Embedded Files
Speakers
Soheil Feizi
Associate Professor at University of Maryland, College Park
cs.umd.edu/~sfeizi
Soheil Feizi is a faculty in the Computer Science department at University of Maryland, College Park (UMD). Before joining UMD, he was a post-doctoral researcher at Stanford University. He received his Ph.D. in EECS, with a minor degree in Mathematics, at MIT. He has published over 90 peer-reviewed papers and given more than 50 invited talks. He has received multiple awards for his work including the ONR's Young Investigator Award, the NSF CAREER Award, the ARO's Early Career Program Award, two best paper awards, the Ernst Guillemin Thesis Award, a Teaching Award, and more than fifteen research awards from national agencies such as NSF, DARPA, ARL, ONR, DOE, NIST as well as industry such as Meta, IBM, Amazon, Qualcomm and Capital One. He is committed to promoting diversity in STEM and has mentored several high school, undergraduate, and graduate students through various programs. He is the organizer of the UMD's Rising Stars in Machine Learning program.
Matt Fredrikson
Associate Professor at Carnegie Mellon University
cs.cmu.edu/~mfredrik
Matt Fredirkson is an Associate Professor in Carnegie Mellon's Computer Science Department and Institute for Software Research, and is a member of CyLab and the Principles of Programming Group.
His research areas are security & privacy, fair and trustworthy artificial intelligence, and formal methods. He is currently working to understand the unique problems that can arise in data-driven systems, which often incorporate machine learning for greater automation or to aid with decision-making. Oftentimes these systems pose a risk to the privacy of end-users and data subjects, unwittingly introduce new forms of discrimination, or jeopardize safety and security in adversarial settings. His goal is to find ways to identify these issues in real, concrete systems before they cause harm, and methods to construct new ones with rigorous guarantees of safety and accountability.
Neil Zhenqiang Gong
Assistant Professor at Duke University
people.duke.edu/~zg70
Neil Zhenqiang Gong is an Assistant Professor in the Department of Electrical and Computer Engineering and Department of Computer Science (secondary appointment) at Duke University. He is broadly interested in cybersecurity and data privacy with a recent focus on the intersections between security, privacy, and machine learning. On one hand, he leverages machine learning techniques to study security and privacy. On the other hand, he builds secure and privacy-preserving machine learning. He received a B.E. from the University of Science and Technology of China (USTC) in 2010 (with the highest honor) and a Ph.D. in Computer Science from the University of California at Berkeley in 2015. During 2015-2019, he was an Assistant Professor in the Department of Electrical and Computer Engineering at Iowa State University.
Mia Hoffmann
Research Fellow at Georgetown University’s Center for Security and Emerging Technology
cset.georgetown.edu/staff/mia-hoffmann
Mia Hoffmann is a Research Fellow at Georgetown’s Center for Security and Emerging Technology (CSET), focusing on AI assessment and governance. Prior to joining CSET, she worked at the European Commission and as a researcher in Brussels, where she studied AI adoption in the economy and its implications for workers and the labor market. Mia holds a M.Sc. in Economics from Lund University in Sweden and a B.Sc. in International Economics from the University of Tuebingen in Germany.
Hima Lakkaraju
Assistant Professor at Harvard University
himalakkaraju.github.io
Hima is Lakkaraju an Assistant Professor at Harvard University with appointments in the Business School and the Department of Computer Science. Prior to her stint at Harvard, she received my PhD in Computer Science from Stanford University.
Her research interests lie within the broad area of trustworthy machine learning. More specifically, she focuses on improving the interpretability, fairness, robustness, and reasoning capabilities of different kinds of ML models including language models and other large pre-trained models.
She leads the AI4LIFE research group at Harvard and recently co-founded the Trustworthy ML Initiative (TrustML) to help lower entry barriers into trustworthy ML and bring together researchers and practitioners working in the field. Her research is being generously supported by NSF, Google, Amazon, JP Morgan, Adobe, Bayer, Harvard Data Science Initiative, and D^3 Insitute at Harvard. Her work has been featured in various major media outlets including the New York Times, TIME magazine, Fortune, Forbes, MIT Technology Review, and Harvard Business Review.
Jonathan Katz
Professor at University of Maryland, College Park
cs.umd.edu/~jkatz
Jonathan Katz is a professor in the Department of Computer Science and a core faculty member in the Maryland Cybersecurity Center with an appointment in the University of Maryland Institute for Advanced Computer Studies. He is also a Fellow of the Joint Center for Quantum Information and Computer Science.
Katz research interests include cryptography, computer and network security and theoretical computer science.
He is a recipient of the Humboldt Research Award, the ACM SIGSAC Outstanding Contribution Award, a University of Maryland Distinguished Teacher-Scholar Award, an NSF CAREER award and more. Katz is also a Fellow of the International Association for Cryptologic Research (IACR). He co-authored the textbook "Introduction to Modern Crytography" and a monograph on digital signature schemes.
Katz has held visiting appointments at UCLA, the École normale supérieure in Paris, France, and IBM in Hawthorne, NY.
He received his doctorate in computer science from Columbia University.
Zico Kolter
Associate Professor, Carnegie Mellon University
zicokolter.com
I am an Associate Professor in the Computer Science Department with the School of Computer Science at Carnegie Mellon University. In addition to my full-time role at CMU, I also serve as Chief Scientist of AI Research for the Bosch Center for AI (BCAI), working in the Pittsburgh Office. BCAI also generously provides funding for much of the research in my group.
My group’s work focuses on machine learning, optimization, and control. Specifically, much of our work aims at making deep learning algorithms safer, more robust, and more explainable; to these ends, we have worked on methods for training provably robust deep learning systems, and including more complex “modules” (such as optimization solvers) within the loop of deep architectures. We also focus on several application domains, with a particular focus on applications in smart energy and sustainability domains.
Emelia Probasco
Senior Fellow at Georgetown’s Center for Security and Emerging Technology (CSET)
cset.georgetown.edu/staff/emelia-probasco
Emelia (Emmy) Probasco is a Senior Fellow at Georgetown’s Center for Security and Emerging Technology (CSET), where she works on the military applications of Artificial Intelligence. Prior to joining CSET, she was the Chief Communications Officer and Communications Department Head at the Johns Hopkins Applied Physics Laboratory (APL), leading technical and institutional communications to support and drive APL’s strategic vision. Prior to APL, Emmy served as a Surface Warfare Officer in the U.S. Navy, deploying twice to the Indo-Pacific. She also served in the Pentagon as the speechwriter to the Chief of Naval Operations and at the U.S. Naval Academy as an instructor in political science. She has masters’ degrees in Forced Migration and Economic and Social History from Oxford University, where she studied as a Rhodes Scholar, and a degree in Political Science from the U.S. Naval Academy.
Matt Turek
Deputy Director at DARPA’s Information Innovation Office (I2O)
darpa.mil/staff/dr-matt-turek
Dr. Matt Turek is the deputy office director for the Defense Advanced Research Agency’s (DARPA) Information Innovation Office (I2O), where he provides technical leadership and works with program managers to envision, create, and transition capabilities that ensure enduring information advantage for the United States and its allies. Previously, Turek served as I2O’s acting deputy director and as a program manager for AI-related programs, including Explainable AI, Machine Common Sense, Media Forensics, and Semantic Forensics. He joined DARPA from Kitware, Inc., where he led a team developing computer vision technologies. Prior to that role, he was at GE Global Research conducting research in medical imaging and industrial inspection.
Apostol Vassilev
Research Supervisor at NIST's Computer Security Division
nist.gov/people/apostol-vassilev
Apostol Vassilev is a Research Supervisor in the Computer Security Division at NIST. His team’s research agenda convers a range of topics in Trustworthy AI and Cybersecurity, including Adversarial Machine Learning (AML), AI bias, meta learning with large language models (LLMs), Multi-Party Threshold Cryptography, novel approaches to cybersecurity testing and measurement through automated machine-based methodologies.
Apostol Vassilev works closely with academia, industry and government agencies on the development and adoption of standards in Artificial Intelligence and Cybersecurity and contributes to national and international standards groups. He is a guest co-editor to the upcoming IEEE Transactions on AI – Special Issue on Responsible AI Engineering. Apostol is a frequent speaker at international conferences and a keynote speaker to many events. Dr. Vassilev holds a Ph.D. in Mathematics from Texas A&M University. He has authored over fifty scientific papers and holds five US patents.
Page updated
Google Sites
Report abuse