellow.
Smith as a graduate student showing an early mobile phone with mutual capacitance sensing.
Smith’s first six patents, developed while he was a graduate student at MIT, pioneered mutual capacitance sensing and led to the creation of a smart airbag system that was included in every Honda car between 2000 and 2015. Before his arrival at UW, Smith spent five years at Intel Research Seattle, creating new capabilities in wireless power, wireless sensing and robotics. He led the creation of the Wireless Identification and Sensing Platform (WISP), the first fully programmable platform for wireless, battery-free sensing and computation powered by radio waves.
Soon after, he developed Wireless Resonant Energy Link (WREL), which uses magnetically coupled resonators to efficiently transfer wireless power even as range, orientation and load vary. With the help of a heart surgeon from Yale, Smith was able to power a ventricular assist device designed for implantation in the human body without requiring a cable through the patient’s chest, called the Free-range Resonant Electrical Energy Delivery System (FREED). This wireless power work at UW is commercialized by WiBotic, a company Smith co-founded with ECE alumnus Benjamin Waters (Ph.D., ‘15). The UW patents are also licensed for implanted heart pumps by Corisma.
Ambient backscatter devices harvest radio signals to wirelessly power communication
“Among the many outstandingly inventive engineers at Intel Research Seattle, we were especially excited that Josh joined our faculty, he is extraordinary in every imaginable respect,” said Ed Lazowska, professor and Bill & Melinda Gates Chair Emeritus at the Allen School. “He is an academic inventor and entrepreneur of the highest caliber and in the finest tradition.”
In 2013, Smith, together with Allen School professor Shyam Gollakota and a team of graduate students, developed Ambient Backscatter using existing wireless signals to provide power and communication for low-power sensing and computing devices. This next led to the creation of Passive-Wi-Fi, bringing low-power Wi-Fi to transmissions. They also invented Interscatter, using wireless transmissions over the air from one technology to another for internet-connected implanted devices. Smith also co-led the UW team behind the world’s first battery‐free phone, as well as a series of ultra-low-power battery-free wireless cameras that communicate via backscatter.
The team’s research is being commercialized by Jeeva Wireless, a UW spinout co-founded by Smith, Gollakota, and ECE alumni Vamsi Talla (Ph.D., ‘16) and Aaron Parks (Ph.D., ‘17).
Prototype of a battery-free cellphone
“Josh has a consistent record of impactful inventions,” said Pun. “I have gotten to know him through a research collaboration to develop touchscreen-based sensors for detection of pathogens such as SARS-CoV-2. Josh devised a creative method to improve detection sensitivity for the virus; he is in the process of testing this idea in his laboratory. If successful, his design could be applied for next generation biosensing devices.”
Smith also co-founded Proprio, which provides surgical visualization and navigation, together with UW neurosurgeon Sam Browd, Allen School graduate student Jim Youngquist, UW Foundation board member Ken Denman, and Michael G. Foster School of Business alumnus Gabe Jones (MBA, ‘14). Smith served on advisory councils and task forces for the United States Postal Service and the Smithsonian Institution and is an IEEE Fellow. His work has earned multiple Best Paper Awards, and he is known for his dedicated mentorship of student researchers.
A robot using non-contact pre-touch sensing to solve the Rubik’s Cube
“I feel so privileged to collaborate with my outstanding UW faculty and student co-inventors,” said Smith, who holds the Milton and Delia Zeutschel Professorship in Entrepreneurial Excellence in ECE. “And invention is just one part of a long process to bring new things into the world.
“I am very grateful to the many people who have worked so hard to take these inventions from the lab to the world, including UW CoMotion, many patent attorneys, and most of all the co-founders and employees at the companies making these technologies real.”
The Allen School is pleased to announce the 2021-22 Distinguished Lecture Series, which kicks off today. Join us over the coming season to hear from experts in microarchitecture, theoretical computer science, artificial intelligence sustainability, low-and no-power devices and a new paradigm for truly extending computer science education to all.
All lectures will take place at 3:30 p.m. in the Amazon Auditorium in the Gates Center and will be live streamed on the school’s YouTube channel.
Gabriel H. Loh will deliver a talk on Thursday, Dec. 2 about “The Motivation for Chiplets and their Adoption in AMD Processors.” Under Moore’s Law, computer systems that once took up an entire warehouse can now fit on an integrated circuit. But the rate of advancements in silicone processes has slowed recently, while manufacturing costs have risen. To address this problem, AMD has opted to break down systems on chips into smaller “chiplets.” Loh will discuss the technical challenges that spurred the company to focus on chiplets as a solution and how they were able to extend their use beyond individual processors.
At AMD Research, Loh focuses on cutting-edge technologies for CPU and GPU microarchitecture, high-speed interconnections, memory systems and component integration. He also oversees patent generation activities. Loh earned the ACM SIGARCH Maurice Wilkes Award from the Association for Computing Machinery’s Symposium on Computer Architecture for his contributions to the field.
Wu’s research at Facebook focuses on high-performance and energy-efficient architecture through hardware heterogeneity, energy harvesting techniques for emerging computing devices, and temperature and energy management for portable electronics. She recently veered into designing systems for machine learning execution at scale as part of her drive to tackle system challenges to enable more efficient, responsible AI.
Carole-Jean Wu will give a lecture on Dec. 9 called “Scaling AI Sustainably: Environmental Implications, Challenges and Opportunities.” Wu’s talk will explore the increasing carbon footprint of AI computing and how hardware and software design and at-scale optimization can reduce the overall impact. She will also discuss new research directions that can help ensure the field of AI advances in an environmentally responsible way.
Jan. 20: Josiah Hester, Breed Chair of Design, Segal Faculty Fellow, and professor of computer engineering at Northwestern University
Josiah Hester will deliver a talk on Jan. 20 called “Batteries Not Included: Reimagining Computing for the Next Trillion Devices.” Powering computer systems in the future needs to rely less on batteries and wall outlets and more on less expensive, sustainable means. Hester will discuss a rethinking of hardware, software, design and tool creation that isn’t dependent on current power systems and what research in that field will look like in the next 10 years.
From soil-powered sensors to smart face masks, Hester’s research at Northwestern focuses on a more sustainable future for computing, inspired by his Native Hawaiian (Kanaka maoli) heritage. To that end, he focuses on the development of battery-free smart devices and systems for intermittent computing that support a range of applications, including health care, conservation, and infrastructure monitoring.
Jan. 27: Mark Guzdial, professor of computer science & engineering at the University of Michigan
Mark Guzdial will give a lecture on Jan. 27 on “Changing Computing To Make It ‘For All.’” Returning to the original concept that computer science should be taught to everyone just like math, reading and the natural sciences, Guzdial will examine how we need to change our approach to teaching computing to ensure it isn’t just a privileged class that understands it. He will review the history of computer science and its early purpose, the barriers to reaching universal computational literacy, and what new kinds of languages and the tools will be needed to extend this knowledge to everyone.
With a focus on computer education research, learning sciences, education public policy and task-specific programming languages, Guzdial studies how people come to understand computing and how to make that process more effective. He co-founded the Association for Computing Machinery’s International Computing Education Research Conference and helped to lead the National Science Foundation-fundedExpanding Computing Education Pathways Alliance to improve computing education in the United States.
Feb. 17: Shafi Goldwasser, director of the Simons Institute for the Theory of Computing and C. Lester Hogan Professor in Electrical Engineering and Computer Sciences at the University of California, Berkeley
Shafi Goldwasser’s research interests span cryptography, computational number theory, complexity theory, fault tolerant distributed computing, probabilistic proof systems and approximation algorithms. She is the co-leader of the Cryptography and Information Security (CIS) Group and a member of the Complexity Theory Group within the Theory of Computation Group and the Laboratory for Computer Science. She received the ACM Turing Award — computing’s highest honor, otherwise known as the “Nobel Prize of computing” — in 2012, and the Gödel Prize in 1993 for “The Knowledge of Interactive Proof Systems” and again in 2001 “Interactive Proofs and the Hardness of Approximating Cliques.”
Allen School professor Jennifer Mankoff received the 2021 Impact Award from the Association for Computing Machinery’s Special Interest Group on Accessible Computing (SIGACCESS) for her work on “Disability studies as a source of critical inquiry for the field of assistive technology” at the 23rd International Conference on Computers and Accessibility (ASSETS). The paper, which was published in 2010, was the first to describe approaches for bridging the gap between the fields of assistive technology research and critical disability studies. Since then, disability studies have received growing attention at ASSETS as a critical component of research aimed at improving the experiences of people with disabilities and the paper has become an important reading in accessibility courses.
Mankoff, who holds the Richard E. Ladner Professorship in the Allen School and co-leads the Center for Research and Education on Accessible Technology and Experiences (CREATE), co-authored the paper while she was a faculty member at Carnegie Mellon University. Gillian R. Hayes, provost, dean and professor at the University of California, Irvine and Devva Kasnitz, City of New York adjunct professor and emeritus director of the Society for Disability Studies, co-authored the paper.
Studying the individual, cultural, societal and theoretical foundations of the design of disability-related technology, Mankoff and her collaborators looked at two of their own research studies with this new lens. In the first, they considered autism and technology. Initially they focused on designing assistive technology to help care providers, such as helping with early diagnosis. Using the disability studies literature, the team transitioned their focus on designing technology that empowers individual students in the classroom. In their second case study, the researchers looked at computer accessibility. Oftentimes computer simulations are created to give the designer an idea of how their technology might be used by people with disabilities. However, these simulations may not be accurate and still lack the thoughts and feelings of the user with disabilities. The researchers offer alternatives to simulation: involve a small number of people with disabilities much more deeply in the design process or gather data that can be used to test hypotheses rather than create a simulation. Ultimately, the research team recommends using technology “to support empowerment and understanding” of people with disabilities.
“Disability studies theory has changed both my research and my approach to living and working as a disabled person, academic, parent and caregiver,” said Mankoff. “Its lens has helped guide my advocacy and identify moments worthy of constructive change. I am incredibly lucky to have had the chance to work with, and learn from, my collaborators on this paper.”
A follow up paper, “Living Disability Theory: Reflections on Access, Research, and Design” won a Best Student Paper Award at ASSETS 2020, 10 years later. It explores the lived experience of four academics with disabilities, including Mankoff and Kasnitz, and was led by graduate student Megan Hofmann and post doctorate Cynthia Bennett, both at Carnegie Mellon University. The paper focuses on moments when disability was misunderstood and derives three related themes: ableism in research, oversimplification of disability, and human relationships around disability. From these themes, the authors suggest paths toward even more strongly integrating disability studies perspectives and disabled people into accessibility research.
Since the paper’s initial publication, Mankoff joined the Allen School faculty, earned election to the SIGCHI Academy by the ACM Special Interest Group on Computer-Human Interaction and won an AccessComputing Capacity Building Award. She previously was named a Sloan Research Fellow and has earned several faculty fellowships and Best Paper Awards for her work on accessible technology.
In honor of today’s National First-Generation College Celebration, the Allen School continues our annual tradition of spotlighting some of our own first-gen community members and what the opportunity to pursue a bachelor’s degree means to them. As the first in their families to navigate the complicated college application process and the array of internship, study abroad and extracurricular activities, these students are using perseverance, resilience and drive to figure it all out on their own or find the resources to help them. Here’s a glimpse of what they’ve experienced and learned along the way.
David Cueva Cortez, undergraduate student
David Cueva Cortez, of Toppenish, Washington, is a senior studying computer science and dance and serves as vice president of GEN1, a group for first-gen students in the Allen School. Both of his parents emigrated from Mexico, and he grew up in a family of seasonal and migrant agricultural workers who picked fruit in various orchards around eastern Washington, from the Tri-Cities to Wenatchee and everywhere in between. Despite his family traveling each week to a different town to work for another employer, his parents still found time to support his desire to continue his academic studies at the University of Washington.
Allen School: What made you decide to pursue a college degree, and how did you navigate the system?
David Cueva Cortez: My family has made many sacrifices so that I could take advantage of the opportunities not present in Mexico and create a better life for myself and generations to come. Their encouragement to complete my college degree, and my own desire not to work in the fields like them, pushed me to where I am today. For me, getting involved with different kinds of organizations helped me navigate the college system. Being involved in cultural organizations helped me celebrate and remember my roots and major-related organizations helped me meet new people and expand my network.
Allen School: Why did you pick UW, and what interested you in computer science?
DCC: First and foremost I wanted to get out of the Yakima Valley and get a feel for a new town and environment. The desire to be in a city and UW being one of the best engineering schools in a tech-driven city made it a no-brainer for me. I am interested in computer science because of the tools it provides you for problem solving and creating new things. I often draw parallels to construction where you are given all these tools to create something that is going to impact someone. In my case, though, I was really drawn to computers — seeing how code could create all these marvelous things made me more inclined to try it and eventually it just stuck with me.
Allen School: What does being a first-generation student mean to you?
DCC: It means being able to take my struggles and life experiences as a non-traditional student to use as fuel to make a change for not only myself but others. Knowing that I am a trailblazer in uncharted territory alongside my peers who share this first-gen experience is what allows us all to succeed despite the odds.
Allen School: What is your favorite part about being at the Allen School?
DCC: I would have to say all the people I have met. People at the university come from rich and diverse backgrounds, and I always enjoy talking with them and listening to their stories. I’ve made many friends here who I’ve known since freshman year and have created so many wonderful memories in and out of school with them.
Wen Qiu, (B.S. ‘21) B.S./M.S. student
Wen Qiu, a student in the B.S./M.S., immigrated from China with her parents about six years ago. She discovered her passion for computer science after joining the robotics team in high school and taking a computer science course. Her parents were her strongest advocates and supported her choice to study computer science at the Allen School.
Allen School: Why did you pick UW and what interested you in computer science?
Wen Qiu: UW was one of my top options since it is in-state and has a prestigious computer science program. Getting a chance to take a computer science course in high school changed my life, and I was fortunate enough to have great teachers, mentors and professors who have helped me along the way. Before I entered college, I viewed computer science as a medium of creativity, but ever since I became a teaching assistant, I have been more intrigued by computer science education as a field. This is my seventh quarter as a TA and I hope that by improving my teaching skills, I can bring a positive impact on my students and show them computer science is a valid path to pursue. No matter what identity they are and how much prior experience they have coming into the class, they still belong and can thrive in this field.
Allen School: What made you decide to pursue a college degree, and how did you navigate through the college system?
WQ: Since both of my parents went to college in China, I had little insight into how colleges work in the US. The STARS program helped ease that transition and find a community within the huge UW campus. I also learned about more opportunities over time by building good relationships with my professors and chatting with my peers in the major.
Allen School: What does being a first-generation student mean to you?
WQ: For me, being a first-generation student means recognizing and being proud of the efforts I put into my coursework and personal growth. It also means being open to sharing the lessons I’ve learned with others and giving back to the community that supports and encourages me to become who I am today.
Allen School: What is your favorite part about being at the Allen School?
WQ: My favorite part about being at the Allen School is the CS education community. There are a lot of faculty members and TAs who genuinely care about teaching and making computer science more inclusive to everyone, and I am excited to be a part of that effort.
Tim Mandzyuk, (B.S. ‘21) B.S./M.S. student
Tim Mandzyuk is a student in the Allen School’s combined B.S./M.S. program. He is the second youngest of six children, and one of only two born in the U.S. His parents grew up without hot water or a flushable toilet in western Ukraine, then part of the Soviet Union. There, his grandparents spent years in prison for their religious beliefs. When the Soviet Union collapsed, his parents moved to the United States, where he was born soon after. Mandzyuk didn’t have much growing up, but his parents worked hard to provide for their children and pushed them to do the same. With their support, he started his pursuit of a college education his junior and senior years of high school, enrolling in the Running Start program at Everett Community College (EvCC). He graduated high school as valedictorian and went on to earn his Associate’s in general engineering at EvCC, graduating with a 4.0 GPA, before joining the Allen School’s computer engineering program. While he struggled during his first quarter at UW, navigating the challenging courses, living on his own for the first time and feeling like an imposter, he enrolled in the Allen School’s transfer student seminar, made friends and eventually realized he was where he belonged.
Allen School: What made you decide to pursue a college degree, and how did you navigate the system?
Tim Mandzyuk: Learning and connecting with others is fun for me. I grew up playing piano, I ran cross country and track in high school and college and tried to get myself out there in many other ways just to be involved. Naturally, college was the next step in the process. I never had this notion of what a “big name” school was and what it “meant” to get into certain universities. This is a cultural difference between Ukraine and the U.S. In Ukraine, there are no sports teams or prestigious universities, mainly because most people end up working on their farms or doing construction. Because of this, my parents didn’t care if I went to college or not, they just wanted me to be successful. I knew I wanted to go to college, and that meant I needed to figure out how to make that happen on my own. Scholarships, applications, emails, you name it, I was figuring it out. I have learned a lot through trial and error, but most of my knowledge comes from a supportive community. My advisors, teachers, family and friends were always there to support me and help me along the way. People would go out of their way to ensure I was able to figure out x, y and z. Truly, without the people in my life and their guidance, I would not be where I am today. I am so grateful for them all.
Allen School: Why did you pick UW, and what interested you in computer engineering?
TM: Growing up just north of Seattle, I always thought of UW as the ideal university. I knew that one day I wanted to go to UW, but figuring out what I wanted to study was a little harder. During my time at EvCC, I took a circuit class where we used arduinos to make a robot. I thought it was the coolest thing, and from that moment I had my mind set on computer engineering. This degree fit me perfectly because it had a nice balance between hardware and software, where I got the best of both worlds. Now here I am, studying at my dream school with a degree in computer engineering and now working on my CSE degree in the B.S./M.S. program.
Allen School: What does being a first-generation student mean to you?
TM: Being a first-generation college student means breaking boundaries. I am the first person in my family to ever attend graduate school. To me, continuing my education is more than learning, it’s about proving that people in my family can do it too. That we are not limited by what our family has done in the past, but that we too can pave new roads that lead to success.
Allen School: What is your favorite part about being at the Allen School?
TM: My favorite thing about the Allen School is the supportive community. When I first came to UW, I was shocked at how many resources there were for me to get help in so many ways, whether that be in classes, with future planning or anything related to my education and time here. I have also enjoyed the education here. It feels like I have learned more in the past two years in the Allen School than I have my entire life before that.
Shari Maginnis, PMP student
Shari Maginnis is a student in the Allen School’s Professional Master’s Program. After 30 years working as a software engineer she might not be a traditional college student, but the love of learning that her parents instilled in her brought her to the Allen School. While higher education was not a part of her parents’ family culture, they were self-motivated and voracious for knowledge. Her mother sewed clothes, curtains and furniture covers, while her father learned to fix “everything.” In the 1970s she helped him assemble their first PC, and in the 80s the two spent hours transcribing and then debugging programs from coding periodicals. When her family moved to Davis, California, home of University of California Davis, all of her high school classmates were college-bound. Maginnis loved school and ended up winning a musical talent scholarship to pay for her freshman year. When her father died suddenly of a heart attack, Maginnis changed gears by refocusing her studies on computer science and working as a coder to pay for her education.
Allen School: What made you decide to continue your pursuit of education?
Shari Maginnis: I worked in that same job for a small company for many years until we were purchased by a well funded dot-com startup. The company culture changed and my professional world expanded, raising the question, “What’s next for me?” If I could do anything in the world, what I wanted most was to go back to school. I began researching options for advanced education and found a perfect fit with the Allen School PMP program. A challenging, high-profile program, focused on working computer professionals and prominent in the local tech community? It’s like the program was created with me in mind — and after two years, I still feel this way.
Allen School: What does being a first-generation student mean to you?
SM: Looking back on my educational career, there is a real hurdle present for first-generation students. Success in higher education is a learned skill which I acquired through tedious trial and error but also absorbed from my community of friends. I owe so much to the powerful examples set by my friends who were making it work alongside me the whole way. Even now, I’m still figuring it out and I’m still learning from my friends.
Allen School Any advice for first-generation students?
SM: I’ve found that hard problems often have many possible solutions. Don’t stop finding solutions until you’ve found one that is a good fit for you. I learned to seek out the people that were making it look easy and make their strategies mine, too. Ask questions. Almost everyone wants you to be successful, so find ways to make it easy for them to help you. Accomplishments, even small ones, are addictive, and aligning your goals with your passions fills your accomplishments with joy as well as satisfaction.
Allen School: What is your favorite part about being at the Allen School?
SM: There is something about a community dedicated to the pursuit of knowledge — it fills me with joy and wonder just to be on the UW campus. I still text campus snapshots to my mom, and she tells me that my father would be proud. That means everything to me, even now.
EJ Pinera, staff
EJ Pinera, the Allen School’s student leadership development coordinator, was born and raised in south Seattle. His mother grew up in a lower income home in west Seattle, and his father immigrated to the U.S. from the Philippines at the age of 12. The two had Pinera when they were 19 years old and instilled in him the value of working hard and studying in order to gain access to higher education, because they could not afford it. Pinera said that because his parents and grandparents didn’t know how to navigate higher education, he researched a way to stand out in the college application process. Joining programs like UW’s Upward Bound and Summer Search and serving as the associated student body president and class valedictorian earned him a full scholarship to Seattle University, where he graduated cum laude with a bachelor’s in psychology. Pinera’s mother went back to school part-time when he started college, and the two earned their degrees in the same weekend.
Allen School: What does being a first-gen student mean to you?
EJ Pinera: While I am humbled to even say I have a college degree, the journey was really tough. I encountered a lot of peers who came from upper-mid socioeconomic backgrounds, and sometimes it felt tough sitting in the same environments. I found myself sitting in classes with folks who easily pulled out Macbook Pros for class, while I brought out an affordable baseline laptop. I overheard peers who would brag about the international trips their parents sent them on during breaks, while for me it was tough finding funds to set aside for simple things like books. Oftentimes folks think first-gen means you mainly don’t understand the college landscape, but it usually includes a lot of racial and classist undertones that folks from privileged backgrounds don’t have to deal with.
Allen School: Did being a first-gen student influence your career?
EP: Absolutely. Before I started on the Diversity & Access Team, I worked at Rainier Scholars, a nonprofit based in south Seattle. I was an academic counselor for students of color in high school and college, and I absolutely loved supporting young, brilliant and gifted first-gen students on their journey to college.
Allen School: What advice do you have for future first-gen students?
EP: The biggest thing that got me through college, and the thing supporting me beyond, is this: take advantage of resources, even when you feel like you don’t deserve to — imposter syndrome is a very real thing, and insecurity itself can hold you back from a lot. Next time you’re standing outside of career services or afraid to email the study abroad office because you feel worried that you’d be judged for being clueless or undeserving due to financial aid, remind yourself that you are worthy and you absolutely deserve every opportunity that comes your way.
Allen School: What does working at the Allen School mean to you?
EP: Working at the Allen School gives me a great opportunity to support the next generation of leaders who will influence the tech world, which is growing rapidly. I get to continue working in a student-support role now as the student leadership development coordinator, and I am enjoying every moment of supporting our student groups. With regard to first-gen especially, I am very passionate about supporting GEN1 and our students from minority backgrounds.
Kurtis Heimerl, professor
Allen School professor Kurtis Heimerl grew up with an enlisted Air Force staff sergeant father and a mother who worked retail as the family bounced around military bases. When Heimerl was eight, they settled in Alaska. He has two older sisters; the eldest, Michelle, was the driving force behind his college career. She was the first to go to college and made sure Heimerl did so as well. After attending school in Idaho, she settled into a job in Seattle and urged her brother to enroll in UW so that he would have familial support nearby. Since his high school didn’t have great college counselors and his parents didn’t have any college experience, Heimerl said Michelle’s guidance was critical for him to navigate the system — when he signed up too late for classes she told him about FIG, a special interest group for first-year students. Heimerl earned his bachelor’s in computer engineering from UW in 2007 and completed his Ph.D. at the University of California, Berkeley in 2013.
Allen School: Why did you decide to pursue your Ph.D. and then become an educator?
Kurtis Heimerl: I did a bunch of internships and just realized that working on the problems of big software companies wasn’t for me. I was on a team at Amazon doing really amazing service-oriented architecture stuff, developing a tier-0 service discovery solution. This was, in retrospect, some of the coolest stuff a systems person can work on in industry. It just didn’t grab me. My Ph.D. allowed me to pursue problems I thought were interesting, rather than those hoisted upon me by my manager.
Allen School: What does being a first-gen student mean to you?
KH: I think my experience has been that I don’t get a lot of what others implicitly understand. This isn’t necessarily entirely bad; I think there were a lot of situations where if I had more context I’d get that what I was trying to do was extremely unlikely, but it worked out anyhow. There are other elements as well that I still struggle with, though I’m not certain if they are cultural or related to being first-generation. For example, I had a tendency to believe that a lot of the world is outside of my reach as it’s only stuff I saw on TV or whatever. Realizing that these opportunities are for you, you’re there, and you’re there for a reason took me a long time to understand.
Allen School: What do you like most about working at the Allen School?
KH: Freedom, nice office, microwave is near me. More truthfully, the University of Washington, and specifically the Allen School, were so foundational in me finding my path that it’s simply a joy to be able to give back to these institutions. I often tell students that to be truly successful you have to “drink the Kool-Aid” wherever you are. It’s really hard to be at Google or Facebook or whatever and not truly believe in their mission. You go in, you write code, but there’s no passion, and that lack of passion makes it hard to climb up the ladder and succeed. My favorite thing about working at UW is that I deeply believe in the mission and purpose of this institution, and that lets me be successful.
Allen School: What advice do you have for future first-gen students?
KH: I think everyone’s journey is unique so it’s hard to generalize. I think the advice I needed and received during my time here is that all paths truly are available. It may not seem that way; it may seem like you’d be lucky to end up at company X for 30 years or that only a certain group of others with some skills you don’t have can do a thing, but it’s not true. You can go to grad school, start a company or become a director. Or, if you really want, work at company X for 30 years. You get to make that choice. I figured this out by watching people I considered my peers taking paths I hadn’t considered viable for someone like me. I think a smarter person could see that on their own.
We are grateful to all of our first-gen students, faculty and staff for the many ways they enrich our campus and school community!
