Jack Dongarra of the University Tennessee was awarded the 2019 SIAM/ACM Prize in Computer Science and Engineering on February 28 at the SIAM Conference on Computational Science and Engineering (CSE19) in Spokane, Washington.

Dongarra is a University Distinguished Professor of Computer Science in the Electrical Engineering and Computer Science Department at the University of Tennessee.

The prize honors Dongarra for his key role in the development of software and software standards, software repositories, performance and benchmarking software, and in community efforts to prepare for the challenges of exascale computing, especially in adapting linear algebra infrastructure to emerging architectures.

He is a Fellow of the AAAS, ACM, IEEE, and SIAM, and a member of the National Academy of Engineering. He also received the 2013 ACM/IEEE Ken Kennedy Award.

For more information read the SIAM news release.

The winners of the 2018-2019 Cutler-Bell Prize in High School Computing were announced by ACM and the Computer Science Teachers Association (CSTA). Four high school students were selected from among a pool of graduating high school seniors throughout the US. Eligible students applied for the award by submitting a project/artifact that engages modern technology and computer science. A panel of judges selected the recipients based on the ingenuity, complexity, relevancy and originality of their projects.

The Cutler-Bell Prize promotes the field of computer science and empowers students to pursue computing challenges beyond the traditional classroom environment. In 2015, David Cutler and Gordon Bell established the award. Cutler is a software engineer, designer, and developer of several operating systems at Digital Equipment Corporation. Bell, an electrical engineer, is researcher emeritus at Microsoft Research.

Each Cutler-Bell Prize winner receives a $10,000 cash prize. The prize amount is sent to the financial aid office of the institution the student will be attending next year and is then put toward each student’s tuition or disbursed. This year’s Cutler-Bell Prize recipients will be formally recognized at the Computer Science Teachers Association’s annual conference, July 7-10, 2019 in Phoenix, Arizona.

The winning projects illustrate the diverse applications being developed by the next generation of computer scientists.

Naveen Durvasula, Montgomery Blair High School, Silver Spring, Maryland
Naveen Durvasula developed a principled method to predict, for a given patient-donor pair, the expected quality and waiting time of the transplant they would receive through kidney exchange. To accomplish this, Durvasula developed a realistic simulator to model the kidney-exchange process using data extracted from a private database. By simulating a given patient-donor pair in the pool many times and recording the quality and waiting time for the transplant, there can be an approximation of the probability distribution over these quantities. Realizing this method was not scalable, Durvasula created a prediction model to interpolate the output of the simulator. After testing the method, it was found it provides clinically acceptable estimates and outperforms all standard applications from the Sci-Kit learn pipeline.

Isha Puri, Horace Greeley High School, Chappaqua, New York
Isha Puri’s project focuses on the development of a system to detect the direction and frequency of gaze fixation to test for and diagnose dyslexia. Realizing that the analysis could be performed on eye movement patterns directly, Puri developed six main steps to the process: take a video of a child reading a standard passage using a webcam, separate the video into frames, isolate right and left eyes from the image, develop a highly accurate eye tracker that uses a webcam, extract fixation frequency and duration features to predict dyslexia and test on real patients. Puri’s software automatically extracts the duration and frequency of reader fixations in a webcam stream with a combination of machine learning methods and then builds a data-driven prediction model to predict a high-risk of dyslexia. This implementation provides a highly accurate and freely available eye tracking methodology for diagnosing a variety of medical conditions.

Eshika Saxena, Interlake High School, Bellevue, Washington
Eshika Saxena set out to explore the possibility of designing a portable and affordable microscope attachment for a smartphone that can capture images of blood cells from a peripheral blood smear and develop software that can enhance and analyze these images automatically and screen for disease without manual intervention. Saxena focused on screening for sickle cell disease, which is prominent in resource-constrained regions where an inexpensive screening solution is needed. This resulted in the successful development of the “HemaCam,” a hematological disease screening framework that makes complex disease screening as simple as taking a picture. HemaCam is comprised of a clip-on, 3D printed attachment that turns a smartphone camera into a microscope capable of capturing blood cell images. These images are analyzed by Saxena’s deep learning software to identify abnormalities and diagnose diseases instantly. The software learns from examples and is fully trained to recognize sickle disease with 95.63% accuracy. The framework makes in-home hematological disease screening viable and extends healthcare across borders. Saxena is in discussion with the “Sickle Odisha” organization in the sickle belt in India, to organize large scale field testing for HemaCam to accelerate disease screening.

Varun Shenoy, Cupertino High School, Cupertino, California
Varun Shenoy’s vision is to develop an effective method to diagnose the onset of wound complications during surgical operations using computer science. The design process was split into three phases: conducting a comprehensive literature survey, developing the algorithms and mobile application, and documenting the results of the research. During phase one, Shenoy defined the project statement and worked with Dr. Oliver Aalami to collect mages for the project's dataset. Next, Shenoy developed the computational model and mobile application, concluding that artificial neural networks would be the optimum classifier, and developed an application for a patient to interact with computational models. Shenoy concluded this project by writing a research report documenting the approach and experimental results in a presentation and poster format, showcasing the impact to not only the patient but the doctor, hospital and insurers. This research has the capability to positively impact postsurgical wound care in our society by leveraging the power of computer science.

“We are proud to support an effort which encourages high school computer science students to develop projects that will advance society,” said Cutler and Bell. “ We hope that, whatever careers these students ultimately pursue, they will consider the ways in which technology can have a positive impact on the wider world. Beyond challenging the students to stretch their skills and imaginations, developing their own projects gives students confidence.”

“The Cutler-Bell Prize challenges high school students to not only stretch their imaginations but also to lay out the practical steps for how a computational approach could solve a pressing problem in society or business," said ACM President Cherri M. Pancake. "These are the kinds of skills students will increasingly need in our digital age. In short, the Cutler-Bell Prize encourages students to see the possibilities, as well as the excitement, that computing offers. ACM thanks Gordon Bell and David Cutler for sponsoring the award, as well as the growing number of students and teachers who participate each year.”

“The high caliber submissions we received this year are outstanding examples of the new ideas that are generated thanks to the increase in K–12 students learning computer science,” said Jake Baskin, Executive Director of CSTA. “Our winners have created projects that have applicable real-world solutions, all resulting from the high-quality computer science education they have received.”

ACM has named 56 members ACM Fellows for significant contributions in areas including computer architecture, mobile networks, robotics, and systems security. The accomplishments of the 2018 ACM Fellows underpin the technologies that define the digital age and greatly impact our professional and personal lives. ACM Fellows are composed of an elite group that represents less than 1% of the Association’s global membership.

"In society, when we identify our tech leaders, we often think of men and women in industry who have made technologies pervasive while building major corporations,” said ACM President Cherri M. Pancake. “At the same time, the dedication, collaborative spirit and creativity of the computing professionals who initially conceived and developed these technologies goes unsung. The ACM Fellows program publicly recognizes the people who made key contributions to the technologies we enjoy. Even when their work did not directly result in a specific technology, they have made major theoretical contributions that have advanced the science of computing. We are honored to add a new class of Fellows to ACM’s ranks and we look forward to the guidance and counsel they will provide to our organization."

Underscoring ACM’s global reach, the 2018 Fellows hail from universities, companies and research centers in Finland, Greece, Israel, Sweden, Switzerland, and the US.

The 2018 Fellows have been cited for numerous contributions in areas including accessibility, augmented reality, algorithmic game theory, data mining, storage, software and the World Wide Web.

ACM will formally recognize its 2018 Fellows at the annual Awards Banquet, to be held in San Francisco on June 15, 2019. Additional information about the 2018 ACM Fellows, and the awards event, as well as previous ACM Fellows, is available through the ACM Fellows site.

ACM named two teams to receive the 2018 ACM Gordon Bell Prize. A seven-member team affiliated with the Oak Ridge National Laboratory is recognized for their paper “Attacking the Opioid Epidemic: Determining the Epistatic and Pleiotropic Genetic Architectures for Chronic Pain and Opioid Addiction,” and a 12-member team affiliated with the Lawrence Berkeley National Laboratory is recognized for their paper “Exascale Deep Learning for Climate Analytics.”

The ACM Gordon Bell Prize tracks the progress of parallel computing and rewards innovation in applying high performance computing to challenges in science, engineering, and large- scale data analytics. The award was presented by ACM President Cherri M. Pancake and Valerie Taylor, Chair of the SC18 Awards Committee, during the International Conference for High Performance Computing, Networking, Storage and Analysis (SC18) in Dallas, Texas. Prior to the awards ceremony, all of the Gordon Bell Prize finalists presented their papers during SC18.

Employing Supercomputers to Combat the Opioid Epidemic
Paper Title: “Attacking the Opioid Epidemic: Determining the Epistatic and Pleiotropic Genetic Architectures for Chronic Pain and Opioid Addiction"
Prize Category: Sustained Performance Prize
Team: Oak Ridge National Laboratory
According to the US Centers for Disease Control and Prevention (CDC), 115 people die every day in the US from opioid overdoes. Additionally, the CDC found that there was a 30% increase in opioid overdoes in the period between July 2016 and September 2017 in 52 areas and 45 states. The aim of the Oak Ridge National Laboratory (ORNL) team is to use supercomputing to provide a tool in combating the opioid epidemic by understanding the underlying genetic architecture of how individuals develop chronic pain and respond to opioids. ORNL team members also believe that their project will help with the identification of new therapeutic approaches for opioid misuse. Genome-wide association studies (GWASs) have led to important discoveries in varied types of diseases. For a genome dataset, the ORNL team had access to the Million Veterans Program (MVP), a joint initiative of the US Department of Energy and the US Veterans Administration (VA). The MVP dataset includes 750,000 human genome types, associated with more than a billion medical records over a 20-year period.

The ORNL team developed a new “CoMet” algorithm that allows supercomputers to process vast amounts of genetic data and identify genes that may be more susceptible to pain and opioid addiction—as well as promising treatments. By running the ORNL team’s algorithm, supercomputers were able to successfully process genetic data at a magnitude that is four to five times greater than the latest state-of-the-art approaches. In addition to processing information about the genetics of pain and opioid addiction, CoMet is currently being used in projects ranging from bioenergy to clinical genomics.

The ORNL team includes Daniel Jacobson, Wayne Joubert, Deborah Weighill, and David Kainer (all of Oak Ridge National Laboratory); Sharlee Climer (University of Missouri-St. Louis); Amy Justice (Yale University/Department of Veterans Affairs); and Kjiersten Fagnan (US Department of Energy Joint Genome Institute).

Employing Deep Learning Methods to Understand Weather Patterns
Paper Title: “Exascale Deep Learning for Climate Analytics"
Prize Category: Scalability and Time to Solution
Team: Lawrence Berkeley National Laboratory
Climate change poses a major challenge to humanity in the 21st century. Increasingly, state and local governments are interested in the question of how extreme weather events will change (or affect) their local communities. In order to address these important questions, climate scientists routinely configure and run high-fidelity simulations under a range of different climate change scenarios. Recently, it has been shown that deep learning methods, wherein artificial neural networks vaguely inspired by the human brain learn from large amounts of data, can be applied to better understand extreme weather conditions. Using high-performance computers, the Lawrence Berkeley National Laboratory (LBNL) team trained a deep neural network to identify extreme weather patterns from high-resolution climate simulations. They demonstrated that accurate datasets can be computed for weather patterns such as tropical cyclones and atmospheric rivers.

To train the neural network, the LBNL team paper proposed an innovative blend of hardware and software solutions. These included a novel architecture as well as a number of system-level innovations to enable the largest graphics processing units (GPU)-based HPC systems in the world to process vast amounts of weather-related data. Their application represents the largest successful high performance computer scaling of a deep learning application to date.

Winning team members from the LBNL include Mr Prabhat, Thorsten Kurth, Mayur Mudigonda, Jack Deslippe, Ankur Mahesh (all from Lawrence Berkeley National Laboratory); Sean Treichler, Joshua Romero, Nathan Luehr, Everett Phillips, Massimiliano Fatica, Michael Houston (all of NVIDIA); and Michael Matheson (Oak Ridge Leadership Computing Facility).

Innovations from advanced scientific computing have a far-reaching impact in many areas of science and society—from understanding the evolution of the universe and other challenges in astronomy, to complex geological phenomena, to nuclear energy research, to economic forecasting, to developing new pharmaceuticals. The annual SC conference brings together scientists, engineers and researchers from around the world for an outstanding week of technical papers, timely research posters, and tutorials.

ACM named 49 Distinguished Members for outstanding contributions to the field. The 2018 ACM Distinguished Members are exemplars for their peers, and represent ACM’s worldwide geographic reach, as well as the exciting range of subdisciplines that constitute today’s technology landscape.

"By honoring these individuals, we highlight the professional achievements behind the technologies that have transformed both our daily lives and society in general,” explains ACM President Cherri M. Pancake. “Each Distinguished Member has also demonstrated a commitment to being part of the professional community through his or her longstanding membership in ACM. These computing leaders really epitomize ACM’s mission of ‘advancing computing as a science and a profession.’"

The 2018 ACM Distinguished Members work at leading universities, corporations and research institutions around the world. They represent countries including Australia, Canada, Chile, China, France, Germany, Japan, New Zealand, Singapore, Sweden, the United States and the United Kingdom. These innovators have made contributions in a wide range of technical areas including algorithms, artificial intelligence, computer architecture, computer science education, cybersecurity, graphics, human-computer interaction, and networking.

The Association for Computing Machinery (ACM) and IEEE Computer Society IEEE-CS) named Sarita Adve of the University of Illinois at Urbana-Champaign as the recipient of the 2018 ACM-IEEE CS Ken Kennedy Award. Adve was cited for her research contributions and leadership in the development of memory consistency models for C++ and Java; for service to numerous computer science organizations; and for exceptional mentoring. The award will be presented at SC 18: The International Conference for High Performance Computing, Networking, Storage and Analysis, November 11-16, in Dallas, Texas

Adve co-developed the memory models for the C++ and Java programming languages (with Hans Boehm, Bill Pugh, and others) based on her early work on data-race-free (DRF) models (with Mark Hill).  The memory model specifies what value a read of a memory address will return, and lies at the heart of the correctness and performance of threaded programs, languages, compilers, and hardware. By impacting the models of the most widely-used programming languages, Adve’s work has influenced the worldwide software community and hardware design.

More recently, with her students, Adve questioned the conventional wisdom of memory models for heterogeneous systems and showed that DRF is a superior model, even for such systems. Her group’s recent work on DRFrlx provides semantics for a large class of relaxed atomics within the DRF framework, a longstanding open problem in the specification of modern memory models.

Adve’s broader research interests are at the hardware/software interface and span the system stack from hardware to applications, with current focus on scalable system specialization and resiliency. She is also known for her innovations in cache coherence, hardware reliability, and power management.

Adve is also recognized for her service to the computing community. As current chair of the ACM Special Interest Group on Computer Architecture (SIGARCH), she instituted many changes inspiring new energy in the functioning of the executive committee, leading to new effective programs in communications, research visioning, and mentoring. With colleagues, she made diversity and inclusion a key focus and led the creation of CARES, a committee to provide support to those who experienced harassment at SIGARCH- and SIGMICRO-sponsored events. Other communities have begun to emulate these activities. Adve also serves on the DARPA ISAT study group and previously served on the board of the Computing Research Association and the NSF CISE advisory committee.

Sarita Adve is the Richard T. Cheng Professor in the Department of Computer Science at University of Illinois at Urbana-Champaign. Her honors include being named a Woman of Vision in innovation by the Anita Borg Institute for Women in Technology in 2012, an IEEE Fellow in 2012, and an ACM Fellow in 2010. She also received the SIGARCH Maurice Wilkes Award in 2008. For three of the last five years, the University of Illinois has selected her students' PhD theses as one of two nominations for the ACM Doctoral Dissertation Award.

ACM and the IEEE Computer Society co-sponsor the Kennedy Award, which was established in 2009 to recognize substantial contributions to programmability and productivity in computing and significant community service or mentoring contributions. It was named for the late Ken Kennedy, founder of Rice University’s computer science program and a world expert on high performance computing. The Kennedy Award carries a $5,000 honorarium endowed by the SC Conference Steering Committee.

Linda Gesenhues (Federal University of Rio de Janeiro) and Markus Höhnerbach (RWTH Aachen University) are the recipients of the 2018 ACM-IEEE CS George Michael Memorial HPC Fellowships. Gesenhues is being recognized for her work on finite element simulation of turbidity currents with an emphasis on non-Newtonian fluids. Höhnerbach is being recognized for his work on portable optimizations of complex molecular dynamics codes. The Fellowships are jointly presented by ACM and the IEEE Computer Society.

Gesenhues’ work on turbidity currents may be a useful tool for scientists studying underwater volcanoes, earthquakes or other geological phenomena occurring on the sea floor. Fluids, including water, become turbid when the concentration of particles, such as sediment, rises to a particular threshold. Because of their density, turbid fluids move differently than non-turbid fluids—frequently cascading downward as they are impacted by gravity. The presence of turbid currents can indicate that mud and sand have been loosened from collapsing slopes, earthquakes, or other phenomena. For these reasons, scientists regularly place turbidity sensors on the sea floor to monitor geologic activity.

A challenge of understanding turbidity currents is cataloging the range of possible movements a fluid may make based on the variables in its surrounding environment. For this reason, employing supercomputers, which can process trillions of possible permutations, is an effective approach. The objective of Gesenhues’ PhD project is to obtain a model for numerical simulation of turbidity currents that can predict the characteristics of such flows using non-Newtonian fluid behavior. Non-Newtonian fluids have a higher resistance to deformation than Newtonian fluids; for example, shampoo (a non-Newtonian fluid) loses its shape more slowly than water (a Newtonian fluid).

Thus far, Gesenhues has developed a “solver” (a numerical model) for a 2D simulation of turbidity currents that has been implemented, established and verified. Recently, she augmented her 2D solver to a 3D model. Here, first tests on small 3D benchmark applications were made, including a column collapse.

Markus Höhnerbach’s research focuses on creating simulations for many-body potentials in molecular dynamics (MD) simulations. MD simulations are an indispensable research tool in computational chemistry, biology and materials science. In an MD simulation, individual atoms are moved time-step by time-step according to the forces derived from so-called potential, which is the mathematical law that governs the interactions between atoms. The general idea of Höhnerbach’s PhD project is to develop methods and tools to make the implementation of MD simulations simple and correct by design while generating fast code for a multiple of platforms. For example, in his paper, “The Vectorization of the Tersoff Multi-Body Potential: An Exercise in Performance Portability,” he demonstrated the performance of a type of MD simulations in a wide variety of platforms and processors.

Recently, Höhnerbach has been working with MD simulations for the adaptive intermolecular reactive bond order (AIREBO) potential, which is frequently used to study carbon nanotubes. Many believe carbon nanotubes hold great potential for the future of computer architecture. Höhnerbach wrote a code for the AIREBO potential that has achieved 3x to 4x speedups when performing realistic large-scale runs on current supercomputers.

The ACM-IEEE CS George Michael Memorial HPC Fellowship is endowed in memory of George Michael, one of the founding fathers of the SC Conference series. The fellowship honors exceptional PhD students throughout the world whose research focus is on high performance computing applications, networking, storage or large-scale data analytics using the most powerful computers that are currently available. The Fellowship includes a $5,000 honorarium and travel expenses to attend SC18 in Dallas, Texas, November 11-16, 2018, where the Fellowships will be formally presented.

ACM and IEEE Computer Society named Susan Eggers, a professor at the University of Washington’s Paul G. Allen School of Computer Science & Engineering, the recipient of the 2018 Eckert-Mauchly Award. Eggers was cited for outstanding contributions to simultaneous multithreaded processor architectures and multiprocessor sharing and coherency. The Eckert-Mauchly Award is known as the computer architecture community’s most prestigious award.

Widely recognized as one of the leading computer architects in the field, Eggers will be the first woman to receive the Eckert-Mauchly Award in its 39-year history.  She is also atypical among engineers in that she received a BA degree in Economics in 1965 and worked in related fields for 18 years before deciding to switch careers and pursue research in computer engineering. In 1983 she joined the graduate program in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley and began working toward a PhD.  She completed her PhD in 1989, starting her faculty career as assistant professor at the University of Washington at the age of 47.

Eggers’s early work focused on maintaining accurate and efficient cache coherency in shared-memory processors. In computing terminology, a cache refers to a hardware or software component that is used to store frequently-used instructions or data. While cache memory can be retrieved quickly and doesn’t take up much space, problems can arise that can significantly impair data accuracy in shared-memory multiprocessors. For example, in multiprocessor computers, the same data may reside in separate, processor-specific caches. To maintain the uniformity of the data across all processors, however, once one set of data is changed, all copies of the data in other caches throughout the computer system must also change in a timely fashion—otherwise data could potentially be lost or overwritten. This management of data is called cache coherency. Beginning in the late 1980s, Eggers made significant contributions to cache coherency protocols as well as other memory-related challenges in multiprocessor computers. She performed the first data-driven study of data sharing in shared-memory multiprocessors which greatly enhanced the field’s understanding of both hardware and software coherency techniques.

Eggers is best known for her foundational work in developing and helping to commercialize simultaneous multithreaded (SMT) processors, one of the most important advancements in computer architecture in the past 30 years. In the mid-1990s, Moore’s Law was in full swing and, while computer engineers were finding ways to fit up to 1 billion transistors on a computer chip, the increase in logic and memory alone did not result in significant performance gains. Eggers was among those who argued that increasing parallelism, or a computer’s ability to perform many calculations or processes concurrently, was the best way to realize performance gains.

From 1995 through 2003, she and her colleagues at the University of Washington developed and validated the idea of SMT as a way to increase central processing unit (CPU) performance. SMT is a technique that permits multiple independent sequences of programmed instructions (threads) to better utilize a computer’s resources by converting their thread parallelism to a simpler instruction-level parallelism. Eggers and her colleagues at the University of Washington presented several landmark papers at the International Symposium of Computer Architecture (ISCA) and other leading gatherings that demonstrated the underlying concepts, performance benefits and implementation simplicity of SMT.

Today, SMT architecture as developed by Eggers and her colleagues remains an essential component in the processors of commercial manufacturers, including Intel and IBM. Earlier in her career, she initiated technology transfer of SMT to product teams at IBM, Fujitsu, MemoryLogix and Sun Microsystems.

Eggers will be formally recognized with the award at the ACM/IEEE International Symposium on Computer Architecture (ISCA) to be held June 2-6 in Los Angeles.

ACM and IEEE Computer Society co-sponsor the Eckert-Mauchly Award, which was initiated in 1979. It recognizes contributions to computer and digital systems architecture and comes with a $5,000 prize. The award was named for John Presper Eckert and John William Mauchly, who collaborated on the design and construction of the Electronic Numerical Integrator and Computer (ENIAC), the pioneering large-scale electronic computing machine, which was completed in 1947.

ACM President Vicki L. Hanson honored three individuals with ACM Presidential Awards. They were recognized for their time and talents in service to ACM.

“We are very proud of the work the Association for Computing Machinery does in so many areas,” said Hanson. “The ACM Presidential Award is a way to honor those who have gone above and beyond to create a dynamic professional environment in which we all have been able to grow in our careers. This year’s Presidential Award recipients, Don Gotterbarn, Andrew McGettrick and Fabrizio Gagliardi, have served ACM for decades and their contributions have been highly consequential.”

The 2018 Presidential Award Recipients include:

Donald Gotterbarn, recognized for 25 years of outstanding service as chief architect of ACM’s Code of Professional Ethics, a living document adopted by the computing community worldwide as the blueprint for professional conduct in the field. Gotterbarn has helped to define what it means, ethically, to be a computing professional. He was a forerunner in recognizing the critical importance of professional ethics and has worked tirelessly—as both an educator and a practitioner—to advance this message to a global audience by developing a computer ethics curriculum, leading workshops, and serving as Chair of ACM’s Committee on Professional Ethics. Throughout the creation of the original code, and now the Code 2018 revision that will be released this summer, Gotterbarn has insisted on engaging the computing community, seeking guidance and feedback in the code’s design and direction, and always appreciating that the cause—and the code—is only as strong as its supporters.

Gotterbarn is a Professor Emeritus at East Tennessee State University and a founder of the Software Engineering Ethics Research Institute. He received a Master’s of Divinity from the Colgate Rochester Divinity School, as well as an MA and PhD in Philosophy from the University of Rochester. His honors include receiving the ACM Special Interest Group for Computers and Society (SIGCAS) Making a Difference Award and the International Society for Ethics and Information Technology (INSEIT) Weizenbaum Award.

Andrew McGettrick, honored for his unwavering commitment to computer science education—particularly in terms of its quality, breadth, and access—for generations of students worldwide. McGettrick served as chair of ACM’s Education Board and Education Council for over 15 years, leaving an indelible imprint as a passionate advocate for equipping computer science students with the knowledge, skills, and tools to succeed in the field. During his tenure, he steered the development of key curricula in computer science and software engineering. In recent years, he has played an instrumental role in championing European educational efforts and professional societies, through his work with ACM’s Europe Council and Informatics Europe. McGettrick was one of the leading forces behind the Informatics for All initiative, an acclaimed report that explores strategies for Informatics education in Europe at all levels.

McGettrick is a Professor Emeritus at the University of Strathclyde, Glasgow (UK). He obtained a degree in Pure Mathematics at the University of Glasgow. He later won a scholarship to Peterhouse in Cambridge and obtained a PhD in Pure Mathematics (Number Theory). Afterwards, he returned to Cambridge where he obtained the Diploma in Computer Science (with distinction). Throughout his professional career he has been at the University of Strathclyde in Glasgow, although he has spent periods of sabbatical at Bell Labs in New Jersey and the Australian National University in Canberra.

Fabrizio Gagliardi, in recognition of his selfless dedication to ACM, ensuring the organization’s activities, services, and influence extend throughout the European continent. He is honored for his tireless efforts as the spirit behind ACM’s public policy arm in Europe—EUACM—having served as its Chair since 2013. Gagliardi is a practical visionary, who realized that if ACM is to inform technology policy in Europe it must have a formidable and local presence. The work of EUACM under Gagliardi’s leadership has made a lasting impression in short order, forging dialogues about computing with members of the European Commission as well as spearheading public policy statements on cybersecurity, artificial intelligence (AI), and CS education. He was a guiding force behind two recent panels featuring ACM and EU Commission representatives.

Gagliardi is Distinguished Research Director at Polytechnic University of Barcelona (Spain), Senior Strategy Advisor at the Barcelona Supercomputing Center, and Chair of EUACM, ACM’s European policy committee. He earned his PhD in Computer Science from the University of Pisa. Earlier in his career, he was Europe, Middle East and Africa Director for External Research at Microsoft Research Corporation. He joined Microsoft in November 2005 after a long career at CERN, the world’s leading laboratory for particle physics in Geneva, Switzerland. Gagliardi is author and co-author of several publications and articles on real-time and distributed computing systems.

Aviad Rubinstein is the recipient of the Association for Computing Machinery (ACM) 2017 Doctoral Dissertation Award for his dissertation “Hardness of Approximation Between P and NP.” In his thesis, Rubinstein established the intractability of the approximate Nash equilibrium problem and several other important problems between P and NP-completeness—an enduring problem in theoretical computer science.

For several decades, researchers in areas including economics and game theory have developed mathematical equilibria models to predict how people in a game or economic environment might act given certain conditions.

When applying computational approaches to equilibria models, important questions arise, including how long it would take a computer to calculate an equilibrium. In theoretical computer science, a problem that can be solved in theory (given finite resources, such as time) but for which, in practice, any solution takes too many resources (that is, too much time) to be useful is known as an intractable problem. In 2008, Daskalakis, Goldberg and Papadimitriou demonstrated the intractability of the Nash equilibrium, an often-examined scenario in game theory and economics where no player in the game would take a different action as long as every other player in the game remains the same. But a very large question remained in theoretical computer science as to whether an approximate Nash equilibrium (a variation of the Nash equilibrium that allows the possibility that a player may have a small incentive to do something different) is also intractable.

Rubinstein’s dissertation introduced brilliant new ideas and novel mathematical techniques to demonstrate that the approximate Nash equilibrium is also intractable. Beyond solving this important question, Rubinstein’s thesis also insightfully addressed other problems around P and NP completeness, the most important question in theoretical computer science. Rubinstein is a postdoctoral researcher at Harvard University and will be starting an appointment as an Assistant Professor at Stanford University in the fall of 2018. He received a PhD in Computer Science from the University of California, Berkeley, an MSc in Computer Science from Tel Aviv University (Israel) and a BSc in Mathematics and Computer Science from Technion (Israel).

Honorable Mentions for the 2017 ACM Doctoral Dissertation Award went to Mohsen Ghaffari, who received his PhD from the Massachusetts Institute of Technology’s Department of Electrical Engineering and Computer Science (MIT EECS) and Stefanie Mueller, who received her PhD from the Hasso Plattner Institute (Germany). 

In Ghaffari’s dissertation, “Improved Distributed Algorithms for Fundamental Graph Problems,” he presents novel distributed algorithms that significantly lower the costs of solving fundamental graph problems in networks, including structuring problems, connectivity problems, and scheduling problems. Ghaffari’s dissertation includes both breakthrough algorithmic contributions and interesting methodology. The first part of the dissertation presents a new maximal independent set (MIS) algorithm, which is a breakthrough because it achieves a better time bound than previous algorithms for this three-decades-old problem. The second part of the dissertation contains a collection of related results about vertex connectivity decompositions. Finally, in the third part of his dissertation, Ghaffari introduces a time-efficient algorithm for concurrent scheduling of multiple distributed algorithms. Ghaffari is an Assistant Professor of Computer Science at ETH Zurich. He received a PhD and SM in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology and received a double major in Computer Science and Electrical Engineering from Sharif University (Iran).

Mueller’s dissertation, “Interacting with Personal Fabrication Devices,” demonstrates how to make personal fabrication machines interactive. Her approach involves two steps: speeding of batch processing and turn taking, and real-time interaction.  Her software systems faBrickator, WirePrint and Platener allow users to fabricate 10 times faster, a process she calls low-fidelity fabrication or low-fab. In her dissertation she also outlines how to add interactivity. Constructable, a tool she developed, allows workers to fabricate by sketching directly on the workpiece, causing a laser cutter to implement these sketches when the user stops drawing. Another of Mueller’s tools, LaserOrigami, extends this work to 3D.  Mueller is an Assistant Professor of Computer Science at MIT EECS and MIT CSAIL. She received a PhD in Computer Science as well as an MSc in IT-Systems Engineering from the Hasso Plattner Institute (Germany). Earlier, she received a BSc in Computer Science and Media from the University of Applied Science Harz (Germany).

Jan Cuny was named recipient of the ACM Distinguished Service Award for the establishment and tireless promotion of projects that have nationally transformed CS education by increasing and diversifying access to high-quality CS education. When she joined the US National Science Foundation (NSF) in 2004, Cuny initiated the Broadening Participation in Computing Program (BPC), which aimed to significantly increase the number of college students earning degrees in computing across the country. The BPC program sought to increase the participation in computing of traditionally underrepresented groups, including women, minorities and persons with disabilities. BPC seeded a number of alliances—large-scale efforts that are continuing to work at the national level to increase diversity in the computing field.

In the K-12 arena, Cuny built on the work of one of those alliances, Into the Loop, that successfully introduced a new high school course, Exploring Computer Science, designed with equity as a core consideration.  Cuny worked with the College Board to develop a new national Advanced Placement (AP) computer science course and exam with similar goals of attracting traditionally underrepresented groups. One challenge the planners faced was that of the 23,000 public high schools in the United States, only 2,000 offered computer science education. Creating new NSF programs, Cuny launched an effort to catalyze a movement to add 10,000 new well-trained CS teachers throughout the country in 10 years. This ambitious professional development effort was dubbed “CS10K.”

While the milestone of 10,000 new CS teachers has not quite been reached yet, Cuny’s vision of a new, more inclusive CS course is a reality. AP Computer Science Principles was launched in the 2016-2017 academic year. More than 2,500 schools offered the course and more than 50,000 students took the exam—the biggest launch in the AP’s history. CS10K became the forerunner to today’s CSforAll movement that is transforming CS education for grades preK-12.

The ACM Distinguished Service Award is presented on the basis of value and degree of services to the computing community. The contribution should not be limited to service to the Association, but should include activities in other computer organizations and should emphasize contributions to the computing community at large.

Judith Gal-Ezer was named recipient of the Karl V. Karlstrom Outstanding Educator Award for her central role in developing a groundbreaking high school computer science curriculum; her outstanding computer science education research; and her extensive service to the education community. In 1995 Gal-Ezer, who is currently a professor emerita at The Open University of Israel, led the development of a bold new CS curriculum for Israeli high school students. Her reimagined approach moved away from conventional pedagogies, which prioritized coding, to emphasizing the underlying ideas of computer science. Gal-Ezer’s framework was such a success at engaging students that many other countries used it as a model as they revised or introduced their own CS curricula.

Gal-Ezer’s seminal works include her 1998 paper “What (Else) Should CS Educators Know,” co-authored with David Harel. In the paper, she advocates that CS educators should extend their knowledge beyond regular CS coursework and be exposed to the foundational ideas of algorithms and systems. The paper inspired a whole generation of CS educators and contributed to a heightened appreciation of the inherent value of studying computing. Gal-Ezer has also been active in developing curricula at the university level. From 1985 onward, she played a prominent role in setting up computer science undergraduate programs, and later a Master’s program, at OUI, where she either personally wrote or supervised much of the CS coursework.

Outside Israel, Gal-Ezer has been an indispensable collaborator for several major organizations that advance CS education. She has been a member of key CS education journal editorial boards, served on the Computer Science Teachers Association’s (CSTA) Advisory Council, and more recently, joined the Committee on European Computing Education (CECE, a group consisting of members from the ACM Europe Council and Informatics Europe) and Google’s education advisory council.

The Karl V. Karlstrom Outstanding Educator Award is presented annually to an outstanding educator who is appointed to a recognized educational baccalaureate institution.  The recipient is recognized for advancing new teaching methodologies; effecting new curriculum development or expansion in Computer Science and Engineering; or making a significant contribution to the educational mission of ACM. Those with 10 years or less teaching experience are given special consideration. A prize of $10,000 is supplied by Pearson Education.

Steve Bourne was named recipient of the Outstanding Contribution to ACM Award for significant contributions to ACM, particularly for reaching out to practitioners through the development of the Practitioners Board and ACM Queue, and for his support of students worldwide through his engagement with, and support of, the ACM International Collegiate Programming Contest (ICPC).

During his tenure as President of ACM (2000-2002), Bourne envisioned and encouraged the expansion of the ACM membership from its historic academic and research base to include practicing professionals. He instituted and fostered projects to interest and support this practitioner demographic, and his involvement in these programs continues to this day. A centerpiece of these efforts was the launch of ACM Queue, a first-of-its kind magazine for practicing software engineers. In enlisting and guiding the magazine’s first editorial board, Bourne envisioned a publication that would not simply chronicle industry news, but rather provide software engineers with insights into future challenges that lie just ahead.

Bourne also broadened ACM’s appeal to professionals by initiating and developing the ACM Practitioners Board. The board meets regularly to ensure that ACM continues to offer products and services that support and enhance the professional and technical development of ACM members. An apt reflection of the fastest-growing areas of computing, the Practitioners Board includes practicing engineers, computer architects, and IT specialists and managers, among many others.

Another of Bourne’s contributions to ACM has been his active participation since 2001 in the ACM-operated International Collegiate Programming Contest (ICPC). Now in its 42nd year, ICPC counts more than 320,000 alumni.

The Outstanding Contribution to ACM Award recognizes outstanding service contributions to the Association. Candidates are selected based on the value and degree of service overall, and may be given to up to three individuals each year.

William Wulf was named recipient of the ACM Policy Award for broad contributions bringing computing into the national agenda, leading computer scientists into public policy where his inspirational leadership promoted key national priorities including diversity and ethics.

A highlight of Wulf’s tenure as Director of the National Science Foundation (NSF) Computer & Information Science & Engineering (CISE) division (1988-1990) was overseeing the merger and conversion of the ARPANet, an early packet-switching network with/to NREN, an early network that supported the research and education communities. This merger, as well as efforts by Wulf and others to work with Congress to craft legislation, led to the publicly accessible internet.

As the Chair of National Research Council (NRC) Computer Science and Telecommunications Board (1992-96), Wulf managed the development of several landmark reports including “Computing the Future: A Broader Agenda for Computer Science and Engineering,” and “Evolving the High Performance Computing and Communications Initiative,” among many others.

While at the National Academy of Engineering (NAE), Wulf became known as the “Education President.” He established NAE’s first Standing Committee on Engineering Education and spearheaded NAE’s technical literacy movement. Two reports: “The Engineer of 2020” and “Educating the Engineer of 2020” were especially well-received and fostered broad consensus among NAE’s membership. Wulf was also recognized for his efforts in championing ethics and greater diversity in the engineering profession during his term at NAE.

The ACM Policy Award was established in 2014 to recognize an individual or small group that had a significant positive impact on the formation or execution of public policy affecting computing or the computing community. This can be for education, service, or leadership in a technology position; for establishing an innovative program in policy education or advice; for building the community or community resources in technology policy; or other notable policy activity. The award is accompanied by a $10,000 prize..

ACM named Amanda Randles recipient of the ACM Grace Murray Hopper Award for developing HARVEY, a massively parallel fluid dynamics simulation capable of modeling the full human arterial system at subcellular resolution and fostering discoveries that will serve as a basis for improving the diagnosis, prevention, and treatment of human diseases. A focus of Randles’s research has been in developing and applying high performance computing to biomedical problems. With HARVEY, she combined her knowledge of applied physics, computational methods and parallel computing to develop a physiologically accurate model of the movement of red blood cells throughout the body. The simulation mapped 500 billion fluid points using a supercomputer with 1.6 million cores (individual processors). HARVEY marked the first time a researcher had been able to effectively model the flow of blood at the cellular level. Randles is presently working with collaborators at the Dana Farber Cancer Institute and Harvard Medical School to extend the use of HARVEY to cancer biology and cardiovascular treatment planning. Randles’s cross-disciplinary approach has helped to bridge the gap between the computer and the clinic—translating computational results into actionable data physicians can use to improve patient outcomes.

The ACM Grace Murray Hopper Award is given to the outstanding young computer professional of the year, selected on the basis of a single recent major technical or service contribution. This award is accompanied by a prize of $35,000. The candidate must have been 35 years of age or less at the time the qualifying contribution was made. Financial support for this award is provided by Microsoft.

Margaret A. Boden was honored for contributions to the philosophy and historiography of cognitive science and artificial intelligence, particularly in the study of human creativity. For four decades, Boden has been one of the world’s premiere thought leaders on the intersection of artificial intelligence, cognitive science and the humanities. Through insightful analyses, she was often the first to reveal surprising connections among disciplines, which she then outlined in a series of highly influential books. In two classic books—Artificial Intelligence and Natural Man (1977) and The Creative Mind (1990)—she introduced the idea of creative cognition, which inspired a generation of researchers and laid the foundation of computational creativity as a new subfield of artificial intelligence.

Boden’s two-volume Mind as Machine: A History of Cognitive Science (2006) is a comprehensive survey of interdisciplinary work at the intersection of cognitive science and computation that highlights work in neuroscience, philosophy, biology, linguistics and computation. The book is considered a valuable reference for young researchers to explore what important work has already been undertaken in their field. Mind as Machine also begins with the provocative question: “When is a program not a program?” It is a fitting introduction to Boden, who has been raising important questions about the challenges and risks of artificial intelligence since the beginning of her career. After more than five decades in the field, Boden continues to be both prolific and relevant. Her most recent book AI, Its Nature and Future (2016) was described by Nature magazine as “a masterclass.”

The ACM - AAAI Allen Newell Award is presented to an individual selected for career contributions that have breadth within computer science, or that bridge computer science and other disciplines. The Newell award is accompanied by a prize of $10,000, provided by ACM and the Association for the Advancement of Artificial Intelligence (AAAI), and by individual contributions.

ACM will present the 2016 Software System Award, Grace Murray Hopper Award, Paris Kanellakis Theory and Practice Award, and Allen Newell Award at its annual Awards Banquet on June 24, 2017 in San Francisco, California.

Scott Shenker was honored for pioneering contributions to fair queueing in packet-switching networks, which had a major impact on modern practice in computer communication. Shenker’s work was fundamental to helping the internet grow from a tool used by a small community of researchers, to a staple of daily life that is used by billions of people. Since the internet was introduced, demand has grown for the ability of computer networks to transmit voice and data simultaneously. Traditionally, this was a challenge, as early networks were not designed to offer integrated services. Shenker was the first to develop the first practical fair queueing algorithm for packet-switching networks, which provided equitable access to transmission bandwidth for different grades of service quality. Many of the commercial routers that make up the internet today use Shenker’s algorithms.

Shenker also developed a mathematical tool for rigorous network research, and introduced ideas for implementing “guaranteed” real-time services such as voice, video streaming and multicasts. Recently, Shenker has been involved in positing how to redesign the internet from the ground up. Software-defined networking (SDN) and software-defined internet architecture (SDIA) are key ideas he developed as part of these inquiries. Researchers consider SDN and SDIA invaluable concepts for mapping out how to most effectively maintain and expand the internet in the coming years.

The ACM Paris Kanellakis Theory and Practice Award honors specific theoretical accomplishments that have had a significant and demonstrable effect on the practice of computing. This award is accompanied by a prize of $10,000 and is endowed by contributions from the Kanellakis family, with additional financial support provided by ACM's Special Interest Groups on Algorithms and Computation Theory (SIGACT), Design Automation (SIGDA), Management of Data (SIGMOD), and Programming Languages (SIGPLAN), the ACM SIG Projects Fund, and individual contributions.

ACM named Fernando Pérez, Brian E. Granger, Min Ragan-Kelley, Paul Ivanov, Thomas Kluyver, Jason Grout, Matthias Bussonnier, Damián Avila, Steven Silvester, Jonathan Frederic, Kyle Kelley, Jessica Hamrick, Carol Willing, Sylvain Corlay and Peter Parente (members of the Project Jupyter Steering Council), recipients of the ACM Software System Award for Project Jupyter, a broad collaboration that develops open source tools for interactive computing, with a language-agnostic design. These tools, which include IPython, the Jupyter Notebook and JupyterHub, have become a de facto standard for data analysis in research, education, journalism and industry. Jupyter has broad impact across domains and use cases. Today more than 2,000,000 Jupyter notebooks are on GitHub, each a distinct instance of a Jupyter application—covering a range of uses from technical documentation to course materials, books and academic publications.

Jupyter has also gained wide industry adoption. Since 2015, Jupyter-based products have been released by several companies including Google (Cloud DataLab), Microsoft (AzureML, HDInsight), Intel (Trusted Analytics Platform), and IBM (IBM Watson Studio). Bloomberg and Anaconda Inc. have partnered with Project Jupyter to develop the next-generation web interface, JupyterLab.

The ACM Software System Award is presented to an institution or individual(s) recognized for developing a software system that has had a lasting influence, reflected in contributions to concepts, in commercial acceptance, or both. The Software System Award carries a prize of $35,000. Financial support for the Software System Award is provided by IBM.

ACM named Andrea Goldsmith of Stanford University the 2018-2019 Athena Lecturer for contributions to the theory and practice of adaptive wireless communications, and for the successful transfer of research to commercial technology. Goldsmith introduced innovative approaches to the design, analysis and fundamental performance limits of wireless systems and networks. Her efforts helped develop technologies used in long-term evolution (LTE) cellular devices as well as the Wi-Fi standards that are used in wireless local area networks. Goldsmith participated in the launch of companies to commercialize her work, which has led to the adoption of her ideas throughout the communications industry.

Initiated in 2006 by the ACM Council on Women in Computing (ACM-W), the Athena Lecturer Award celebrates women researchers who have made fundamental contributions to computer science. The award carries a cash prize of $25,000, with financial support provided by Google.

“The anytime, anywhere computing era in which we now live owes a debt to innovators like Andrea Goldsmith who have helped lay the groundwork for the wireless infrastructure that makes mobile  computing possible,” said ACM President Vicki L. Hanson. “Her work has improved the transmission, reception and overall quality of wireless communications. Importantly, Goldsmith’s career has exemplified the spirit of the ACM Athena Lecturer Award in the numerous ways she has mentored young women throughout her career. She has helped prepare promising young women PhD students and postdocs for faculty positions, and she has worked to develop actionable strategies to improve the climate, recruitment and retention of women in the high tech industry.”

Adaptive MIMO
Beginning in the early 1990s, Goldsmith developed several fundamental capacity results for wireless systems. Understanding the Shannon capacity limits of these systems can lead to benefits including increased data rates and extended range while lessening the impact of ongoing challenges in wireless communications including co-channel interference, poor reception, and outages. Goldsmith was the first to propose and develop the underlying theory for time-varying adaptive modulation, as well as new multiple input/multiple output (MIMO) techniques that have been employed throughout the field to improve network capacity and performance.

She proposed techniques, including design of modulation and coding scheme (MCS) tables and quadrature amplitude modulation (MQAM and code) indexed by signal noise radio (SNR) bands, that are used in a variety of wireless systems including EDGE, Wi-Fi and 3GPP/LTE.

Quantenna
In 2005, Goldsmith founded Quantenna Communications to build a product and company around her research in adaptive MIMO wireless. In 2008, as CTO, she led the development of the world’s first 4x4 adaptive MIMO 802.11n Wi-Fi chipset. Compared with other Wi-Fi products on the market, the Quantenna chipset provided better data rates, coverage and reliability and was especially effective for wireless distribution of multiple HD video streams. Today Quantenna products are used by major carriers including AT&T, DirectTV, Comcast, France Telecom, Swisscom and Telefonica.

Biographical Background
Andrea Goldsmith is the Stephen Harris Professor in the School of Engineering at Stanford University. She co-founded and served as Chief Technical Officer of Plume Wi-Fi and of Quantenna, and she currently serves on the corporate or technical advisory boards of Crown Castle Inc., Interdigital Corp., Sequans, Quantenna and Cohere.

Goldsmith has published 160 journal papers, 320 peer-reviewed conference papers, and three textbooks, one of which has been translated into Chinese, Japanese and Russian. She also holds 29 patents, with three pending. Goldsmith is a member of the National Academy of Engineering and the American Academy of Arts and Sciences, and is a Fellow of the IEEE and of Stanford. She has received several awards for her work, including the IEEE ComSoc Edwin H. Armstrong Achievement Award, as well as the National Academy of Engineering Gilbreth Lecture Award. Goldsmith received her PhD, MS and BS degrees in Electrical Engineering from the University of California, Berkeley.

The Athena Lecturer is invited to present a lecture at an ACM event. Goldsmith’s Athena Lecture will be delivered at an ACM event later this year. The award is named after Athena, the Greek goddess of wisdom. With her knowledge and sense of purpose, Athena epitomizes the strength, determination, and intelligence of the “Athena Lecturers.”

Goldsmith will formally receive the Athena Lecturer Award at ACM’s annual awards banquet on June 23, 2018 in San Francisco.

ACM named Dina Katabi of the Massachusetts Institute of Technology’s Computer Science and Artificial Intelligence Laboratory (MIT CSAIL) the recipient of the 2017 ACM Prize in Computing for creative contributions to wireless systems. Recognized as one of the most innovative researchers in the field of networking, Katabi applies methods from communication theory, signal processing and machine learning to solve problems in wireless networking. Among her contributions, she is cited for co-authoring several highly influential papers on overcoming interference in wireless networks to improve the flow of data traffic.  And in inventing a device that seems to be lifted out of the pages of science fiction, she and her team pioneered the use of wireless signals in applications that can sense humans behind walls, determine their movements and even surmise their emotional states. These trailblazing human-sensing technologies hold out promise for use in several applications of daily life including helping the house-bound elderly, and perhaps determining survivors within buildings during search and rescue operations.

The ACM Prize in Computing recognizes early-to-mid-career contributions that have fundamental impact and broad implications. The award carries a prize of $250,000. Financial support is provided by an endowment from Infosys Ltd.

“Innovations which help facilitate communications across mobile networks certainly address an important need,” explained ACM President Vicki L. Hanson. “One recent report estimated that worldwide mobile data traffic grew 18-fold between 2011 and 2016. Dina Katabi’s work has contributed to a seamless increase in traffic, as well as the ever-increasing volumes of data that are shared over mobile systems. The official citation for the ACM Prize in Computing cites Katabi’s creative contributions because she is known for reimagining longstanding challenges in original ways.”

“Infosys is proud to support the ACM Prize in Computing, which this year honors Dina Katabi for her groundbreaking achievements in mobile systems,” said Salil S. Parekh, CEO of Infosys. “By 2020, experts predict that there will be 11.6 billion mobile-connected devices in the world. Our use of these devices, and the underlying networks that they rely upon, will play an increasingly important role in every aspect of life—from the way we communicate with friends and family, to our jobs, to the health of the world economy. By recognizing Katabi’s contributions, we educate the public about the technologies they use every day but may take for granted. Hopefully, we might also inspire the next generation to work in this exciting and very impactful area of computing science and practice.” 

Wireless Network Coding
Wired networks simply route (or forward) signals from one point to another, and early wireless networks were based on this blueprint. Wireless networks, however, are fundamentally different from wired networks and at times face challenges including inadequate mobile support, dead spots, and low throughput—or the amount of data that can be moved from one point to another in a given time. As wireless technology developed, many proposed a new unifying design paradigm called network coding in which each node in a network would perform some computation. At each node, the transmission could be mixed (encoded), or re-mixed (re-encoded), in order to be unmixed (decoded) at its final destination. Katabi was a leader in presenting ideas to make the theory of network coding practical as a way to improve network performance. The papers in which she introduced concrete methods to make network coding practical received awards at major conferences and remain staples of the reading lists in wireless classes.

Interference Mitigation
Following up on her work in network coding, Katabi and her collaborators have written several research papers on the fundamental problem of interference in wireless networks, which occurs when multiple nodes transmit concurrently. In these papers, she modeled how wireless signals mix in the air as code, and then outlined algorithms that allow the receiver to decode these interference-based codes. Katabi’s methods were not only shown to overcome interference in wireless transmissions, but in some instances can be exploited to increase the amount of data that can move over the network.

Sensing and Wireless Signals
At ACM SIGCOMM 2013, Katabi presented a highly influential paper, “See through Walls with Wi-Fi!” She demonstrated how Wi-Fi-based devices and their variants can be used to detect people behind walls, their movements, and even their emotional states. The device works by transmitting wireless radio signals that traverse a wall and reflect off a person’s body back to the device. While the data that comes back from these reflections is very minimal, Katabi and her team developed a series of algorithms that separate the meaningful signals from the random noise produced by the walls and other reflections. The technology can identify a person’s silhouette and detect gestures as subtle as the rise and fall of a person’s chest from the other side of a house. Her lab has recently advanced the technology to remotely monitor a person’s heart rate and other vital signs, to infer, among other indicators, their emotional states. The work has generated a huge amount of interest and was one of the invited demonstrations at President Obama’s White House Demo Day.

Sparse Fast Fourier Transform
In computing, the Discrete Fourier Transform (DFT) is a mathematical technique that is used for processing streams of data in a range of computational tasks including audio/image processing, biochemistry, astronomy, and even GPS. Traditionally, the Fast Fourier Transform (FFT) was the algorithm that was used to process data for a wide range of computational tasks. Katabi, along with MIT colleague Piotr Indyk and students, developed a new algorithm, the Sparse Fast Fourier Transform (SFFT) that processes data 10 to 100 times faster than the FFT. Among its many other benefits, Katabi’s faster transform means that computers need less power to process the same amount of data.

Background
A native of Damascus, Syria, Dina Katabi is the Andrew and Erna Viterbi Professor of Computer Science and Director of the Center for Wireless Networks and Mobile Computing at the Massachusetts Institute of Technology (MIT). She received a PhD and MS in Computer Science from MIT, and a BS in Electrical Engineering from Damascus University, Syria.

Katabi is the author or co-author of over 100 scholarly publications covering a wide range of topics in networks and data communications. Her papers have been cited more than 20,000 times by researchers. She has been recognized with several honors including a MacArthur Fellowship, the ACM Grace Murray Hopper Award, several ACM SIGCOMM Best Paper Awards, an ACM SIGCOMM Test of Time Award and a National Science Foundation Career Award. Katabi is an ACM Fellow and was elected to the National Academy of Engineering.

ACM will present the 2017 ACM Prize in Computing at its annual Awards Banquet on June 23, 2018 in San Francisco, California.

ACM named John L. Hennessy, former President of Stanford University, and David A. Patterson, retired Professor of the University of California, Berkeley, recipients of the 2017 ACM A.M. Turing Award for pioneering a systematic, quantitative approach to the design and evaluation of computer architectures with enduring impact on the microprocessor industry. Hennessy and Patterson created a systematic and quantitative approach to designing faster, lower power, and reduced instruction set computer (RISC) microprocessors. Their approach led to lasting and repeatable principles that generations of architects have used for many projects in academia and industry. Today, 99% of the more than 16 billion micro-processors produced annually are RISC processors, and are found in nearly all smartphones, tablets, and the billions of embedded devices that comprise the Internet of Things (IoT).

Hennessy and Patterson codified their insights in a very influential book, Computer Architecture: A Quantitative Approach, now in its sixth edition, reaching generations of engineers and scientists who have adopted and further developed their ideas. Their work underpins our ability to model and analyze the architectures of new processors, greatly accelerating advances in microprocessor design.

The ACM Turing Award, often referred to as the “Nobel Prize of Computing,” carries a $1 million prize, with financial support provided by Google, Inc. It is named for Alan M. Turing, the British mathematician who articulated the mathematical foundation and limits of computing.

“ACM initiated the Turing Award in 1966 to recognize contributions of lasting and major technical importance to the computing field,” said ACM President Vicki L. Hanson. “The work of Hennessy and Patterson certainly exemplifies this standard. Their contributions to energy-efficient RISC-based processors have helped make possible the mobile and IoT revolutions. At the same time, their seminal textbook has advanced the pace of innovation across the industry over the past 25 years by influencing generations of engineers and computer designers.”

Attesting to the impact of Hennessy and Patterson’s work is the assessment of Bill Gates, principal founder of Microsoft Corporation, that their contributions “have proven to be fundamental to the very foundation upon which an entire industry flourished.”

Development of MIPS and SPARC
While the idea of reduced complexity architecture had been explored since the 1960s—most notably in the IBM 801 project—the work that Hennessy and Patterson led, at Stanford and Berkeley respectively, is credited with firmly establishing the feasibility of the RISC approach, popularizing its concepts, and introducing it to academia and industry. The RISC approach differed from the prevailing complex instruction set computer (CISC) computers of the time in that it required a small set of simple and general instructions (functions a computer must perform), requiring fewer transistors than complex instruction sets and reducing the amount of work a computer must perform.

Patterson’s Berkeley team, which coined the term RISC, built and demonstrated their RISC-1 processor in 1982. With 44,000 transistors, the RISC-1 prototype outperformed a conventional CISC design that used 100,000 transistors. Hennessy co-founded MIPS Computer Systems Inc. in 1984 to commercialize the Stanford team’s work. Later, the Berkeley team’s work was commercialized by Sun Microsystems in its SPARC microarchitecture.

Despite initial skepticism of RISC by many computer architects, the success of the MIPS and SPARC entrepreneurial efforts, the lower production costs of RISC designs, as well as more research advances, led to wider acceptance of RISC. By the mid-1990s, RISC microprocessors were dominant throughout the field.

Groundbreaking Textbook
Hennessy and Patterson presented new scientifically-based methodologies in their 1990 textbook Computer Architecture: a Quantitative Approach. The book has influenced generations of engineers and, through its dissemination of key ideas to the computer architecture community, is credited with significantly increasing the pace of advances in microprocessor design. In Computer Architecture, Hennessy and Patterson encouraged architects to carefully optimize their systems to allow for the differing costs of memory and computation. Their work also enabled a shift from seeking raw performance to designing architectures that take into account issues such as energy usage, heat dissipation, and off-chip communication. The book was groundbreaking in that it was the first text of its kind to provide an analytical and scientific framework, as well as methodologies and evaluation tools for engineers and designers to evaluate the net value of microprocessor design.

Biographical Background

John L. Hennessy
John L. Hennessy was President of Stanford University from 2000 to 2016. He is Director of the Knight-Hennessy Scholars Program at Stanford, a member of the Board of Cisco Systems and the Gordon and Betty Moore Foundation and Chairman of the Board of Alphabet Inc. Hennessy earned his Bachelor’s degree in electrical engineering from Villanova University and his Master’s and doctoral degrees in computer science from the State University of New York at Stony Brook.

Hennessy’s numerous honors include the IEEE Medal of Honor, the ACM-IEEE CS Eckert-Mauchly Award (with Patterson), the IEEE John von Neumann Medal (with Patterson), the Seymour Cray Computer Engineering Award, and the Founders Award from the American Academy of Arts and Sciences. Hennessy is a Fellow of ACM and IEEE, and is a member of the National Academy of Engineering, the National Academy of Sciences and the American Philosophical Society.

David A. Patterson
David A. Patterson is a Distinguished Engineer at Google and serves as Vice Chair of the Board of the RISC-V Foundation, which offers an open free instruction set architecture with the aim to enable a new era of processor innovation through open standard collaboration. Patterson was Professor of Computer Science at UC, Berkeley from 1976 to 2016. He received his Bachelor’s, Master’s and doctoral degrees in computer science from the University of California, Los Angeles.

Patterson’s numerous honors include the IEEE John von Neumann Medal (with Hennessy), the ACM-IEEE CS Eckert-Mauchly Award (with Hennessy), the Richard A. Tapia Award for Scientific Scholarship, Civic Science, and Diversifying Computing, and the ACM Karl V. Karlstrom Outstanding Educator Award. Patterson served as ACM President from 2004 to 2006. He is a Fellow of ACM, AAAS and IEEE, and was elected to the National Academy of Engineering and the National Academy of Sciences.

ACM will present the 2017 ACM A.M. Turing Award at its annual Awards Banquet on June 23, 2018 in San Francisco, California.

Ken Banks was named recipient of the Eugene L. Lawler Award for developing FrontlineSMS, using mobile technology and text messaging to empower people to share information, organize aid, and reconnect communities during crises. A self-described “mobile anthropologist,” Banks has a gift for building technology that benefits humanity. As someone who was writing code and tinkering with computers since he was 13, Banks instinctively saw an opportunity to harness the world’s most-used communication platform—mobile messaging—to help people in the developing world.  In 2005, he designed, coded and launched FrontlineSMS, a mobile messaging platform that allows people to subscribe to groups, receive alerts, and establish communication hubs. FrontlineSMS played an important role in the 2007 Nigerian presidential election, where it was used to monitor, identify and curtail violence and harassment at polling places. Because of FrontlineSMS’s built-in flexibility, it quickly became a standard platform deployed in 170 countries by countless organizations. It has been used to help family farmers in Laos, train rural medics in Ecuador, double the amount of patients receiving tuberculosis care in Malawi, and monitor disease outbreaks across Africa. 

Banks continues his work as an Entrepreneur-in-Residence at CARE International. To achieve CARE’s goal of raising more people above the $2 per day extreme poverty level, Banks is leading the development of a new mobile phone application for Village Savings and Loan Associations. Along with his colleagues at CARE, he is also investigating how technology might be used to advance gender equality in Rwanda. His two books The Rise of the Reluctant Innovator and Social Entrepreneurship and Innovation recount his experiences—and those of other global social innovators— and serve as guides for those who are inspired to leverage technology for positive social change.

The Eugene L. Lawler Award for Humanitarian Contributions within Computer Science and Informatics recognizes an individual or group who has made a significant contribution through the use of computing technology. It is given once every two years, assuming that there are worthy recipients. The award is accompanied by a prize of $5,000.