Edmund Clarke Pioneered Methods for Detecting Software, Hardware Errors

CMU Professor Earned Turing Award, Computer Science's Highest Honor

Edmund M. Clarke, University Professor Emeritus at Carnegie Mellon University and co-recipient of the 2007 Turing Award – computer science's equivalent of the Nobel Prize – died Dec. 22 of COVID-19, following a long illness. Clarke, together with his Harvard University graduate student, E. Allen Emerson, and, working separately, Joseph Sifakis of the University of Grenoble, developed an automated method for detecting design errors in computer hardware and software. Called model checking, it is widely used and has helped to improve the reliability of complex computer chips, systems and networks. The Association for Computing Machinery (ACM) awarded the Turing to the three scientists for this achievement. "With Ed Clarke's passing, the world lost a giant in computer science and CMU said goodbye to a beloved member of our community," said Farnam Jahanian, president of Carnegie Mellon University. "Ed’s pioneering work in model checking applied formal computational methods to the ultimate challenge: computers checking their own correctness. As systems become ever more complex, we are just beginning to see the wide-reaching and long-term benefits of Ed's insights, which will continue to inspire researchers and practitioners for years to come.” Since the dawn of computing, engineers have checked for logic errors in computer circuitry or software programs by running simulations to test performance and by manually checking each line of computer code. But as the number of components on computer chips grew geometrically and as software and computer systems similarly became more complex, these hit-or-miss "informal verification" methods proved inadequate. Errors often went undetected until after a product was released, when correcting even minor errors is expensive. Model checking, by contrast, is a type of "formal verification" that analyzes the logic underlying a design, much as a mathematician uses a proof to determine that a theorem is correct. Far from hit or miss, model checking considers every possible state of a hardware or software design and determines if it is consistent with the designer's specifications. "Intellectual rigor was a hallmark of Ed Clarke; it earned him computer science's highest honor and through him infused the Computer Science Department for more than 30 years," said Martial Hebert, dean of Carnegie Mellon's School of Computer Science. "He was a shining example for both the faculty and students and he is missed by all of us." Clarke earned his Ph.D. in computer science at Cornell University in 1976. He taught at Duke University and then Harvard before joining CMU's Computer Science Department in 1982, where his research group continued to pioneer formal verification and automatic theorem proving. He is one of the founders of the Computer Aided Verification conference and was the former editor-in-chief of the journal Formal Methods in Systems Design. He became an emeritus professor in 2015. "Ed Clarke was a brilliant researcher but also a kind and caring individual," said Randal E. Bryant, Founders University Professor of Computer Science Emeritus. "I especially admire his ability to mentor Ph.D. students and postdoctoral researchers, many of whom have had major impact throughout the world through their research." In 1995, Clarke was the first recipient of the endowed FORE Systems Professorship and in 2008 was named a University Professor, CMU's highest faculty honor. He is the co-recipient of the 1998 ACM Kanellakis Award, the 1999 Allen Newell Award for Excellence in Research, the 2004 IEEE Harry H. Goode Memorial Award and the Conference on Automated Deduction's 2008 Herbrand Award for Distinguished Contributions to Automated Reasoning. In 2014, the Franklin Institute presented him its Bower Award and Prize for Achievement in Science for his leading role in the conception and development of techniques for verification of computer systems. He is survived by his wife, Martha, the graduate admissions coordinator for the Computer Science Department and School of Computer Science until her 2014 retirement. He also is survived by three sons, James Clarke of Portland, Oregon; Jonathan Clarke of Decatur, Ga., and Dr. Jeffrey Clarke of Durham, N.C., and six grandchildren. Private funeral services are being arranged by Laughlin Memorial Chapel in Mt. Lebanon. The family requests contributions to the Mt. Lebanon United Methodist Church Food Pantry, 3319 West Liberty Ave., Pittsburgh, PA 15216, and to the Edmund and Martha Clarke Endowed Graduate Fellowship in the School of Computer Science.

The Salad Days of AI

Students Create Digital Green Thumbs To Nurture Vegetables in Automated Greenhouses

Nidhi Jain has never had much luck growing plants. "I've tried to work with plants, but they didn't want to work with me," said the senior computer science major from California. "So I've stuck to succulents." Green thumb or no, this fall Jain and her classmates in the School of Computer Science's Autonomous Agents course applied their knowledge of artificial intelligence, including machine learning and computer vision, to grow lettuces and radishes in small, automated greenhouses. Without ever seeing or touching their plants in person, they worked in groups of three to nurture their sprouts, writing programs that made all of the decisions on adjusting light, humidity and soil moisture based on sensor data. Reid Simmons, who teaches the course with Stephanie Rosenthal, said using AI to grow vegetables is a good way for students to put into practice the knowledge of AI-based autonomous agents that they learned in class. Agents have applications in many areas, such as self-driving cars, intelligent factories and smart homes. Automated greenhouses proved a good match to the need for a course exercise. "We wanted something that was physical, that would have to interact with the environment," explained Simmons, a research professor in the Robotics Institute and Computer Science Department (CSD) who directs SCS's undergraduate AI degree program. And they wanted these agents to run for two weeks at a time. "Most of the alternatives were robots and the likelihood that a robot would work for two weeks was very low." Plants grow — and die — slowly, so they don't provide the immediate, dramatic feedback of, say, a robot running into a wall. But students said they nevertheless learned a lot about the pitfalls of autonomous agents during the semester's two growing periods. "Deployment isn't as easy as you think," said Vicky Zeng, a senior artificial intelligence major from Singapore. The autonomous agents receive input from temperature, humidity, soil moisture and light sensors, which they interpret to make adjustments on light, watering and fan operation. Faulty soil moisture sensors, however, plagued all of the teams, resulting in plants going without needed water. "Even if your agent is running fine, it can end up making poor decisions if it's getting bad sensor data," she said. "Some of what they're learning is that relying only on your sensor values can be problematic," said Rosenthal, an assistant teaching professor in CSD. During the second growing period, she noted, moisture sensors showed there was plenty of water in the soil despite most teams never having watered, "but after a week we know the plants probably need water." In that case, the students were allowed to make a one-time adjustment to prevent all their plants from dying. Autonomous agents thus must be designed to cope with errors, Zeng said. More than that, "We can't be waiting to see errors. We have to have methods for predicting them. Sometimes things are out of your control but you try to prevent them from getting into that state." One solution: setting a maximum number of days that the plants can go without watering. Arthur Dzieniszewski, a senior computer science major from New Jersey, comes from a family of gardeners and was immediately intrigued by the autonomous agents course when he heard about it. Many courses in computer science are heavy on theory, so having a course grounded by growing plants made it more interesting and relatable, he said. Overall, the teams had great success in the two growing periods. Though they were graded based on the first two weeks of growth, Simmons and Rosenthal allowed the plants to grow an extra two weeks so they had a chance to develop enough for harvesting. The vegetable-growing exercise proved popular with the students, Rosenthal said, and several chose to take the course, in part, because of it. Dzieniszewski has even created his own automated greenhouse that is functionally equivalent to what the class used. Though he doesn't have any plants growing yet, he can control the greenhouse remotely and use an autonomous agent to run it. After each growing period, the teams would make presentations to the class, summarizing their experiences and lessons learned. Jain said this was one of her favorite parts of the class. Another highlight, she said, was when Simmons harvested some of the vegetables from the first growing period and ate the radishes during class. "This was really exciting because I was finally able to have some success at growing some plants," Jain added.

CyLab Researchers Design Privacy Icon for Use by California Law

This past January, you may have noticed the phrase "Do not sell my personal information" at the bottom of many webpages. If you didn't, it could be because there's no icon next to it — even though the California Consumer Privacy Act (CCPA) suggests using one. After a year without guidance on what that icon should look like, California has proposed an official icon to include with the opt-out text — one developed by researchers from Carnegie Mellon University's CyLab and the University of Michigan's School of Information. "Icon design for privacy applications can be really difficult because information privacy is not easy to visualize," said Lorrie Cranor, the director of CyLab and leader of its Usable Privacy and Security Laboratory. "We tried a variety of designs and performed a series of user tests that give us confidence that our icon will do its job effectively." Creating and approving the icon has been a yearlong process. Late last year, researchers from CyLab and the University of Michigan developed a dozen icons and tested their ability to communicate privacy choices and "do not sell my personal information" themes with hundreds of participants on Amazon Mechanical Turk. They then performed another study with users, evaluating which text accompanying the icon (e.g. "Privacy Options," "Do Not Sell My Personal Information," "Do Not Sell My Info") best communicated their privacy choices. After receiving participant feedback, researchers found that a blue toggle-like icon with the text, "Privacy Options" yielded the most accurate understanding. The team suggested that this icon could be used not only for compliance with the California law, but also to indicate where consumers could find a website's privacy choices in one place. The team also recommended "Do Not Sell My Personal Information" as an option, since that verbiage complied with the CCPA as written. In February, the researchers shared these findings with the California Office of the Attorney General (OAG), and a few days later the OAG released their revised regulations, which included a somewhat-similar red toggle-like icon. To the researchers, the revised icon looked too much like an actual toggle that you might see on an iPhone, and they worried it could cause confusion. The team ran another series of user tests and confirmed their suspicions: users were much more likely to interpret the California icon as an actual toggle. "Small changes can sometimes make a big difference," said Cranor, who is the FORE Systems Professor of Computer Science and Engineering & Public Policy. "You won't really know unless you test with users." On Dec. 10, the California OAG proposed using the team's blue stylized toggle icon in the privacy regulation. Public comments are being accepted through Dec. 28. Users may begin to see the new stylized icon in website footers early next year. The team presented their findings at last month's USENIX Conference on Privacy Engineering Practice and Respect (PEPR).

Justine Sherry Wins 2020 VMWare Systems Research Award

Justine Sherry, an assistant professor in the Computer Science Department (CSD), has won the 2020 VMWare Systems Research Award, in recognition of her seminal contributions to the networking field. VMWare presents the award each year to a faculty member who is within the first five years of their first tenure-track appointment. It includes a $125,000 award to support her research. "Justine has pursued a coherent and impactful research agenda with interesting problem formulations, ambitious systems projects and heavy lifting," said Ole Agesen, a VMWare fellow and a member of the selection committee. "These are also characteristics that the award is meant to celebrate." Sherry is known for early and influential work to identify and drive a research agenda around network middleboxes, which perform in-band packet processing functions ranging from network address translation and security inspection to load balancing and firewalling. As recently as a decade ago, the role of middleboxes was underappreciated, but her research showed that they comprise as much as a third of deployed infrastructure. One of Sherry's key contributions was the idea that middlebox function could be deployed in the cloud rather than in dedicated physical components. Network Functions Virtualization (NFV) has since become a $12 billion market and she continues to make well-rounded contributions to the field. "Justine's work shows an aspect of fearlessness," said Srinivasan Seshan, CSD head. "She does a great job with problems that are risky or could take a long time to pay off, making them work out, and seeing where they will go." Sherry joined CSD in 2016 and is also a member of CyLab. She earned her master's and Ph.D. in computer science at the University of California, Berkeley. She is a recipient of the SIGCOMM doctoral dissertation award, the David J. Sakrison prize and a number of best paper awards.

App Alerts Users to IoT Data Collection Around Them

Billions of internet of things (IoT) devices — such as smart cameras, microphones and location trackers — hide in plain sight, monitoring everything from activities to our facial expressions. Fortunately, there's an app and corresponding digital infrastructure that helps users discover those devices, and learn about the data they collect and the privacy controls they offer. The IoT Assistant app, developed by researchers in Carnegie Mellon University's CyLab, allows users to explore a map of IoT devices around them and learn about their data collection policies and practices. "New laws like the California Consumer Privacy Act (CCPA) and the General Data Protection Regulation call for increased transparency about the types of data being collected about people, how that data is used and what options people are given," said CyLab's Norman Sadeh, a professor in the Institute for Software Research (ISR) and principal investigator on the Personalized Privacy Assistant Project. "Our app and infrastructure pave the way toward compliance, allowing people to take control of their privacy." Once they have downloaded the app from the App Store or Google Play, users can immediately begin exploring a map of IoT devices around them. No account creation is required. By clicking on pins on the map, users can learn about a device's data practices, including the types of data collected, how long it retains the data, who it shares the data with and more. Users can also filter information to focus on certain types of data collection around them (e.g., video capture, audio recording or location tracking), and choose notification options. The app is supported by the IoT Portal, which houses the database of devices and systems that appear in the app. The portal offers a collection of device templates that IoT creators and vendors can use to describe their devices, as well as a wizard to guide them through creating entries for new technologies that may not have a template. "We want to make it easy for people who deploy IoT technologies to publicize the presence of their resources and their data practices," Sadeh said. Volunteers who want to report devices they have spotted can also access the portal. Even if contributors don't know all the details about a device, they can enter partial descriptions of what they are confident they know. "Even simple awareness is important," Sadeh said. The IoT Assistant app gained more than 17,000 users the first week after its soft launch earlier this year. Nearly 200,000 IoT resources in North America, Europe and Australia have been registered in the IoT Portal. The project is supported by a grant from DARPA and funding from the National Science Foundation' Secure and Trustworthy Cyberspace program.

CMU Launches New Privacy Engineering Degree Options

As new privacy regulations require companies to improve how they handle user privacy, more and more working professionals are seeking formal training in privacy engineering. "While we've offered a full-time master's degree program in privacy engineering since 2013, until now we haven't had an option for those seeking privacy engineering training while continuing to work," said CyLab's Lorrie Cranor, co-director of CMU's Privacy Engineering Program and a professor in the Institute for Software Research (ISR) and the Engineering and Public Policy Department. Now, CMU has two flexible options for privacy engineering education and training. The first will allow working professionals to pursue the Master of Science in Information Technology — Privacy Engineering (MSIT-PE) part-time and remotely. Depending on the number of courses taken per semester, the program can be completed in two to four years. "Working professionals no longer need to quit their jobs and move to Pittsburgh to pursue this degree and receive the training they need," said CyLab's Norman Sadeh, co-director of the Privacy Engineering Program and a professor in the ISR. For working professionals who can't commit to a part-time master's program, CMU will also offer a privacy engineering certificate that can be obtained remotely. The program comprises a combination of mini-tutorials, class discussions and hands-on exercises aimed at delivering the fundamentals of privacy engineering. "The idea behind the privacy engineering certificate is that working professionals can learn the key concepts in privacy engineering on the weekend over the course of just two months," Sadeh said. The certificate program is available to individual students as well as cohorts of 15-25 students from a single organization. According to the International Association of Privacy Professionals, privacy engineers in the U.S. earn an average salary of $136,000. Those with a privacy technologist certification earn more than $170,000. "Graduates from our privacy engineering programs will be well equipped to compete in this emerging, fast-growing job market," Cranor said.

SCS Team Wins Most Influential Paper Award at Data Mining Conference

A 2010 paper by a trio of School of Computer Science researchers that described an algorithm for detecting spammers, faulty equipment, credit card fraud and other anomalous behavior won the Most Influential Paper Award at the 2020 Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD). The paper was authored by Christos Faloutsos, the Fredkin Professor of Artificial Intelligence in the Computer Science Department (CSD), and two SCS students who subsequently received doctorates — Leman Akoglu, now Dean's Associate Professor in the Heinz College of Information Sciences; and Mary McGohon, site reliability engineering manager at Google. Both Faloutsos and Akoglu hold courtesy appointments with the Machine Learning Department; Akoglu is also affiliated with CSD. The PAKDD is one of the top data mining conferences and its "most influential" award recognizes a paper published at the conference 10 years earlier that has had significant influence. The trio's winning paper, "OddBall: Spotting Anomalies in Weighted Graphs," discussed a method for analyzing graphs to find nodes that could be considered strange. Such a technique could be used for a wide variety of applications, including detecting network intrusions, political campaign donation irregularities, and accounting inefficiencies or fraud. In social networks, it might detect unusual behaviors, such as adding friends indiscriminately in popularity contests. Their algorithm sought out these anomalous nodes by looking not only at individual nodes, but also at their neighbors. These neighborhoods of nodes would forms spheres, or balls, hence the Oddball name for the algorithm. The algorithm proved to be fast and could function without supervision. It not only detected strangeness, but assigned an "outlierness" score to each node.

Von Ahn Named National Academy of Inventors Fellow

Luis von Ahn, a consulting professor in Carnegie Mellon University's Computer Science Department and co-founder and CEO of the language-learning platform Duolingo, is among 175 academic inventors elected as 2020 fellows of the National Academy of Inventors (NAI). As a CMU graduate student and later faculty member, von Ahn helped develop the modern CAPTCHA, a tool that enables websites to distinguish between bots and real people. He also invented reCAPTCHA, a variation that digitized books as people solved each CAPTCHA puzzle. Later, he and his former student, CMU alumnus Severin Hacker, invented Duolingo, a free service for learning languages that now boasts more than 300 million users worldwide. Last year, Duolingo became Pittsburgh's first "unicorn" — a tech startup valued at more than $1 billion. "Throughout my career, I've been passionate about using invention and technology to make a positive difference in the world — previously with reCAPTCHA and now with Duolingo," von Ahn said. "It is a great honor to be elected an NAI fellow and represent Carnegie Mellon alongside many other talented academic inventors who have created lasting impact." The NAI Fellows Program highlights academic inventors who have demonstrated a spirit of innovation and contributed to inventions that have made a tangible impact on quality of life, economic development and the welfare of society. Election to NAI fellow is the highest professional distinction accorded solely to academic inventors. Von Ahn was an early pioneer of crowdsourcing, initially by devising online games that harnessed game play to accomplish tasks. His ESP Game, for instance, assigned descriptive labels to unlabeled images that had been uploaded to the web. Google purchased the ESP Game and later reCAPTCHA, which also took advantage of crowdsourcing. Duolingo had its own crowdsourcing angle — people learning a language with the app would translate texts for Duolingo customers as they completed practice exercises. Von Ahn and Hacker emphasize that their larger goal is to help millions of people learn English or another language that they need to compete for jobs but cannot afford without the free Duolingo app. Von Ahn, who earned his Ph.D. in computer science at CMU in 2005, has received numerous awards, among them the 2018 Lemelson-MIT Prize for invention, a 2006 MacArthur "Genius" Fellowship and the Association for Computing Machinery's Grace Hopper Award. As a faculty member, he held the Nico A. Habermann development chair in computer science. He received the Presidential Early Career Award for Scientists and Engineers, accepted Sloan Research and Packard fellowships, and was named to MIT Technology Review's prestigious TR35 list of top young innovators. The 2020 class of NAI fellows will be inducted in June at the NAI annual meeting in Tampa, Florida. The class collectively holds more than 4,700 U.S. patents and represents 115 research universities and governmental and nonprofit research institutes worldwide.

Amazon Donates $2 Million to Carnegie Mellon's Computer Science Academy

Gift Will Support Initiative That Offers Free CS Curriculum to Schools Serving Students From Underserved, Underrepresented Communities

Amazon will provide $2 million to support Carnegie Mellon University's Computer Science Academy for the next three years so it can continue to provide a free, online computer science curriculum for middle and high school students. The donation, announced during Computer Science Education Week, comes from Amazon as part of its Amazon Future Engineer program — a childhood-to-career computer science education program aimed at inspiring, educating and training students from underserved and underrepresented communities to study computer science and coding. "Computer science skills are becoming more and more critical to the future success of today’s students," said Shanika Hope, head of Amazon Future Engineer, U.S. "Amazon Future Engineer is excited to support Carnegie Mellon’s Computer Science Academy to expand the innovative and important work they do to ensure more students in need and their hard-working teachers have access to excellent computer science education resources." CMU's School of Computer Science (SCS) launched CMU CS Academy two years ago to fill an instructional gap in grades K-12 and to assist high-need schools that have limited opportunities in computer science instruction. It also provides training for teachers, especially those who may not have previously taught computer science or programming. More than 1,200 schools and 22,000 students in the U.S. and 29 other countries are using the curriculum this fall, and over 50,000 students have participated in classrooms using the curriculum to date. CMU CS Academy aims to serve a million students by 2024. Financial support from Amazon comes at a critical time, said David Kosbie, an associate teaching professor who co-directs the CMU CS Academy with Mark Stehlik, SCS assistant dean for outreach. He noted that the academy is growing exponentially and is poised to complete its high school curriculum by developing a capstone course patterned after one of CMU's introductory computer science courses. "The impact of this Amazon gift is enormous," Kosbie said. "It will fund our existing operations and allow us to continue to develop our curriculum to reach even more students and teachers who otherwise would not have access to this high-quality content and support. "We're excited because our goals mesh so well with those of Amazon Future Engineer, which is focused on students from underserved communities and from groups typically underrepresented in the tech field,” he continued. "We share a similar vision to bridge the equity divide. That's why we're free and that's why we emphasize professional development for educators." Erin Cawley, program manager for CMU CS Academy, said almost 60% of the public high schools using the curriculum are high-needs schools that qualify for federal Title I supplemental funds. The CMU CS Academy curriculum includes four courses that leverage the expertise of CMU's top-ranked computer science school but are geared for use by a range of students, from those in middle school and afterschool programs to high school students. So far, two of the courses are available in Spanish and one in German. The fifth and final course in the curriculum, which is being developed with Amazon's support, will be more intensive and feature even more real-world problem-solving exercises than the previous courses. "It is meant to be the bridge between high school computer science and college computer science," Kosbie said. "When they're done with this course, students will be ready to go into any college program and take a computer science course anywhere in the world." The courses are online but are designed to be used in conjunction with a teacher, rather than for self-study. For that reason, CMU CS Academy provides teacher support and training at a level uncommon for free curricula. Its staff includes four full-time members who are assisted by 20 to 30 CMU undergraduate students majoring in computer science and related fields. Several SCS faculty members have also provided leadership support and helped with curricula creation. To date, CMU CS Academy has been supported by SCS, as well as by gifts from individuals. Amazon Future Engineer is part of Amazon’s $50 million investment in computer science and STEM education. Amazon Future Engineer has donated more than $20 million to organizations that promote computer science and STEM education across the country. Each year, Amazon Future Engineer aims to inspire 550,000 K-12 students across more than 5,000 schools to explore computer science through elementary school curriculum, middle and high school courses, and teacher professional development. The organization also awards four-year, $10,000 scholarships to 100 students; offers guaranteed and paid Amazon internships to gain work experience; awards ten $25,000 Amazon Future Engineer Teacher of the Year Awards; and forms unique partnerships with trusted institutions to bring new and inclusive project-based-learning coding experiences to students.

Forbes Names Guo Among '30 Under 30' Outstanding Young Scientists

Anhong Guo, who recently completed his Ph.D. in the Human-Computer Interaction Institute (HCII) and next month will join the University of Michigan faculty, was named to the 2021 Forbes "30 Under 30" in science for his work on combining human and artificial intelligence to make visual information more accessible. Guo, who was advised by the HCII's Jeff Bigham, led such projects as StateLens, a system that used reverse engineering and a hybrid crowd-computer vision pipeline to make existing dynamic touchscreens more accessible to people with visual disabilities. He was first author of a 2019 paper on AI fairness that examined how widely deployed AI systems may not work properly for people with disabilities and may actively discriminate against them. His work on human- and AI-based camera sensing became part of the CMU spinoff Zensors, which employs computer vision to make smart and reactive spaces. During his studies at the HCII, Guo was a Swartz Innovation Fellow and a Snap Inc. Research Fellow. He will join the University of Michigan as an assistant professor of computer science and engineering. The Forbes 30 Under 30 feature for 2021 highlights a total of 600 entrepreneurs, activists, scientists and entertainers in 20 categories.  

CMU CS Academy Embraces 'Hour of Code'

Novices Can Try Coding During Computer Science Education Week

The Carnegie Mellon Computer Science Academy will encourage students to try coding, at least for an hour, as part of Hour of Code, a grassroots program supported by more than 200,000 educators worldwide that coincides with Computer Science Education Week, which is Dec. 7-13 this year. CMU CS Academy has assembled materials to help students who want to participate in Hour of Code and has developed its own minicourse to help guide novices. Information is available on the organization's website. CMU CS Academy was launched two years ago by the School of Computer Science to fill an instructional gap in grades K-12 and to assist high-need schools that have limited opportunities in computer science instruction. It has developed an online curriculum that is designed to be used in conjunction with a classroom teacher. The curriculum is available free of charge. The academy also provides training for teachers, especially those who may not have previously taught computer science or programming.

Robotics Institute Alumnus Named to Forbes 30 Under 30

Sandeep Konam's Abridge AI Extracts Information From Doctor-Patient Communications

Robotics Institute alumnus Sandeep Konam has been named to Forbes magazine's 2021 "30 Under 30" list in the healthcare field for co-founding Abridge, a Pittsburgh-based startup that helps people stay informed about their health. Its app uses artificial intelligence to extract key insights from recorded health conversations. Advised by Manuela Veloso and Stephanie Rosenthal, Konam earned a master's degree in robotics in 2017. While at CMU, he created EXAID, an app for matching cancer patients with clinical trials. EXAID was a McGinnis Venture Competition finalist and won an award at the inaugural Medical Capital Innovation Competition in Cleveland. After graduation, he worked briefly for UPMC Enterprises before starting Abridge in February 2018 with Dr. Shiv Rao. Their goal, Konam said, is to focus on conversations between patients and their doctors as a way to improve health outcomes. Konam leads Abridge's machine learning efforts, which power Abridge's ability to find key takeaways from health conversations — such as prescription instructions or next steps — and provide trustworthy definitions and applicable coupons. Earlier this year, Abridge announced that it had secured $15 million in funding. It is available to download on the App Store and Play Store. The Forbes 30 Under 30 feature for 2021 highlights a total of 600 entrepreneurs, activists, scientists and entertainers in 20 categories.

Sandholm Wins AAAI Engelmore Award

Delphi Enhances COVIDcast With Change Healthcare Claims Data

Unique Data Helps Researchers Track and Forecast Pandemic Patterns

Change Healthcare and Carnegie Mellon University's Delphi Research Group today announced the launch of Delphi's enhanced COVIDcast real-time COVID-19 indicators. Since April, Delphi has been collecting real-time data on self-reported COVID-19 symptoms and other disease indicators nationwide. This county-level information about the coronavirus pandemic is updated continuously and shared with both the public and health researchers. Now, COVIDcast is taking a further step by adding de-identified COVID-19 claims from Change Healthcare to its unique combination of survey, testing and mobility data. "Tracking and forecasting the spread of a novel disease such as COVID-19 is a challenging task that requires new types and sources of data," said Ryan Tibshirani, an associate professor of statistics who co-directs Delphi with Roni Rosenfeld, head of the Machine Learning Department. "We are always evaluating our data streams and looking at ways of filling gaps in our knowledge. Change Healthcare has stepped up in the biggest way possible to give us crucial information for understanding the current state of the pandemic. We are extremely appreciative of their contributions to our effort." As a preeminent research university, Carnegie Mellon leverages its leadership in machine learning, statistics and data science, as well as its partnership with the U.S. Centers for Disease Control and Prevention, to offer a more complete and real-time picture of COVID-19 than previously possible. Its Delphi Research Group works to advance the theory and practice of epidemic forecasting. Now enhanced with Change Healthcare's de-identified claims, COVIDcast helps researchers better understand the pandemic's impact at the community level by providing comprehensive, geographically detailed, continuously updated indicators of pandemic activity. Understanding the impact of the pandemic on individual communities helps researchers learn patterns and identify trends that will make it possible to improve patient treatment within each community. The data used by COVIDcast is de-identified in accordance with HIPAA privacy regulations. "Delphi group's vision is to make epidemiological forecasting as universally accepted and useful as weather forecasting," said Tim Suther, senior vice president of Data Solutions at Change Healthcare. "The addition of de-identified COVID-19 claims from Change Healthcare allows COVIDcast to present a more complete, multidimensional picture of the pandemic and its impact."

Sandholm Wins AAAI Engelmore Award

Tuomas Sandholm, the Angel Jordan University Professor of Computer Science, has received the 2021 Robert S. Engelmore Memorial Lecture Award from the Association for the Advancement of Artificial Intelligence (AAAI) for his AI research and service to the AI community. Specifically, the award cites Sandholm for his outstanding research contributions in AI, its application to electronic marketplaces, his highly original use of AI in strategic multiplayer games such as poker, and the application of AI to optimize transplant organ exchanges. He will receive the award at the AAAI's Innovative Applications of Artificial Intelligence conference, which will be held virtually Feb. 4–6, and will present an hourlong keynote lecture at the conference. Sandholm's research focuses on the convergence of artificial intelligence, economics and operations research. Since 1989, Sandholm has pioneered large-scale combinatorial markets. He founded research fields such as market clearing algorithms, structured bidding languages, preference elicitation from multiple parties, and automated mechanism design. He founded a company that fielded 800 of the largest combinatorial multi-attribute markets, totaling $60 billion and saving customers more than $6 billion. His current startup, Optimized Markets, brings a new optimization-powered paradigm to advertising campaign creation, scheduling and pricing optimization in TV, digital and cross-media advertising. Along with his students, Sandholm has developed leading algorithms for several general classes of games. Last year, their AI called Pluribus became the first and only AI to beat professional poker players at multiplayer No-Limit Texas Hold'em, the first superhuman AI milestone in any game with more than two players. No-Limit Texas Hold'em is the main benchmark for testing algorithms that solve imperfect-information games. His startup, Strategy Robot, develops and fields computational game theory and opponent exploitation products for defense and intelligence applications. His startup Strategic Machine applies the technologies to business, finance and gaming applications. Since 2010, Sandholm's algorithms have been running the national kidney exchange for the United Network for Organ Sharing, where they autonomously make the kidney exchange transplant plan for 80% of all U.S. transplant centers each week. He also co-invented never-ending altruist-donor-initiated chains, which have become the main modality of kidney exchange worldwide and have led to around 10,000 life-saving transplants. He also invented multi-organ exchanges; the first liver-kidney swap took place in 2019. He has received numerous awards, including the prestigious Marvin Minsky Medal for his work on computer poker, the Computers and Thought Award, the inaugural ACM Autonomous Agents Research Award, the Allen Newell Award for Research Excellence, a Sloan Fellowship, a Carnegie Science Center Award for Excellence, an Edelman Laureateship, and an NSF Career Award. He is a fellow of the ACM, AAAI and INFORMS. The Engelmore Award honors the late Robert Engelmore, a CMU physics alumnus who was an AI research director of the Defense Advanced Research Projects Agency, an editor of AI Magazine and executive director of the Heuristic Programming Project at Stanford University. Previous recipients of the award with Pittsburgh connections include Stephen Smith, research professor in the Robotics Institute; Bruce Buchanan of the University of Pittsburgh; and CMU alumni Edward Feigenbaum of Stanford, Milind Tambe of Harvard University, Craig Knoblock of the University of Southern California, Steven Minton of Fetch Technologies, and Oren Etzioni of the Allen Institute for Artificial Intelligence.

Cranor, Touretzky Named 2020 AAAS Fellows

Lorrie Cranor and David S. Touretzky, both faculty members in the School of Computer Science, are among almost 500 members of the American Association for the Advancement of Science (AAAS) to be named 2020 AAAS fellows. The lifetime distinction recognizes important contributions to STEM disciplines, including pioneering research, leadership within a given field, teaching and mentoring, fostering collaborations, and advancing public understanding of science. Previous notable recipients include Thomas Edison, Margaret Mead and Grace Hopper. Cranor is the director and Bosch Distinguished Professor in Security and Privacy Technologies of CyLab, and is the FORE Systems Professor of Computer Science and of Engineering and Public Policy in the Institute for Software Research and the Department of Engineering and Public Policy. The AAAS cited her "for contributions to usable privacy and security research, policy and education." She founded the Symposium On Usable Privacy and Security (SOUPS) conference and co-edited the seminal book "Security and Usability." She regularly presents privacy research in Washington, D.C., policy forums and served as chief technologist of the Federal Trade Commission in 2016.

New Technique Isolates Brain Cells Associated With Parkinson's Disease

Analysis Shows Changes in How Diseased Cells Sense and Use Oxygen

Carnegie Mellon University researchers have developed a new technique for isolating a type of brain cell associated with Parkinson's disease symptoms, enabling them to study that cell type in detail. The technique, which works only in specially bred mice, costs less than previous methods for isolating these brain cells, said Alyssa Lawler, a Ph.D. student in biological sciences. By using it, she and her colleagues already have detected previously undiscovered changes to how the diseased neurons sense and use oxygen. The researchers describe the technique and their findings in a research paper published online by the journal JNeurosci. "Even a small portion of the brain can have dozens of different cell types," said Andreas Pfenning, an assistant professor in CMU's Computational Biology Department. "Each of these cell types has different roles in the behavior of an animal and also in disease." Separating cells of a certain type from their neighbors is thus a critical first step for researchers who want to study them. In this case, the research team focused on parvalbumin-expressing (PV+) neurons, which have been implicated in Parkinson's disease by the lab of Aryn Gittis, associate professor of biological sciences. Mice with Parkinson's symptoms regain motor control and their ability to run around when these cells are stimulated. Lab mice have been bred with PV+ cells that contain a protein called Cre that activates a fluorescent green protein. That fluorescence makes it possible for cell-sorting machines to isolate the cells from others in a mixture. But cell-sorting machines are extremely expensive, so Lawler developed a cheaper method, called Cre-Specific Nuclear Anchored Independent Labeling, or cSNAIL. The new technique uses a virus commonly employed by researchers to deliver DNA to brain cells. When the virus enters PV+ cells, Cre causes the tag to fluoresce. In the case of cSNAIL, researchers use antibodies to detect the tag and pull the PV+ nuclei away from other cells. "The technique turned out to be really specific, really efficient," Lawler said, noting that it can be adapted to other mouse models that use the Cre protein. In a subsequent analysis of the PV+ neurons, the researchers found that those from sick mice produced more RNA involved in the expression of genes that sense or use oxygen. Further study also showed that the DNA in the nucleus unwound in ways indicating that the oxygen-sensing genes were more active. "Oxygen-sensing pathways have been implicated in other, earlier aspects of Parkinson's disease, but not previously in PV+ cells," Lawler said. These pathways are involved in both protecting and killing cells during neurodegeneration. Pfenning noted that datasets from this study are part of a larger effort to build machine learning models that will help researchers interpret disease mechanisms by looking at how particular DNA sequences respond to different conditions across types of cells. "We're learning how to talk to cells, to speak their language," Lawler said. The National Institutes of Health and the National Science Foundation supported this research.

World's Fastest Open-Source Intrusion Detection Arrives

Intrusion-detection systems are the invisible intelligence agencies in computer networks. They scan every packet of data passed through the network, looking for signs of any one of the tens of thousands of cyberattack styles they recognize. As internet speeds increase, data volumes grow. To keep up, intrusion-detection systems have morphed into giant racks and stacks of servers, driving up energy costs for organizations that rely on them. That's all about to change. Researchers in Carnegie Mellon University's CyLab have developed the fastest-ever open-source intrusion-detection system — one that achieves speeds of 100 gigabits per second using a single server. "What was previously possible with 100-700 processor cores and a whole rack of machines, we can now do with five processor cores in a single server," said CyLab's Justine Sherry, an assistant professor in School of Computer Science's Computer Science Department. The researchers presented their work at the recent USENIX Symposium on Operating Systems Design and Implementation. Key to the researchers' success is using a field-programmable gate array (FPGA), an integrated circuit that users can program with customized code. The researchers programmed the FPGA specifically to detect intrusion, employing algorithms that are significantly faster than previous ones and that could not run on traditional processors. Sherry said that the FPGA processes an average of 95% of data packets on its own when it's placed in a network. The other 5% continue to central processing units when the FPGA becomes overwhelmed, hence the system's five processor cores. "The FPGA does most of the work, but some of it still goes to the processors," Sherry said. The new system produces enormous energy savings. To do the same work as the FPGA, a traditional system comprising hundreds of processing cores would use 38 times more power. "It's like your electricity bill used to be $100, and now it's $3," said Sherry. "We created one pizza box-sized machine to do the work of a whole room of servers." The researchers' open-source code can be downloaded on GitHub.

Zhu, Kaufman Receive Chairs Honoring Longtime HCII Faculty

Haiyi Zhu and Geoff Kaufman, both faculty members in the Human-Computer Interaction Institute (HCII), are the inaugural recipients of junior professorships funded by a gift from HCII Professor Jason Hong and his wife, Shelley Zhang. The professorships are named in honor of two prominent, longtime HCII faculty members: Daniel Siewiorek and Robert Kraut. Zhu is the Daniel P. Siewiorek Assistant Professor of Human-Computer Interaction and Kaufman is the Robert E. Kraut Assistant Professor of Human-Computer Interaction. They are among 13 newly appointed career development chair recipients across the university who will be honored during a virtual celebration at 5 p.m. on Wednesday, Nov. 11. Both also will be virtually feted during a pre-reception at 4 p.m. that will also feature Hong and HCII Director Jodi Forlizzi. Zhu is a social computing researcher who joined the HCII last year. Her broad interests are in the design and social impact of AI technologies in online and offline communities. She is particularly interested in developing AI systems that respect and balance community stakeholders' values. For instance, she has studied how algorithmic tools Wikipedia uses to judge the quality of edits and take corrective action can better align with the values of the Wikipedia community. She earned her undergraduate degree in computer science at Tsinghua University and her master's degree and Ph.D. at the HCII. She served as an assistant professor at the University of Minnesota, Twin Cities, before joining the HCII faculty.

Fragkiadaki Wins Air Force Young Investigator Award

Katerina Fragkiadaki, an assistant professor in the Machine Learning Department, is one of 36 scientists and engineers nationwide — and one of just two from Carnegie Mellon University — to receive funding this year through the Air Force's Young Investigator Research Program (YIP). Giulia Fanti, an assistant professor in the Electrical and Computer Engineering Department who has a courtesy appointment in the Computer Science Department, also won a YIP grant. The YIP aims to foster creative basic research in science and engineering, enhance early career development of outstanding young investigators, and increase opportunities for young investigators to recognize the Air Force mission and related challenges in science and engineering. Recipients receive a three-year grant totaling $450,000. The award will support Fragkiadaki's efforts to develop multimodal perception systems that use lifelong learning to improve their performance with little human guidance. This continual-learning framework would acquire common-sense knowledge about the world through agents embodied in simulated and real-world scenes. The agents would sense, move in and interact with their environments. They also would interact with human analysts who narrate and explain events in natural language. Fragkiadaki earned her bachelor's degree at the National Technical University of Athens, and her Ph.D. at the University of Pennsylvania. Before joining CMU, she was a post-doctoral researcher at the University of California, Berkeley, and at Google Research. Earlier this year, Fragkiadaki received the National Science Foundation's prestigious Faculty Early Career Development (CAREER) Award.