About ACM Athena Lecturer Award

New York, NY, April 26, 2023 – ACM, the Association for Computing Machinery, today named Margo Seltzer, a Professor at the University of British Columbia, as the 2023-2024 ACM Athena Lecturer. Seltzer is recognized for foundational research in file and storage systems, pioneering research in data provenance, impactful software contributions in Berkeley DB, and tireless dedication to service and mentoring. Initiated in 2006, the ACM Athena Lecturer Award celebrates women researchers who have made fundamental contributions to computer science.

Database Software

In 1992, while studying at the University of California at Berkeley, Seltzer, along with Keith Bostic and Mike Olson, introduced BerkeleyDB, a database software library. Berkeley DB underpinned a range of first-generation Internet services including account management, mail servers, and online trading platforms. This software has been a part of many popular operating systems including Linux, FreeBSD, Apple's OSX, and the GNU standard C library (glibc). Originally developed as an open-source library, Seltzer and Bostic founded Sleepycat Software in 1996 to continue the development of Berkeley DB and provide commercial support. Berkeley DB was an early and influential example of the NoSQL movement and pioneered the "dual license" approach to software licensing.

Data Provenance and Log-Structured File Systems

Seltzer later pioneered whole-system data provenance, a paradigm that provides system support for assessing the quality of information by understanding where the data comes from, who is using the data, and how it was obtained. Her research demonstrated how provenance could be practically supported at the system level to implement important applications in security and compliance. Her subsequent work focused on applications of provenance, including intrusion detection, data loss prevention and attack attribution, and computational reproducibility.

She is also known for her careful and nuanced work in log-structured file systems, where she adapted various approaches for use in the UNIX file systems and updates of file system metadata.

Teaching and Service

Seltzer has received several awards for excellence in teaching and leadership for her work broadening participation in computer science. She is deeply involved in mentoring, and several of her former students have become leaders in academia and industry. She has served as program chair for conferences in systems and databases and serves on numerous advisory boards for scientific and national boards.

“To be selected for the ACM Athena Award, a candidate must pass a very high bar,” said ACM President Yannis Ioannidis. “She must be a person who has both made fundamental technical contributions and impacted the computing community through service. Margo Seltzer not only meets these criteria but sets the bar extremely high. Regarding the former, her work on Berkeley DB and data provenance has broken new ground and has been very impactful in the data management and systems communities, both in academia and industry. Regarding the latter, in addition to her teaching and mentoring awards, she is known for her efforts to broaden participation in computer science among traditionally underrepresented groups. When considering all that Margo is involved in, one question that comes to mind is ‘Where does she find the time?’ Having overlapped with her at Harvard for a year, I think I have the answer: `She doesn’t find it. She creates it!’ We congratulate Margo Seltzer on being named the ACM Athena Lecturer and we look forward to celebrating her work at the ACM Awards Banquet.”

Seltzer will be formally presented with the ACM Athena Lecturer Award at the annual ACM Awards Banquet, which will be held this year on Saturday, June 10 at the Palace Hotel in San Francisco. The ACM Athena Lecturer Award carries a cash prize of $25,000, with financial support provided by Two Sigma.

ACM named Éva Tardos, a Professor at Cornell University, as the 2022-2023 ACM Athena Lecturer. Tardos is recognized for fundamental research contributions to combinatorial optimization, approximation algorithms, and algorithmic game theory, and for her dedicated mentoring and service to these communities. Initiated in 2006, the ACM Athena Lecturer Award celebrates women researchers who have made fundamental contributions to computer science.

Tardos is one of the most influential leaders in the field of theoretical computer science. Her impact spans deriving deep theoretical results, shaping new research areas, and influencing a broad range of applications. Her key contributions in combinatorial optimization include the first strongly polynomial-time algorithm for the minimum-cost flow problem (for which she received the Fulkerson Prize) and a general framework for fast approximation of packing and covering linear programs.

She developed fundamental approximation algorithms, developing new algorithmic techniques for the use of linear programming and rounding in network design problems. The applications of her work include solving problems in facility location, network routing, and the spread of influence in social networks. Tardos also played a key role in founding the field of algorithmic game theory by developing algorithms in the presence of self-interested agents that are governed by incentives and economic constraints.

Her pioneering work using game-theoretic ideas to quantify the performance gaps between centrally managed network traffic and the flow of traffic directed by self-interested agents (selfish routing) was recognized with the Gödel Prize. She subsequently developed new approaches to analyzing dynamic games and new algorithms for mechanism design including composable ones.

Tardos is an outstanding educator, mentor, and leader in her scientific community. She has received awards for excellence in teaching and leadership for her work supporting women in computer science, and several of her former students are now prominent figures in the field. She co-authored one of the leading textbooks used in undergraduate computer science, Algorithm Design, and co-edited Algorithmic Game Theory, a significant book at the intersection of economics and computation.

“Each year ACM honors a preeminent woman computer scientist as the Athena Lecturer,” said ACM President Gabriele Kotsis. “Athena Lecturers are recognized for both enduring technical contributions, as well as their community service and mentoring. Éva Tardos has played a central role in shaping the field of algorithms over three decades, and she has been one of the foremost authorities in the emerging field of algorithmic game theory. Her work, her generosity to younger colleagues, and her service to the wider field have been outstanding. We look forward to presenting her with this award and we know she will continue to make contributions for years to come.”

Tardos will be formally presented with the ACM Athena Lecturer Award at the annual ACM Awards Banquet, which will be held this year on Saturday, June 11 at the Palace Hotel in San Francisco. The ACM Athena Lecturer Award carries a cash prize of $25,000, with financial support provided by Two Sigma.

ACM named Ayanna Howard, dean of The Ohio State University College of Engineering, as the 2021-2022 ACM Athena Lecturer. Howard is recognized for fundamental contributions to the development of accessible human-robotic systems and artificial intelligence, along with forging new paths to broaden participation in computing through entrepreneurial and mentoring efforts. Her contributions span theoretical foundations, experimental evaluation, and practical applications.

Howard is a leading roboticist, entrepreneur, and educator whose research includes dexterous manipulation, robot learning, field robotics, and human-robot interaction. She is a leader in studying the overtrust that people place in robots in various autonomous decision-making settings. In addition to her stellar research record, Howard has a strong record of service that demonstrates her commitment to advancing the field and broadening participation.

“Ayanna Howard is a trailblazer in vital research areas, including topics such as trust and bias in AI, which will continue to be front-and-center in society in the coming years,” said ACM President Gabriele Kotsis. “The quality of her research has made her a thought leader in developing accessible human-robot interaction systems. Both as an entrepreneur and mentor, Ayanna Howard has worked to increase the participation of women and underrepresented groups in computing. For all these reasons, she is precisely the kind of leader ACM seeks to recognize with the Athena Lecturer Award.”

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 gives an invited talk at a major ACM conference of her choice.

KEY TECHNICAL CONTRIBUTIONS

Robotic Manipulation
Her doctoral research on dexterous robotic manipulation of deformable objects proposed some of the first ideas on the modeling of deformable objects via physical simulation, such that they could be robustly grasped by robot arms. This work also demonstrated how neural networks could be trained to extract the minimum force required for subsequent deformable object manipulation tasks.

Terrain Classification of Field Robots
Terrain classification is critical for many robots operating in unstructured natural field environments, including navigating the Arctic or determining safe landing locations on the surface of Mars. Howard’s work introduced fuzzy logic methods to model environmental uncertainty that advanced the state of the art in field robotics, including finding evidence of never-before-observed life on Antarctica’s sea floor.

Robotics for Children with Special Needs
Howard studied the ways in which socially-effective robots could improve the access and scalability of services for children with special needs, as well as potentially improve outcomes through the engaging nature of robots. In adapting her contributions to real-world settings for assistive technology for children, her work has also provided first-of-its-kind computer vision techniques that analyze the movement of children to devise therapeutic measures.

Overtrust in Robotics and AI Systems
Howard is a leader in modeling trust among humans, robots and AI systems, including conversational agents, emergency response scenarios, autonomous navigation systems, child-robot interaction, and the use of lethal force. Her work introduced human-robot interaction algorithms that, for the first time, quantified the impact of robot mistakes on human trust in a realistic, simulated, and very high-risk scenario. This work has led to better understanding of the biases and social inequities underlying AI and robotic systems.

BROADENING PARTICIPATION/SERVICE TO THE FIELD

Howard has created and led numerous programs designed to engage, recruit, and retain students and faculty from groups that are historically underrepresented in computing, including several NSF-funded Broadening Participation in Computing initiatives. She was the principal investigator for (PI)/co-PI for Popularizing Computing in the Mainstream, which focused on creating interventions to engage underrepresented groups in the computing field; Advancing Robotics for Societal Impact Alliance , an initiative to provide mentorship to computer science faculty and students at Historically Black Colleges and Universities (HBCUs); and Accessible Robotic Programming for Students with Disabilities, an initiative to engage middle- and high school students with disabilities in robotics-based programming activities. She also led and co-founded efforts to broaden participation in the field through the IEEE Robotics PhD Forum and the CRA-WP Graduate Cohort Workshop for Inclusion, Diversity, Equity, Accessibility, and Leadership Skills.

As part of her service to the field, Howard has held key roles on various editorial boards and conference/program committees. Some of her more high-profile efforts have included co-organizing the AAAI Symposium on Accessible Hands-on AI and Robotics Education, the International Joint Conference on Neural Networks, the International Conference on Social Robotics, and the IEEE Workshop on Advanced Robotics and Its Social Impacts.

ACM has named Sarit Kraus of Bar-Ilan University the 2020-2021 ACM Athena Lecturer for foundational contributions to artificial intelligence, notably to multi-agent systems, human-agent interaction, autonomous agents and nonmonotonic reasoning, and exemplary service and leadership in these fields. Her contributions span theoretical foundations, experimental evaluation, and practical applications. Multi-agent systems are regarded as vital to the increasingly complex challenges within artificial intelligence and have broad applications in a number of areas.

Kraus is recognized as one of the world’s leading researchers in multi-agent systems, in which a distributed group of agents (computers, robots, and/or humans) interact and work collaboratively to solve problems. Beyond her work in multi-agent systems, Kraus has made significant contributions to knowledge representation (another area of artificial intelligence research) by incorporating nonmonotonic reasoning, and to randomized policies for security applications by combining methods from game theory, machine learning and optimization. Kraus is also recognized for her service to the field as an outstanding educator and mentor, as well as for her conference, editorial, and leadership roles.

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 gives an invited talk at a major ACM conference of her choice.

“Each year, it is ACM’s honor to put a spotlight on the instrumental role that women play in the computing field by selecting an Athena Lecturer,” said ACM President Cherri M. Pancake. “The ability of multi-agent systems to effectively work together is at the core of AI research and will be the lynchpin of many of the technologies that will shape the future. With seminal work in AI stretching back to the early 1990s, it is fair to say that Sarit Kraus has introduced new ways of thinking in multi-agent systems research, while also shepherding research ideas into practical applications. Her colleagues also cite her generosity and sensitivity in mentoring the next generation of researchers, which aligns perfectly with our mission in bestowing this particular award.”

Multi-agent Systems

In a multi-agent system (MAS), a distributed network of agents (which could include computers or humans) work together to solve a problem that is beyond the capacity of a single agent. For example, if two autonomous vehicles were approaching an intersection, the software systems (agents) in each vehicle would communicate with each other via sensors, and perhaps a central computer coordinating traffic in the neighborhood in order to ensure the vehicles would not collide. Multi-agent systems are increasingly used in a wide range of areas, from Internet of Things (IoT) applications like smart cities, supply-chain management, smart electric grids, robotics, and online trading to many mobile computing services.

The focus of Kraus’s research in multi-agent systems has been to develop intelligent agents that can interact proficiently with each other and with people, in both cooperative and conflicting scenarios. As with other areas of AI, this work requires an understanding of human behavior and decision-making in order to develop models for how the agents will make decisions. Toward this goal, Kraus developed innovative methods combining machine learning techniques for human modeling, formal decision-making and game theory approaches to enable agents to interact well with people. In a series of seminal papers, Kraus developed formal models of agent interaction that have been used in several practical applications including the ARMOR project, which combines game theory and optimization methods to improve robotics security at venues such as the Los Angeles International Airport; the Sheba Project, which deploys machine-learning techniques to facilitated training and rehabilitation (including speech therapy) at hospitals in Israel; developing a virtual suspect, integrating psychological models and machine learning, to enhance law enforcement training; recommendation systems for smart cars; and developing an automated mediator for use in studies on the influence of different mediation types on intra- and inter-country negotiations.

Kraus’s work in multi-agent systems also includes the shared plans framework for collaborative planning and acting, models of coalition formation, automated negotiation, and culture-sensitive agents. For example, her 1996 paper, co-authored with Barbara Grosz, “Collaborative plans for complex group action,” provided a framework for investigating fundamental questions about how agents collaborate and has been especially influential in the development of MAS research, having been cited nearly 1,400 times.

Automated Negotiation

Kraus is recognized as a world leader in a subfield of multi-agent systems called automated negotiation, in which the goal is to build computers that can reach agreements with other computers, negotiate on behalf of humans, or perhaps do a better job than human negotiators. Automated negotiation systems are designed to operate without any human intervention. Automated negotiation especially comes into play in economic domains and has garnered increasing interest with the rise of e-commerce applications. As with her broader work within multi-agent systems, Kraus designed models and protocols for automated negotiation algorithms that she introduced in dozens of seminal papers stretching back to the early 1990s. Kraus is a co-author (with Michael Wooldridge and Shaheen Fatima) of the book Principles of Automated Negotiation, a state-of-the-art treatment of the subject.

Nonmonotonic Reasoning
In designing artificially intelligent systems, researchers seek to simulate the logic humans use to make assumptions about the world, even in the face of incomplete or new information. In the traditional example, if a human is told that an animal is a bird, the human will logically assume that it can fly. However, when the human is informed that the bird is a penguin, which cannot fly, the human must adjust his/her logic to allow for potential exceptions to the general rule “all birds fly.” In artificial intelligence, nonmonotonic reasoning refers to the ability of a system to take back conclusions when initial assumptions were incorrect and/or new information is given. Nonmonotonic systems are also designed to reach new/alternative conclusions in these instances. Kraus was the lead author (with Daniel Lehmann and Menachem Magidor) of the landmark 1990 paper “Non-monotonic Reasoning, Preferential Models and Cumulative Logics,” which has been recognized as a highly useful attempt to provide theoretical foundations for nonmonotonic logic that could be used in AI systems. Kraus’s subsequent publications in nonmonotonic logic have shaped the development of this important subfield of AI and opened up new lines of research.

Service to the Field and Mentoring
Over the years, Kraus has served the research community by taking on many volunteer roles. She has been a General, Program or Workshop Chair for several leading AI conferences including IJCAI, ICMAS, AAMAS, and ECAI. Currently, she is serving on the editorial boards of the Journal of Artificial Intelligence Research, Journal of Autonomous Agents and Multi-agent Systems, and Annals of Maths & AI. As an educator and mentor, she has supervised 62 Master’s students and 34 PhD students. In the spirit of the ACM Athena Lecturer Award, Kraus is also a recognized leader in efforts to increase the participation of women in science.

Biographical Background
Sarit Kraus is a Professor of Computer Science at Bar-Ilan University in Ramat Gan, Israel, where her research is focused on intelligent agents and multi-agent systems. She received her Bachelor’s, Master’s and PhD degrees from The Hebrew University of Jerusalem.

Kraus has written six books, 122 journal articles, and 176 conference papers, and has received nine patents. Twelve of her publications have won best paper awards and two have won the IFAAMAS Influential Paper Award. She is a Fellow of ACM, the European Association for Artificial Intelligence (EurAI), and the Association for the Advancement of Artificial Intelligence (AAAI). Her honors include receiving the IJCAI Computers and Thought Award in 1995, the ACM SIGART Autonomous Agents Research Award in 2007, and the prestigious Israel EMET Prize in 2010.

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.

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 Lydia E. Kavraki of Rice University as the 2017-2018 Athena Lecturer. Kavraki was cited for the invention of randomized motion-planning algorithms in robotics and the development of robotics-inspired methods for bioinformatics and biomedicine. Kavraki is an internationally recognized leader in developing physical algorithms, an area that addresses the computational challenges of objects moving in space while subject to physical constraints. She has made significant contributions in an impressively wide range of areas, from how a robot might move through a course of obstacles, to how a drug molecule might change its shape to interact with a target protein, to her current work with planning the motions of Robonaut 2, NASA’s robotic assistant at the International Space Station.

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 Athena Lecturer is invited to present a lecture at an ACM event. 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." 

“Planning the motion of objects in a three-dimensional space has been a central challenge in the robotics field for a long time,” said ACM President Vicki L. Hanson. “Lydia Kavraki’s Probabilistic Roadmap Method has had a tremendous impact. It is now widely used in robotics applications in industry and is a foundational idea for numerous researchers in the field. She was then able to transfer the insights she discovered in robotics to bioinformatics and biomedicine, where she has also made important advances. Although Kavraki is being recognized with the Athena Lecturer Award for her research contributions, she has also been a generous mentor and strong role model for younger colleagues, especially women. In this way, her career exemplifies the award’s overarching goal of celebrating and supporting women in computing.”

Kavraki’s 1996 doctoral dissertation proposed the Probabilistic Roadmap Method (PRM), a technique to plan the motion of robots, which had been an enduring challenge in the field. The Probabilistic Roadmap Method was immediately hailed for its simple implementation and its ability to scale (that is, return reliable results when applied to increasingly large datasets). PRM and the subsequent advances on the original approach are now included as a fundamental tenet of motion planning in most robotics textbooks. Additionally, to aid in the dissemination of her research, Kavraki spearheaded an open source Open Motion Planning Library. The library has been used in more than 30 different robotics systems, and continues to receive new contributions from around the world.

Kavraki was also the first to recognize that the motion-planning techniques she was developing in robotics could be applied to great effect in biology and medicine. She wrote new algorithms for the analysis of the motion, shape and flexibility of molecules that had a major impact on computational biology, as well as many subareas, including drug discovery and design. Recently, she has been developing structural methods to identify cross-reactivity hot spots in T-cells. The project has the potential to introduce safer immunotherapy treatments for cancer patients.

In another exciting project that takes her research to new heights, Kavraki has been working with NASA on Robonaut 2 (R2), a humanoid robot with formidable mechanical capability and capacity to work in human-occupied environments. It is anticipated that R2s will help humans in spaceship inspection and maintenance, caretaking tasks in future long missions, and space exploration. The variety of ways in which the robot will need to move, as well as NASA’s hopes that R2 will perform dexterous manipulation—that is, complete delicate tasks with its hands—will require leading-edge motion-planning technology. R2 was expected to be deployed at the International Space Station later in 2017.

Lydia Kavraki will formally receive the 2017-2018 ACM Athena Lecturer Award at ACM's annual Awards Banquet on June 24, 2017 in San Francisco, California.