DAVE BAGGETT is the CEO and founder of INKY. Prior to INKY, Mr. Baggett was co-founder and chief operating officer of travel search provider ITA Software and oversaw software development, operations, and customer relations, expanding the company to 500 employees. Google acquired ITA for $700 million in 2011. Mr. Baggett has a B.S./B.A. in computer science and linguistics from the University of Maryland, College Park (UMCP), and a S.M. in computer science from the Massachusetts Institute of Technology (MIT). He is a trustee of the University of Maryland College Park Foundation and a member of the UMCP Computer, Math and Natural Sciences Board of visitors and chair of its Entrepreneurship Task Force.
DAVID BRUMLEY is the CEO and co-founder of ForAllSecure, and a professor at Carnegie Mellon University (CMU) in electrical and computer engineering and computer science. ForAllSecure’s mission is to make the world’s software safe, and it develops automated techniques to find and repair exploitable bugs to make this happen. Professor Brumley previously was the director of CyLab, the CMU Security and Privacy Institute. His honors include a U.S. Presidential Early Career Award for Scientists and Engineers from President Obama, a 2013 Sloan Foundation award, and numerous best paper awards. Professor Brumley is also advisor and a founding member of PPP, one of the world’s most elite competitive hacking teams.
WYATT HOFFMAN is a senior research analyst with the Nuclear Policy Program and the Cyber Policy Initiative at the Carnegie Endowment for International Peace. His research focuses on private-sector cyber capabilities, emerging technologies, and the intersection of nuclear weapons and cybersecurity. He is a graduate of Carnegie’s James C. Gaither Junior Fellows Program and was a Rotary Global Grant Scholar in Peace and Conflict Prevention and Resolution at King’s College London’s Department of War Studies.
ALEX KANTCHELIAN obtained his Ph.D. in computer science from the University of California, Berkeley, in 2016. His research explores the space of machine learning for security applications and its dual, the security of machine learning itself. His work has appeared in NIPS, ICML, CCS, and DIMVA, and he has been a program committee member for the Artificial Intelligence and Security Workshop since 2014. Dr. Kantchelian is presently a software engineer at Google where he develops machine learning-based detection systems for security.
ZICO KOLTER is an assistant professor in the Computer Science Department at CMU and also serves as chief scientist of artificial intelligence (AI) research for the Bosch Center for Artificial Intelligence. His work focuses on the intersection of machine learning and optimization, with a large focus on developing more robust, explainable, and rigorous methods in deep learning. In addition, he has worked in a number of application areas, highlighted by work on sustainability and smart energy systems. He is the recipient of the Defense Advanced Research Projects Agency Young Faculty Award and best paper awards at KDD, PESGM, and IJCAI.
SVEN KRASSER currently serves as chief scientist at CrowdStrike where he leads the machine learning efforts utilizing CrowdStrike’s Big Data information security platform. He has productized machine learning-based systems for over a decade and most recently led the research and development (R&D) of the first fully machine learning-based anti-malware engine featured on VirusTotal. Dr. Krasser has authored numerous peer-reviewed publications and is co-inventor of more than 30 patented network and host security technologies.
BO LI is an assistant professor in the department of Computer Science at University of Illinois, Urbana-Champaign, and is a recipient of the Symantec Research Labs fellowship. Previously she was a postdoctoral researcher at the University of California, Berkeley. Her research focuses on both theoretical and practical aspects of security, machine learning, privacy, game theory, and adversarial machine learning. She has designed several robust learning algorithms, a scalable framework for achieving robustness for a range of learning methods, and a privacy-preserving data publishing system. Her recent research focuses on adversarial deep learning and generative models, as well as designing scalable robust machine learning models against adversarial attacks.
DAVID R. MARTINEZ is associate head in the Cyber Security and Information Sciences Division at MIT Lincoln Laboratory. In this capacity, he is focusing on the strategic and innovative directions of the division in the areas of artificial intelligence for cybersecurity, cyber resilient systems, big data analytics, and secure cloud computing. He is also a member of MIT Lincoln Laboratory’s steering committee and recently served as the laboratory’s chief information officer. Mr. Martinez, who joined MIT Lincoln Laboratory in 1988, has served in various management positions. During 1993-1999, he held leadership roles in the Embedded Digital Systems Group. He served as associate head (1999-2004) and head (2004-2010) of the Intelligence, Surveillance, and Reconnaissance (ISR) Systems and Technology Division. As head of the ISR Systems and Technology Division, he had direct line management responsibility for the division’s programs in the development of advanced techniques and prototypes. Mr. Martinez was responsible for more than $140 million in total R&D budget and total personnel of 330+ people. Prior to joining the laboratory, he was employed as a principal research engineer at ARCO Oil and Gas Company, specializing in adaptive seismic signal processing. He received the ARCO special achievement award for his work on the 1986 Cuyama Project, which provided a superior, cost-effective approach to three-dimensional seismic surveys. He holds three U.S. patents based on his work in signal processing for seismic applications. He served as the president and chairman of the board of directors at Mercury Federal Systems during 2010-2011. In that role, he was responsible for the company’s operations and strategic directions. He returned to the laboratory as a principal researcher in the Communication Systems and Cyber Security Division before accepting the appointment to the newly formed Cyber Security and Information Sciences Division. From 1999 to 2004, Mr. Martinez served on the Army Science Board. In 2007-2008, he served on the Defense Science Board ISR Task Force. He founded the High Performance Embedded Computing Workshop in 1997, which in 2012 became an Institute of Electrical and Electronics Engineers (IEEE) conference. He has been the keynote speaker at both national and international conferences. He has served as an associate editor of the IEEE Signal Processing magazine, and co-authored/co-edited the book titled High Performance Embedded Computing Handbook: A Systems Perspective (2008). In 2003, he was elected IEEE fellow “for technical leadership in the development of high performance embedded computing for real-time defense systems.” Most recently, he founded and chaired the Artificial Intelligence for Cyber Security workshop. He was awarded the Eminent Engineer Award from the College of Engineering at New Mexico State University (NMSU), and was elected to the NMSU Klipsch Electrical and Computer Engineering Academy. He is a member of the NMSU dean’s advisory council in engineering, and the Florida International University School of
Computing and Information Sciences advisory board. Mr. Martinez was awarded a bachelor’s degree from NMSU, an M.S. degree from MIT, and the E.E. degree jointly from MIT and the Woods Hole Oceanographic Institution. He completed an M.B.A. from the Southern Methodist University.
TYLER MOORE is an associate professor of computer science at the University of Tulsa, where he holds the Tandy Chair of Cyber Security and Information Assurance. His research focuses on security economics, cybercrime measurement, and cybersecurity policy. Dr. Moore serves as director of StopBadware, a nonprofit anti-malware organization. He is a founding editor-in-chief of the Journal of Cybersecurity, a new interdisciplinary journal published by Oxford University Press. He was a 2016-2017 New America Cybersecurity fellow. Prior to joining the University of Tulsa, he was a postdoctoral fellow at the Center for Research on Computation and Society at Harvard University, the Hess Visiting Assistant Professor of Computer Science at Wellesley College, and an assistant professor at Southern Methodist University. A British Marshall Scholar, Dr. Moore completed his Ph.D. at the University of Cambridge, and he holds B.S. degrees in computer science and applied mathematics from the University of Tulsa.
VINH X. NGUYEN is the national intelligence officer for cyber issues at the National Intelligence Council in the Office of the Director of National Intelligence. Mr. Nguyen leads the Intelligence Community mid- and long-term strategic analysis to support and advance the cyber mission. He serves as the subject-matter expert and advises the Director of National Intelligence (DNI) on cyber issues in support of the DNI’s role as the principal intelligence adviser to the president. Recruited by National Security Agency (NSA) through the Stokes Program, Mr. Nguyen received the dual degrees in psychology and computer science from the University of Pennsylvania. He earned his M.A. in international science and technology policy at George Washington University’s Elliott School of International Affairs, where he focused his work on defense innovation policies and processes. He was trained on positive executive leadership at the University of Michigan’s Ross School of Business. Mr. Nguyen was responsible for leading and integrating the enterprise-wide cryptologic mission to detect and assess the cybersecurity threats from the Asia-Pacific areas at NSA. He has served in many key analytic and technical positions in the network security, information operations, and counterterrorism areas at NSA. He was instrumental in developing and prototyping cyber attribution methods, leading joint operations against key adversaries, and analyzing terrorist use of the Internet. Mr. Nguyen was a recipient of the DNI’s Exceptional Accomplishment Award (2017), NSA’s Senior Special Achievement Award (2015), the DNI’s Presidential Daily Briefing Pin (2013), the Meritorious Civilian Service Award (2010), the Sparky Baird Award for the best contributed article published in the SIGNAL magazine (2007), and the Distinguished Young AFCEAN of the Year Award (2006-2007). He joined the Defense Intelligence Senior Level ranks in 2014.
UNA-MAY O’REILLY is the leader of Anyscale Learning For All (ALFA) Group at MIT’s Computer Science and Artificial Intelligence Laboratory, focusing on scalable machine learning, evolutionary algorithms, and frameworks for large-scale knowledge mining, prediction, and analytics. ALFA conducts research in artificial adversarial intelligence- related to cybersecurity, MOOC data analytics, and data-driven medical modeling. Dr. O’Reilly has expertise in agile data science systems with rapid intelligent data analytics capabilities. These systems span organization and visualization of raw data, through to machine learning inference. Dr. O’Reilly received the EvoStar Award for Outstanding Achievements in Evolutionary Computation in Europe in 2013. She is recognized by Association for Computing Machinery (ACM) Special Interest Group on Genetic and Evolutionary Computation (SIG-EVO) for her significant contributions having been elected a fellow of ISGEC, serves as vice-chair of ACM SIG-EVO, and has served as chair of the Genetic and Evolutionary Computation Conference (GECCO). She has served on the GECCO business committee, co-led the 2006 and 2009 Genetic Programming: Theory to Practice Workshops, and co-chaired EuroGP, the largest conference devoted to genetic programming. In 2013, Dr. O’Reilly co-inaugurated the Women in Evolutionary Computation group at GECCO. She is an area editor for data analytics and knowledge discovery for Genetic Programming and Evolvable Machines (Kluwer), editor for Evolutionary Computation (MIT Press), and action editor for the Journal of Machine Learning Research. She serves in an advisory role on the Oak Ridge National Laboratory Directorate Advisory Committee.
NICOLAS PAPERNOT is a research scientist at Google Brain working on the security and privacy of machine learning. He will join the University of Toronto and Vector Institute as an assistant professor and Canada CIFAR Artificial Intelligence Chair in fall 2019. He earned his Ph.D. in computer science and engineering at the Pennsylvania State University, working with Professor Patrick McDaniel and supported by a Google Ph.D. fellowship in security and privacy. Dr. Papernot received a best paper award at the International Conference on Learning Representations in 2017. He is also the co-author of CleverHans, an open-source library widely adopted in the technical community to benchmark machine learning in adversarial settings, and tf.Privacy, an open-source library for training differentially private models with TensorFlow. He serves on the program committees of several conferences including ACM CCS, IEEE S&P, and USENIX Security. In 2016, he received his M.S. in computer science and engineering from the Pennsylvania State University and his M.S. in engineering sciences from the Ecole Centrale de Lyon.
DELIP RAO is the vice president of research at AI Foundation where he leads speech, language, and vision research efforts for generating and detecting artificial content. Prior to this, he founded Joostware, an AI research consulting company, and in 2016, The Fake News Challenge, an initiative to bring AI researchers across the world to work on fact-checking related problems. Mr. Rao is the author of a recent book on Deep Learning and Natural Language Processing. Previously, he was a summer researcher at Google, the first machine learning researcher on the Twitter antispam team, and an early researcher at Amazon Alexa team. He is a graduate from the Center for Language and Speech Processing and Human Language Technology Center of Excellence at Johns Hopkins University.
JAY STOKES works in the Cloud and Infrastructure Security Group in Microsoft Research, and his primary area of interest is using machine learning, AI, and signal processing for computer security. He is particularly interested in understanding how deep learning can improve computer security.
YEVGENIY VOROBEYCHIK is an associate professor of computer science and engineering at Washington University in Saint Louis. Previously, he was an assistant professor of computer science and biomedical informatics at Vanderbilt University. His work focuses on game-theoretic modeling of security and privacy, adversarial machine learning, algorithmic and behavioral game theory and incentive design, optimization, and network science. Dr. Vorobeychik received an National Science Foundation CAREER award in 2017 and was invited to give an International Joint Conferences on Artificial Intelligence 2016 early career spotlight talk. He also received several best paper awards, including one of 2017 Best Papers in Health Informatics. He was nominated for the 2008 ACM Doctoral Dissertation Award and received honorable mention for the 2008 International Foundation for Autonomous Agents and Multiagent Systems Distinguished Dissertation Award.