ACM President Cherri Pancake honored Vinton G. Cerf with the 2019 ACM Presidential Award. The award was presented to Cerf at ACM's annual Awards Banquet on June 15 in San Francisco.

His citation reads:
In addition to his well-publicized technical contributions, for which he won the Turing Award, Vint Cerf crafted a unique vision of what ACM could be and achieve as an organization. He has served as a member of ACM Council three times, and was elected ACM President in 2012. After completing his term as Past President, he became the Awards Co-Chair. That much is in the public record. But his singular contribution to ACM remains largely unknown: Vint was the principal driver in establishing the ACM Fellows Program in 1993. The Fellows program, of course, recognizes the top 1% of ACM members from around the world for their outstanding accomplishments and service to the computing community. The luster of becoming a Fellow has not diminished with time. Indeed, with the newer Distinguished Member grade, and with the eminence of each year's Fellows class (13 of whom have gone on to win the Turing Award), the program has only grown in stature. As for impact, Fellows constitute some of ACM's best ambassadors and serve as models for younger members. While the Fellows program is now an established part of the ACM "landscape," this was not always the case—and likely wouldn't be had Vint not championed the concept. This 2019 ACM Presidential Award recognizes his extraordinary record of service to ACM.

ACM and IEEE Computer Society named Mark D. Hill, a professor at a professor at the University of Wisconsin—Madison, the recipient of the 2019 Eckert-Mauchly Award. Hill was cited for contributions to the design and evaluation of memory systems and parallel computers. Widely regarded as the leading memory systems researcher in the world today, Hill made seminal contributions to the fields of cache memories, memory consistency models, transactional memory, and simulation. Hill’s work with over 160 co-authors, which has received more than 20,000 citations, has been guided by the tenet that researchers should develop designs and models. The Eckert-Mauchly Award is considered the computer architecture community’s most prestigious award.

In the 1980s Hill developed the “3C” model of cache misses. A “cache miss” is an instance when data requested for processing by software or hardware is not found in the computer’s cache. Cache misses can cause delays as the program or application must then access the data elsewhere. Hill’s 3C model classified these misses into “compulsory misses,” “capacity misses,” and “conflict misses.” The model was influential, as it led to important innovations such as victim caches and stream buffers, and is now a standard concept in computer architecture textbooks.

Many regard Hill’s work in in memory consistency models as his most significant contribution. With his student Sarita Adve, he developed SC for DRF: a consistency model using sequential consistency (SC), where data races can be avoided (data race free, or DRF). Hill’s SC for DRF model has had significant impact for computer architects, especially as multiprocessors became ubiquitous and architects had to reason about which memory consistency model to use in their architectures and implementations. Years after Hill developed SC for DRF, it became the basis of Java and C++ memory models and, more recently, is being used with graphics processing units (GPUs) to understand memory consistency with heterogeneous processors.

Hill’s third major contribution is his work in transactional memory, a technique to minimize blocking due to critical sections. With David Wood he developed the LogTM transactional memory system, one of the first and widely-cited approaches to transactional memory. For the first time, this system enabled transactions to overrun their buffer and cache capacities, making transactions significantly easier for programmers to implement.

Hill (with David Wood and others) also made significant contributions to the evaluation of parallel computers. The Wisconsin Wind Tunnel project, for instance, pioneered fast parallel simulation running on parallel machines. Other important tools Hill has produced to evaluate memory systems and parallel computers include his Dinero cache simulator, as well as the GEMS full system simulator and gem5, which have been cited over 3,000 times by researchers and practitioners. BadgerTrap, one of his most recent tools, studies virtual memory behavior. Hill has also had significant influence on virtual memory implementation. For example, he proposed the idea of “page reservation,” which is now used in Linux.

Hill will be formally recognized with the award at the ACM/IEEE International Symposium on Computer Architecture (ISCA) to be held June 22-26 in Phoenix, Arizona.

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.

Chelsea Finn of the University of California, Berkeley is the recipient of the 2018 ACM Doctoral Dissertation Award for her dissertation, “Learning to Learn with Gradients.” In her thesis, Finn introduced algorithms for meta-learning that enable deep networks to solve new tasks from small datasets, and demonstrated how her algorithms can be applied in areas including computer vision, reinforcement learning and robotics.

Deep learning has transformed the artificial intelligence field and has led to significant advances in areas including speech recognition, computer vision and robotics. However, deep learning methods require large datasets, which aren’t readily available in areas such as medical imaging and robotics.

Meta-learning is a recent innovation that holds promise to allow machines to learn with smaller datasets. Meta-learning algorithms “learn to learn” by using past data to learn how to adapt quickly to new tasks. However, much of the initial work in meta-learning focused on designing increasingly complex neural network architectures. In her dissertation, Finn introduced a class of methods called model-agnostic meta-learning (MAML) methods, which don’t require computer scientists to manually design complex architectures. Finn’s MAML methods have had tremendous impact on the field and have been widely adopted in reinforcement learning, computer vision and other fields of machine learning.

At a young age, Finn has become one of the most recognized experts in the field of robotic learning. She has developed some of the most effective methods to teach robots skills to control and manipulate objects. In one instance highlighted in her dissertation, she used her MAML methods to teach a robot reaching and placing skills, using raw camera pixels from just a single human demonstration.

Finn is a Research Scientist at Google Brain and a postdoctoral researcher at the Berkeley AI Research Lab (BAIR). In the fall of 2019, she will start a full-time appointment as an Assistant Professor at Stanford University. Finn received her PhD in Electrical Engineering and Computer Science from the University of California, Berkeley and a BS in Electrical Engineering and Computer Science from the Massachusetts Institute of Technology.

Honorable Mentions for the 2018 ACM Doctoral Dissertation Award go to Ryan Beckett and Tengyu Ma, who both received PhD degrees in Computer Science from Princeton University.

Ryan Beckett developed new, general and efficient algorithms for creating and validating network control plane configurations in his dissertation, “Network Control Plane Synthesis and Verification.” Computer networks connect key components of the world’s critical infrastructure. When such networks are misconfigured, several systems people rely on are interrupted—airplanes are grounded, banks go offline, etc. Beckett’s dissertation describes new principles, algorithms and tools for substantially improving the reliability of modern networks. In the first half of his thesis, Beckett shows that it is unnecessary to simulate the distributed algorithms that traditional routers implement—a process that is simply too costly—and that instead, one can directly verify the stable states to which such algorithms will eventually converge. In the second half of his thesis, he shows how to generate correct configurations from surprisingly compact high-level specifications.

Beckett is a researcher in the mobility and networking group at Microsoft Research. He received his PhD and MA in Computer Science from Princeton University, and both a BS in Computer Science and a BA in Mathematics from the University of Virginia.

Tengyu Ma’s dissertation, "Non-convex Optimization for Machine Learning: Design, Analysis, and Understanding,” develops novel theory to support new trends in machine learning. He introduces significant advances in proving convergence of nonconvex optimization algorithms in machine learning, and outlines properties of machine learning models trained via such methods. In the first part of his thesis, Ma studies a range of problems, such as matrix completion, sparse coding, simplified neural networks, and learning linear dynamical systems, and formalizes clear and natural conditions under which one can design provable correct and efficient optimization algorithms. In the second part of his thesis, Ma shows how to understand and interpret the properties of embedding models for natural languages, which were learned using nonconvex optimization.

Ma is an Assistant Professor of Computer Science and Statistics at Stanford University. He received a PhD in Computer Science from Princeton University and a BS in Computer Science from Tsinghua University.

ACM named Constantinos Daskalakis and Michael J. Freedman recipients of the ACM Grace Murray Hopper Award.

Daskalakis, a professor at the Massachusetts Institute of Technology, is recognized for his seminal contributions to the theory of computation and economics, particularly the complexity of Nash Equilibrium.

Strategic interaction greatly complicates behavior in socioeconomic environments, from traditional markets and offline social networks to modern technological systems such as online advertising platforms, kidney exchanges, cryptocurrencies, sharing economy applications, and online social networks. To analyze behavior in such strategic environments, economists have long relied on concepts of equilibrium. Daskalakis’s work, with Goldberg and Papadimitriou, has challenged equilibrium theory by showing that Nash equilibrium is computationally intractable and thus unattainable, in general. His work has influenced an ongoing reshaping of the study of strategic behavior, showing that computation must play an essential role in the foundations of game theory and economics. Daskalakis’s more recent work has resolved long-standing open problems in multi-dimensional mechanism design, and advanced several other fields, including machine learning, probability theory and statistics.

Freedman, a professor at Princeton University, is cited for the design and deployment of self-organizing geo-distributed systems.

By introducing new algorithms and protocols, Freedman has shown how to build scalable, performant, and autonomous distributed systems for modern heterogeneous deployments and realistic workloads. Some of Freedman’s most popular systems include CoralCDN, a content distribution infrastructure that has been deployed at hundreds of network sites worldwide and been used by millions of clients to share images, videos and other content; the JetStream system, which employs an innovative approach to data streaming analytics; and TimescaleDB, an open source time series database that provides complex queries at scale on both historical and fresh data. Additionally, in more fundamental research, Freedman and colleagues have demonstrated that theoretically deep cloud systems need not be slow or scale poorly.

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.

Pavel Pevzner, a professor at the University of California San Diego, receives the ACM Paris Kanellakis Theory and Practice Award for pioneering contributions to the theory, design and implementation of algorithms for string reconstruction and to their applications in the assembly of genomes.

Pevzner’s research interests span the field of computational biology, and his work has been guided by tailoring algorithmic ideas to biological problems. The life sciences have been transformed by the ability to rapidly sequence and assemble genomes for organisms from existing and extant species and use these assembled genomes to answer fundamental and applied questions in biology, medicine and other sciences. Pevzner has made fundamental contributions to the theoretical study of string algorithms and to their application to scalable reconstruction of genomes and other biological sequences such as antibodies and antibiotics. Pevzner’s algorithms underlie almost all sequence assemblers used today and were used to reconstruct the vast majority of genomic sequences available in databases.

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.

Henry Kautz was honored for contributions to artificial intelligence and computational social science, including fundamental results on the complexity of inference, planning and media analytics for public health.

Beginning with his doctoral dissertation, Kautz, now a professor at the University of Rochester, has studied how computers can infer the goals and plans of people by studying their behavior. He has made a range of fundamental contributions to theory and practice in knowledge representation and reasoning, planning and plan recognition and computational social science. Kautz was one of the pioneers in analyzing the computational complexity of knowledge representation formalisms. He was also a co-developer of the first randomized local search algorithms for Boolean satisfiability testing, which have found practical application in planning, graphical models, and software verification.

In the area of pervasive computing and social media analytics, his trailblazing projects have included a system to help cognitively disabled people find their way by inferring the transportation destinations of selected groups of people; a project that uncovered the central role of air travel in the spread of diseases by analyzing social media data; and an initiative to improve the efficiency of restaurant health inspections by combining social media reports of food poisoning with location data.

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 named Gerald C. Combs recipient of the ACM Software System Award for for creating the Wireshark network protocol analyzer, an essential tool for nearly anyone who designs, deploys, analyzes and troubleshoots the wide range of network protocols that tie the internet together, and for continued leadership of the international Wireshark developer community.

Combs started Wireshark as an open source project in 1997 under the name Ethereal. The software quickly became the most commonly used system for visually analyzing network protocol traffic. Before the advent of Ethereal and Wireshark, protocol analyzers were expensive, dedicated pieces of hardware that were only available to large institutions. The creation of an open source network protocol analyzer democratized access to network protocol analysis. It also enabled people to learn about network protocols, as they were able to visualize the traffic on their own networks. In addition, Wireshark has also had significant influence on the areas of network engineering and cybersecurity. Engineers who work alongside security experts in financial institutions and other high-profile businesses make extensive use of Wireshark in their ongoing fight against cybercrime.

Combs, who serves as Director of Open Source Projects at Riverbed Technology, has continued to work on the Wireshark code. He spent 20 years guiding the open source community that has developed around the software and leading SharkFest, an annual educational conference focused on sharing knowledge, experience and best practices among the Wireshark developer and user communities.

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.

Robert Sedgewick was named recipient of the Karl V. Karlstrom Outstanding Educator Award for developing classic textbooks and online materials for the study of algorithms, analytic combinatorics, and introductory computer science that have educated generations of students worldwide. Sedgewick is best known for his series of Algorithms textbooks, which have been bestsellers for four decades (12 books in four editions covering five programming languages). The books develop a scientific approach to the study of algorithms, based on experiments with real code to validate hypotheses about performance based on mathematical analysis.

His recent book (with Kevin Wayne), Computer Science: An Interdisciplinary Approach, is a comprehensive introduction to the field and was named by ACM Computing Reviews as “Best of Computing Notable Book” for 2017. His book Analytic Combinatorics (with Philippe Flajolet) is an advanced graduate text that has been recognized with the 2019 Leroy P. Steele Prize for Mathematical Exposition.

More recently, Sedgewick has been extremely active as a pioneer and innovator in online education. He has co-developed extensive online content associated with his books that attract millions of visitors annually. Sedgewick has also recorded over 100 hours of online lectures on programming, computer science, and algorithms that reach hundreds of thousands of people around the world. The Sedgewick-Wayne Algorithms online course has been listed as one of the top 10 Massive Open Online Courses (MOOCs) of all time.

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.

Victor Bahl was named recipient of the ACM Distinguished Service Award for significant and lasting service to the broad community of mobile and wireless networking, and for building strong linkages between academia, industry, and government agencies. His efforts have led to the creation of a prolific global community with a strong foundation that has created leaders and fostered and supported tens of thousands of researchers and engineers worldwide working in these areas. Bahl, a Distinguished Scientist at Microsoft Research, was a co-founder and the driving force behind ACM SIGMobile, ACM’s Special Interest Group dedicated to all things mobile. He created MobiSys, the International Conference on Mobile Systems, Applications and Services, and for nearly two decades has steered MobiCom, the International Conference on Mobile Computing and Networking. Under Bahl’s leadership, both of these conferences have grown to become highly respected international events and publication venues. Also in the vein of publishing and disseminating the best in mobile technology research, Bahl founded GetMobile, a quarterly scientific publication related to wireless communications and mobility, and served as its first editor.

He has been especially active in advancing the field by strengthening ties and fostering better understanding among academics, practitioners, and government officials. For example, he has positively influenced spectrum policies of the US Federal Communications Commission and that of several European, South American and Asian countries, through technology inventions, demonstrations, and technical evangelism involving academia-industry-government collaboration on opportunities around dynamic spectrum sharing, and he has initiated key efforts in mobile computing and wireless networking within the US National Science Foundation.

In the beginning of the last decade, when experimental wireless research was hampered by the lack of realistic hardware and software tools (especially in academia), Bahl led, through Microsoft Research, the creation and free distribution of the Mesh Academic Research Kit, a significant enabler for research in Wi-Fi systems, which has been adopted by more than 1,200 academic institutions worldwide. This toolkit allowed academic researchers to experiment with mesh technologies. He also drove the creation created of the complementary Microsoft Digital Inclusion program that disbursed more than $1.2 million in funding to academic institutions that applied wireless mesh and related technologies to bridge the digital divide in communities around the world. In the early days of cloud computing, Bahl created a research and training program, with tools and services, on cloud-powered mobile computing. Over 60 large universities offered senior and graduate-level courses based on this program.

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.

Meenakshi Balakrishnan was named recipient of the Eugene L. Lawler Award for research, development, and deployment of cost-effective embedded-system and software solutions addressing mobility and education challenges of the visually impaired in the developing world.

Balakrishnan, a professor at the Indian Institute of Technology, Delhi, has dedicated more than a decade to addressing the challenges of the visually impaired by developing low-cost, computing technology-based solutions. Each of his devices has been developed by the meticulous integration of hardware, software, and firmware. His applications have not only improved the quality of life for countless people, but also have made their day-to-day lives dramatically safer. These technologies are especially valuable in the developing world, where there are fewer resources for the visually impaired.

Perhaps his best-known technology is the SmartCane project, which allows the visually impaired to detect items above their knees within a distance of 3 meters. Balakrishnan equipped the probing cane with ultrasonic ranging, wherein the cane conveys the distance of obstacles using vibrations. Balakrishnan has also worked tirelessly to bring the SmartCane to market at an affordable cost. Working with for-profit, nonprofit, and government organizations, he introduced the SmartCane at 5% of the cost of a comparable product in the West. Within India he has made over 70,000 devices available through government initiatives and 45 partner agencies. SmartCane has also won numerous awards, including the Best Paper Award at the International Conference on Mobility and Transport for Elderly and Disabled Citizens (TRANSED) 2010.

Additional technologies Balakrishnan and his lab have developed include the OnBoard bus identification and homing system, which helps the visually impaired identify bus routes and locate the entry door, and The Refreshable Braille, which allows the visually impaired to read digital text line-by-line through a tactile interface.

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.

Chris Stephenson was named recipient of the Outstanding Contribution to ACM Award for advancing CS education by architecting and nurturing the Computer Science Teachers Association to incorporate more than 22,000 K-12 CS educators and partners into the ACM community.

Central to Stephenson’s vision has been the idea that advancing computing as a professional field requires K-12 students to be introduced to computer science by educators with the tools, training, knowledge, and confidence both to teach the subject matter and to inspire students with their passion. She also has been guided by the ideas that K-12 teachers will be more effective in the classroom if actively engaged with other members of the professional computing community, and that K-12 computer science education is more effective when it is informed by academic research and industry expertise.

To realize her vision, Stephenson founded the Computer Science Teachers Association (CSTA) in 2004, with the support of ACM, and thereafter became its founding Executive Director. During her 10 years leading CSTA, she grew the organization to include 20,000 members around the world and 60 regional chapters.

Her scholarly research contributions were disseminated in several influential reports including: Bringing Computational Thinking to K-12: What Is Involved and What Is the Role of the Computer Science Education Community?; the inaugural CSTA K-12 Computer Science Standards; Running on Empty: The Failure to Teach K–12 Computer Science in the Digital Age; and Bugs in the System: Computer Science Teacher Certification in the U.S. These reports have led to projects, initiatives, and policy changes that have deeply and positively impacted K-12 education and educators globally.

Now Head of Computer Science Education Strategy at Google, Stephenson has continued her work with ACM education initiatives. She is currently a member of the ACM Education Board, where she has been actively engaged in developing curricular materials to meet the needs of computer science educators and students, both in the US and abroad. She also recently co-chaired the Board’s retention in undergraduate computer science task force.

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.

ACM named Mendel Rosenblum of Stanford University the recipient of the inaugural ACM Charles P. “Chuck” Thacker Breakthrough in Computing Award. Rosenblum is recognized for reinventing the virtual machine for the modern era and thereby revolutionizing datacenters and enabling modern cloud computing. In the late 1990s, Rosenblum and his students at Stanford University brought virtual machines back to life by using them to solve challenging technical problems in building system software for scalable multiprocessors. In 1998, Rosenblum and colleagues founded VMware. VMware popularized the use of virtual machines as a means of supporting many disparate software environments to share processor resources within a datacenter. This approach ultimately led to the development of modern cloud computing services such as Amazon Web Services, Microsoft Azure, and Google Cloud.

The ACM Charles P. “Chuck” Thacker Breakthrough in Computing Award recognizes individuals or groups who have made surprising, disruptive, or leapfrog contributions to computing ideas or technologies. Recipients of the award are expected to give the ACM Breakthrough Lecture at a major ACM conference. The award is accompanied by a $100,000 cash prize, with financial support provided by Microsoft.

“The new paradigm of cloud computing, in which computing services are delivered over the internet, has been one of the most important developments in the computing industry over the past 20 years,” said ACM President Cherri M. Pancake. “Cloud computing has vastly improved the efficiency of systems, reduced costs, and been essential to the operations of businesses at all levels. However, cloud computing, as we know it today, would not be possible without Rosenblum’s reinvention of virtual machines. His leadership, both through his early research at Stanford and his founding of VMware, has been indispensable to the rise of datacenters and the preeminence of the cloud.”

As the name suggests, virtual machines are systems comprised of software, hardware, or a combination of the two, that enable one computer to behave like another. IBM and others developed the idea of virtualization in the 1960s to enable timesharing. However, as new methods of timesharing were developed and the price of hardware dropped, virtual machines fell out of favor. By the late 1980s, virtualization was considered an irrelevant and obsolete idea.

In the late 1990s, Rosenblum and his students at Stanford University revisited the idea of virtual machines to develop system software for FLASH, an experimental large-scale multiprocessor. They recognized that existing operating systems could not support large numbers of processors, and modifying one to work efficiently on FLASH would have been very difficult. Instead, they decided to use virtual machines to run multiple operating system instances on FLASH, each with only a few virtual processors.

The success of his work on FLASH prompted Rosenblum to found the company VMware in 1998 with Diane Greene, Edouard Bugnion, Scott Devine, and Ellen Wang. VMware popularized the use of virtual machines as a means of allowing any disparate software environments to share processor resources within a datacenter. Today, every commercial cloud environment, including major providers such as Amazon Web Services, Microsoft Azure, and Google Cloud, is based on virtualization concepts developed by Rosenblum and his colleagues.

“We’re excited to see the contributions of Mendel Rosenblum recognized with the inaugural ACM Charles P. Thacker Breakthrough Award,” said Eric Horvitz, Technical Fellow and Director of Microsoft Research. “The award was envisioned to honor the intellect and vision of Chuck Thacker, who was known for upending conventional thinking and introducing breakthrough innovations that changed the trajectory of computing. Mendel Rosenblum is a fabulous choice to receive the inaugural Thacker Award. Rosenblum sought to address a daunting new challenge by reimagining virtualization, an approach that many had bypassed. Virtual machines are essential to the way cloud computing functions, and it is hard to overstate the importance of cloud computing for the computing field as well as for industry more generally.”

Biographical Background

Mendel Rosenblum is the DRC Professor in the School of Engineering and Professor of Electrical Engineering at Stanford University. In 1998, he co-founded VMware, a private company that developed many of the core technologies that underpin cloud computing today. As a subsidiary of Dell Technologies, VMware remains a leader in cloud computing and platform virtualization software and services, employing more than 21,000 people.

A graduate of the University of Virginia, Rosenblum earned his Master’s and doctoral degrees in Computer Science from the University of California, Berkeley. Rosenblum is a Fellow of ACM, and his numerous honors include receiving the ACM Software System Award for VMware Workstation 1.0; the ACM/SIGOPS Mark Weiser Award for innovation in operating system research; the IEEE Reynolds B. Johnson Information Storage Award (with John Ousterhout); and the ACM Doctoral Dissertation Award for his dissertation “The Design and Implementation of a Log-Structured File System.” Rosenblum is a member of the National Academy of Engineering and the American Academy of Arts and Sciences.

Rosenblum will formally receive the award at ACM’s annual Awards Banquet on June 15, 2019 in San Francisco.

ACM named Shwetak Patel of the University of Washington and Google the recipient of the 2018 ACM Prize in Computing for contributions to creative and practical sensing systems for sustainability and health. Before Patel’s work, most systems for monitoring energy and health required expensive and cumbersome specialized devices, precluding practical widespread adoption. Patel and his students found highly creative ways to leverage existing infrastructure to make affordable and accurate monitoring a practical reality. Patel quickly turned his team’s research contributions into real-world deployments, founding companies to commercialize their work.

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

“Despite the fact that he is only 37, Shwetak Patel has had significant impact on the field of ubiquitous computing for nearly two decades,” said ACM President Cherri M. Pancake. “His work has ushered in some really exciting possibilities in the areas of sustainability and health. The widespread adoption of systems where individuals can monitor their health with smartphones could revolutionize health care—especially in the developing world. Shwetak Patel certainly exemplifies the ACM Prize’s goal of recognizing work with ‘fundamental impact and broad implications.’”

“Infosys is proud to support the ACM Prize in Computing, which this year recognizes Shwetak Patel for his trailblazing work in ubiquitous computing,” said Pravin Rao, COO of Infosys. “Beyond breaking new conceptual ground through research in many areas, Shwetak Patel is especially adept at rapidly bringing his ideas to the public via new products that are accessible and affordable. Patel’s vision for ubiquitous computing is to enhance our everyday world with sensing, data processing and computation. The way in which his digital health initiatives combine AI with sensors and mobile computing is also very exciting and will likely have a significant impact on health care around the world for many years to come.”

Patel’s research closed the gap between science fiction and reality in many applications in ubiquitous computing for sustainability and health.

Monitoring Energy and Water Usage in the Home

With the emergence of embedded computing systems over the past few decades, a longstanding goal has been to use embedded devices to gain a more fine-grained understanding of home water and energy usage than is available by simply reading a monthly utility bill. In industry, one proposed solution has been to develop “smart appliances” in which items such as refrigerators or televisions would be fitted with special meters so that that their energy consumption could be monitored. Rather than having smart devices throughout the home, each with its own meter, Patel recognized that a home’s electrical system (and later its plumbing system) can be reconsidered as a network capable of capturing and transmitting information. Patel’s insight was that each appliance, as it uses power, generates and transmits information as “noise” (perturbations) on the circuit. Patel then developed a method to “disambiguate” (separate and catalog) which rooms, appliances, and times of day energy was being used. Patel engineered the system so that an entire home could be monitored with just one meter for electricity and one meter for plumbing. Zensi, Inc., the startup he formed to commercialize his work, was sold to Belkin, which subsequently opened a 25-person R&D lab in Seattle to conduct further sustainability research alongside Patel in his team. In developing these products, Patel also became an electrician and plumber.

Low-Powered Home Sensors

Building on his work on sustainability in residential environments, Patel next developed a new approach for wireless sensor nodes in the home, which dramatically reduced power consumption of each node while continuing to cover the whole home. Patel’s Sensor Nodes Utilizing Powerline Infrastructure (SNUPI) nodes contain an ultra-low-power transmitter that extends its range by coupling its wirelessly transmitted signal to the existing powerlines. SNUPI was a core component of Patel’s next startup, WallyHome. Through its network of low-powered sensors WallyHome monitors temperature, humidity and any potential water leakages. For example, if an event(such as a dishwasher leak) occurs in the home, the homeowner will receive an instant text on their mobile phone. While WallyHome was purchased by Sears Holding Company in 2015, Patel’s research in smart home sensing has informed much of the growing smart home industry, including companies like Google, Next, and Samsung.

Digital Health

More recently, Patel has leveraged sensors already on mobile phones (such as cameras and microphones) for physiological sensing and the management of chronic diseases. These technologies include SPiroSmart and CoughSense, which monitor lung function; BiliCam, which detects neonatal jaundice in newborns; HemaApp, which monitors hemoglobin levels; OsteoApp, to screen for osteoporosis; and BPSense, which monitors blood pressure. Patel has been working closely with Bill Gates and the Gates Foundation to share these technologies throughout the developing world. His work using a microphone for respiratory monitoring has already been deployed in parts of India and Bangladesh, and HemaApp is being used in Peru to screen for childhood anemia. He also commercialized some of these technologies, which were acquired by Google.

Biographical Background

Shwetak N. Patel is the Washington Research Foundation Entrepreneurship Endowed Professor in Computer Science and Engineering at the University of Washington, where he directs the Ubicomp Lab, which develops innovative sensing systems for real-world applications in health, sustainability and novel interactions. He is also a director at Google working on health care.

Patel earned his Bachelor’s and PhD degrees in Computer Science from Georgia Institute of Technology. His numerous honors include receiving a MacArthur Fellowship, a Sloan Fellowship, a Presidential Early Career Award for Scientists and Engineers (PECASE), MIT TR-35 Award, and a National Academy of Engineering Gilbreth Award. Patel is a Fellow of ACM.

Patel will formally receive the ACM Prize in Computing at ACM’s annual awards banquet on June 15, 2019 in San Francisco.

University of Montreal Professor Yoshua Bengio was named co-recipient of the 2018 ACM A.M. Turing Award along with Geoffrey Hinton and Yann LeCun for conceptual and engineering breakthroughs that have made deep neural networks a critical component of computing. In the 1990s, Bengio combined neural networks with probabilistic models of sequences, such as hidden Markov models. These ideas were incorporated into a system used by AT&T/NCR for reading handwritten checks, were considered a pinnacle of neural network research in the 1990s, and modern deep learning speech recognition systems are extending these concepts.

In 2000, Bengio authored the landmark paper, “A Neural Probabilistic Language Model,” that introduced high-dimension word embeddings as a representation of word meaning. Bengio’s insights had a huge and lasting impact on natural language processing tasks including language translation, question answering, and visual question answering. His group also introduced a form of attention mechanism which led to breakthroughs in machine translation and form a key component of sequential processing with deep learning.

Since 2010, Bengio’s papers on generative deep learning, in particular the Generative Adversarial Networks (GANs) developed with Ian Goodfellow, have spawned a revolution in computer vision and computer graphics. In one fascinating application of this work, computers can actually create original images, reminiscent of the creativity that is considered a hallmark of human intelligence.

ACM named Elisa Bertino of Purdue University the 2019-2020 ACM Athena Lecturer for pioneering and impactful contributions to data management, security, and privacy, along with outstanding contributions to broadening participation in computing via professional leadership and mentoring. Bertino is recognized as one of the top data management and data security experts in the world, and has made contributions to data security and privacy in many different contexts, including context-based access control; digital identity management; data integrity; Internet of Things and sensor network security; secure and privacy-preserving provenance; privacy-preserving analytics; protection from insider threats; and cloud security. Through these efforts, she provided formal foundations and implementations of mechanisms that have become commonplace in industrial products. Bertino is also an outstanding educator and mentor who has been especially active in encouraging young women to pursue careers in computing.

Initiated in 2006, the ACM 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 Two Sigma. The Athena Lecturer is invited to present a lecture at an ACM event. Bertino chose to give her Athena Lecture at the ACM Conference on Data Application, Security and Privacy (CODASPY 2019) in Dallas, Texas.

“There are few issues more important to the computing field, and the broader society, than cybersecurity,” said ACM President Cherri M. Pancake. “However, modern cybersecurity approaches need to take into account the way we live now. Elisa Bertino has made fundamental contributions that allow people access to systems based on their roles, the time of day, as well as their locations. These contributions are especially significant because of the mobile revolution and Internet of Things—as well as the fact that systems can be attacked from anywhere in the world. Beyond her extensive research contributions, Bertino has had a lasting impact on the field through her mentorship of younger colleagues.”

Security Access Control Based on Time and Location

In the computer security field, role-based access control (RBAC) allows only authorized users to access a system. Bertino was a trailblazer in extending RBAC controls to take contextual information into account, including time and space considerations. Her 2001 paper T-RBAC: A temporal role-based access control model, co-authored with Piero Andrea Bonatti and Elena Ferrari, outlined how access to a system could be made available at certain times and unavailable at others. The paper has been cited more than 1,000 times and transformed the design of security systems developed by industry.

In 2007 Bertino and co-authors made another significant contribution to role-based access control in the paper GEO-RBAC: A Spatially Aware RBAC, in which the access depends on user location. Bertino’s GEO-RBAC model was introduced before mobile computing became ubiquitous, and has become an essential component of most security systems.

Bertino has made several other contributions to access control models and enforcement mechanisms, including original contributions to privacy-aware access control, attribute-based access control, encryption-based access control for data on the cloud and tools for policy analysis.

Security of Cellular Networks

Bertino’s pioneering work on the security of cellular networks is exemplified in her recent paper, LTEInspector: A Systematic Approach for Adversarial Testing of 4G, which introduced a model-based testing approach to investigate the security and privacy of the 4G LTE protocol. Bertino and colleagues uncovered 10 new, as well as nine prior, attacks. Security experts see the LTEInpsector approach as an important tool in securing 4G as well as 5G networks. For this recent work, Bertino was named to the GSMA Mobile Security Research Hall of Fame.

Professional Leadership and Mentoring

In the spirit of the Athena Award, Bertino has been a strong advocate and mentor for women. For example, 16 of the 35 PhD students she has mentored are women, and five of the PhD students currently working in her lab are women. To address the ongoing gender imbalance in the cybersecurity field, Bertino recently co-founded (with Danfeng Yao) the Workshop for Women in Cybersecurity (CyberW).

Biographical Background

Elisa Bertino is the Samuel Conte Professor of Computer Science at Purdue University, where she also heads the Cyber Space Security Lab. She held positions in industry, including the IBM Almaden Research Center, and academia, most notably at the University of Milan, before joining Purdue University in 2004. Bertino received her Dr degree in Computer Science from the University of Pisa.

Bertino is a Fellow of ACM, IEEE and AAAS, and has received several awards and honors, including the IEEE Computer Society Technical Achievement Award, the Tsutomu Kanai Award, and the ACM SIGSAC Outstanding Contributions Award.

The ACM Athena Lecturer 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.” 

Bertino will formally receive the Athena Lecturer Award at ACM’s annual awards banquet on June 15, 2019 in San Francisco.

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.

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. 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.

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.

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..