2024 Keynotes
Lisa Einstein serves as the Cybersecurity and Infrastructure Security Agency’s first Chief AI Officer. In this role, she leads CISA’s efforts to responsibly adopt AI tools that can help advance the agency’s mission and works to identify and mitigate risks to U.S. critical infrastructure associated with AI. Einstein previously served as Senior Advisor for AI at CISA and as Executive Director of CISA’s Cybersecurity Advisory Committee. In her previous roles, she led the development and implementation of CISA’s AI Roadmap, an actionable plan to promote beneficial uses of AI to enhance CISA’s cybersecurity capabilities, ensure AI systems are protected from cybersecurity threats, and mitigate the risks malicious uses of AI pose for critical infrastructure.
Outside of work, Einstein is a part-time research advisor in the Stanford Intelligent Systems Laboratory. She was Stanford’s first dual master’s degree recipient in computer science (artificial intelligence concentration) and international policy (cyber policy and security concentration). While at Stanford, she led Lt. Gen. (ret) H.R. McMaster’s research team on emerging technologies and geopolitics and conducted AI research, including co-developing the first AI speech recognition models for three West African languages spoken by 10 million people in seven countries. During the COVID-19 pandemic, she helped to organize a massively-scaled free virtual class that taught introductory coding skills to 22,000 students from 148 countries by mobilizing 2000 volunteer teaching assistants.
As a Peace Corps Volunteer in Guinea, Lisa taught physics to over 600 students in a rural village and worked with some of her students to co-found a local NGO that promotes girls’ education and combats early marriage and gender-based violence. She received her BA from Princeton in physics and dance and danced professionally for several years, including with Camille A. Brown and Dancers.
Joshua Saxe leads Meta's efforts to integrate security into its large language models (LLMs) and protect them from application-level cyberattacks. Before joining Meta, he served as chief scientist at Sophos, principal investigator on multiple DARPA programs at Invincea Labs, and led machine learning security research at Applied Minds. Joshua co-authored the book "Malware Data Science" with Hillary Sanders, published by No Starch Press. He has authored dozens of scientific papers and patents on security AI and has presented at numerous conferences, including Defcon, Blackhat and RSA.
Ram Shankar Siva Kumar is a Data Cowboy working on the intersection of machine learning and security. At Microsoft, he founded the AI Red Team, bringing together an interdisciplinary group of researchers and engineers to proactively attack AI systems and defend from attacks.
His recent book on attacking AI systems, NOT WITH A BUG has been called “Essential Reading” by Microsoft’s Chief Technology Officer and received wide praise from industry leaders at DeepMind, OpenAI as well as policy makers and academia. He is donating his proceeds of the book royalty to Black In AI.
His work on AI and Security has appeared in industry conferences like RSA, BlackHat, Defcon, BlueHat, DerbyCon, MIRCon, Infiltrate, academic workshops at NeurIPS, ICLR, ICML, IEEE S&P, ACM - CCS. His work has been covered by Bloomberg, VentureBeat, Wired, and Geekwire. He founded the Adversarial ML Threat Matrix, an ATT&CK style framework enumerating threats to machine learning. His work on adversarial machine learning appeared notably in the National Security Commission on Artificial Intelligence (NSCAI) Final report presented to the United States Congress and the President.
He is currently Tech Policy Fellow at UC Berekeley and an affiliate at the Berkman Klein Center for Internet and Society at Harvard University, where he is broadly investigating two questions: How do we assess the safety of ML systems? What are the policy and legal ramifications of AI, in the context of security? He is also Technical Advisory Board Member at the University of Washington.
2023 Keynotes
Tom Goldstein is the Volpi-Cupal Associate Professor of Computer Science at the University of Maryland, and director of the Maryland Center for Machine Learning. His research lies at the intersection of machine learning and optimization, and targets applications in computer vision and signal processing. Professor Goldstein has been the recipient of several awards, including SIAM’s DiPrima Prize, a DARPA Young Faculty Award, a JP Morgan Faculty award, an Amazon Research Award, and a Sloan Fellowship.
Shawn Richardson is the Director of Cyber Defense Operations at NVIDIA, leading the product security operations center and incident response teams. She has spent most of her 20+ year career in product security and incident response roles at companies like Microsoft, Palo Alto Networks and Amazon. She served as a board member for FIRST.org, an international organization that brings together incident response and security teams from countries across the world to ensure a safe internet for all, and currently participates in the several industry special interest groups.
2022 Keynotes
Amanda Rousseau absolutely loves taking apart malware. She currently works on the Microsoft Offensive Research & Security Engineering (MORSE) team to help find vulnerabilities in the Windows OS. Previously, she worked as an Offensive Security Engineer on the Red Team at Facebook, Malware Researcher at Endgame, FireEye, and the U.S. Department of Defense Cyber Crime Center. Amanda received a MS in Information Systems Engineering from Johns Hopkins University. Her research interests include malware evasion techniques, rootkits, dynamic behavior classification, and developing runtime kernel detections. You can find Amanda on Twitter at @malwareunicorn.
Dr. Mikel D. Rodriguez is the director of The Artificial Intelligence and Autonomy Innovation Center at MITRE labs and leads the AI Red Team for the Department of Defense. Being part of a not-for-profit in the public interest Dr. Rodriguez works with a team that can look beyond the bottom line of any particular product or organization and focus harnessing AI to help address national and global challenges. For the past twenty years his research has focused on exploring how artificial intelligence and in particular Computer Vision can be used to help solve problems for a safer world. He obtained his PhD at UCF's Center for Research in Computer Vision. He was a visiting researcher at the Robotics Institute at Carnegie Mellon and a post-doctoral fellow at INRIA at the Département d'Informatique of Ecole Normale Supérieure in Paris, France. Dr. Rodriguez is the editor of the ACM Journal for Responsible Computing. Dr. Rodriguez was the chair of the ODNI Video Analytics Research Working Group and is a senior technical advisor for the Pentagon's Project MAVEN. He has served in the program committee for IEEE Computer Vision and Pattern Recognition, IEEE International Conference on Computer Vision, and IEEE Transactions on Pattern Analysis and Machine Intelligence.
2021 Keynotes
Katie Nickels is the Director of Intelligence for Red Canary as well as a SANS Certified Instructor for FOR578: Cyber Threat Intelligence and a non-resident Senior Fellow for the Atlantic Council’s Cyber Statecraft Initiative. She has worked on cyber threat intelligence (CTI), network defense, and incident response for over a decade for the U.S. DoD, MITRE, Raytheon, and ManTech. Katie hails from a liberal arts background with degrees from Smith College and Georgetown University, embracing the power of applying liberal arts prowess to cybersecurity. Katie has shared her expertise with presentations, webcasts, podcasts, and blog posts, including a presentation at Black Hat as well as her personal blog, “Katie’s Five Cents." Katie has also served as a co-chair of the SANS CTI Summit and FIRST CTI Symposium. She was a 2020 recipient of the SANS Difference Maker Award and the 2018 recipient of the President's Award from the Women's Society of Cyberjutsu. She also serves as the Program Manager for the Cyberjutsu Girls Academy, which seeks to inspire young women to learn more about STEM. You can find Katie on Twitter @LiketheCoins.
Nicolas Papernot is an Assistant Professor in the Department of Electrical and Computer Engineering and the Department of Computer Science at the University of Toronto, and a faculty member at the Vector Institute where he holds a Canada CIFAR AI Chair, and a faculty affiliate at the Schwartz Reisman Institute.
His research interests are at the intersection of security, privacy, and machine learning. A sample of his research includes cleverhans.io which he co-authored, and research in proof-of-learning, collaborative learning beyond federation, dataset inference, machine unlearning, differentially private ML, and adversarial examples.
Prof. Papernot earned a Ph.D. in Computer Science and Engineering at the Pennsylvania State University, working with Prof. Patrick McDaniel and was supported by a Google PhD Fellowship. Upon graduating, he spent a year at Google Brain in Úlfar Erlingsson's group.
2019 Keynotes
Dr. Aleatha Parker-Wood is the Machine Learning and Algorithmic Privacy lead at Humu, a company dedicated to making work better for everyone everywhere. Prior to Humu, she was a Sr. Principal Research Engineer and manager in the Center for Advanced Machine Learning at Symantec, where her team did original research and contributed machine learning to numerous Symantec products including SEP 14, Email Security.cloud, Norton Core, phishing page detection, and more. She holds multiple security-related patents, and serves on the steering committee for ScAINet, the SeCurity AI Networking conference. She received her Ph.D. in Computer Science from the University of California, Santa Cruz.
Nicholas Carlini is a research scientist at Google Brain. He analyzes the security and privacy of machine learning, for which he has received best paper awards at IEEE S&P and ICML. He graduated with his PhD from the the University of California, Berkeley in 2018.
2018 Keynotes
Maya Gupta is a Principal Scientist at Google where she leads the Glassbox Machine Learning R&D team that focuses, among other things, on end-to-end machine learning interpretability and trusting machine learning classifiers. Prior to Google, Maya was an Associate Professor of Electrical Engineering at the University of Washington in Seattle. There, she received numerous awards, including the presidential early career award for scientists and engineers and the Office of Naval Research Young Investigator Award. She received her PhD in Electrical Engineering at Stanford under the direction of Robert Gray, and joint degrees in Electrical Engineering and Economics from Rice University. She is also the CEO of the wooden jigsaw puzzle company Artifact Puzzles.
Alexander Kott serves as the chief of the Network Science Division of the Army Research Laboratory headquartered in Adelphi, MD. In this position, he is responsible for fundamental research and applied development in performance and security of both tactical mobile and strategic networks. He oversees projects in network performance and security, intrusion detection, and network emulation. Between 2003 and 2008, Dr. Kott served as a Defense Advanced Research Projects Agency (DARPA) program manager responsible for a number of large-scale advanced technology research programs. His earlier positions included technical director of BBN Technologies, Cambridge, MA; director of R&D at Logica Carnegie Group, Pittsburgh, PA; and IT research department manager at AlliedSignal, Inc., Morristown, NJ. Dr. Kott received the Secretary of Defense Exceptional Public Service Award and accompanying Exceptional Public Service Medal, in October 2008. He earned his Ph.D. from the University of Pittsburgh, Pittsburgh, PA, in 1989, published over 70 technical papers, and co-authored and edited six technical books.