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2018 USENIX Security and AI Networking Conference

May 11, 2018
Atlanta, GA, USA

The 2018 USENIX Security and AI Networking Conference (ScAINet ’18) will take place on Friday, May 11, 2018, at the Georgia Tech Hotel and Conference Center in Atlanta, GA, USA.

Recent developments in AI have created new challenges and opportunities for security. The Security and AI Networking conference (ScAInet) will bring together a diverse cross-section of security and ML, including researchers and engineers from academia and industry. Our goal is to explore the rich frontier at the intersection of artificial intelligence, machine learning, and cybersecurity. This will be a one-day, vendor-neutral event, with a focus on community building, networking, and cross-pollination between industry and academia. Presented topics will include:

  • Advances in AI/ML techniques
  • AI/ML applications to cybersecurity
  • Existing state-of-the-art approaches to security problems

The program (available soon) will consist of a single track of invited talks and will conclude with a panel session.

Registration Information

The registration fee for ScAINet '18 is $250.

Questions? Contact

Invited Speakers

David Freeman
Research Scientist/Engineer, Facebook

David Freeman is a research scientist/engineer at Facebook working on integrity and abuse problems. He previously led anti-abuse engineering and data science teams at LinkedIn, where he built statistical models to detect fraud and abuse and worked with the larger machine learning community at LinkedIn to build scalable modeling and scoring infrastructure. He has published numerous academic papers on aspects of computer security and recently co-authored a book on Machine Learning and Security, published by O'Reilly. He holds a Ph.D. in mathematics from UC Berkeley and did postdoctoral research in cryptography and security at CWI and Stanford University.

Jason Polakis
Assistant Professor, Computer Science Department, University of Illinois at Chicago

Jason Polakis is an Assistant Professor at the University of Illinois at Chicago. 
He is broadly interested in identifying the security and privacy limitations of Internet technologies, designing robust defenses and privacy-preserving mechanisms, and enhancing our understanding of the online ecosystem and its threats. 
His research has revealed significant flaws in popular services, and major vendors like Facebook have adopted his proposed defenses. His work has resulted in multiple publications at top tier security and computer science conferences.

Tummalapalli Sudhamsh Reddy
Senior Data Scientist, Kayak

Dr. Tummalapalli Sudhamsh Reddy is a senior data Scientist at Kayak Software Corp, which is one of the leading travel metasearch engines in the world. Amongst his many roles at Kayak, Sudhamsh is responsible for the bot detection and search results ranking. Before joining Kayak, Sudhamsh developed fraud detection models for detecting credit card fraud at ACI Worldwide Inc. He has previously been a guest scientist at Fermi National Accelerator Lab and Brookhaven National Lab.

Dr. Reddy obtained his M.S and Ph.D. in Computer Science from the University of Texas at Arlington.

Brendan Saltaformaggio
Assistant Professor, School of Electrical Computer Engineering, Georgia Institute of Technology

Dr. Brendan Saltaformaggio is an Assistant Professor in the School of Electrical and Computer Engineering at Georgia Tech. He is the Director of the Cyber Forensics Innovation (CyFI) Laboratory, whose mission is to further the investigation of advanced cyber crimes and the analysis and prevention of next-generation malware attacks, particularly in mobile and IoT environments. This research has led to numerous publications at top cyber security venues, including a Best Student Paper Award from the 2014 USENIX Security Symposium.

Le Song
Associate Director, Center for Machine Learning, Georgia Institute of Technology, and Alibaba

Le Song obtained his B.S. degree in computer science from the South China University of Technology, Guangzhou, China in 2002. After that, he received his Master's degree in 2004, and Ph.D. degree in 2008 both in computer science from the University of Sydney, Australia. Le was also a Ph.D. student with the Statistical Machine Learning Program at NICTA, and his thesis advisor was Alex Smola. Since Summer 2008, Le was a postdoc fellow at Carnegie Mellon University, working on machine learning and computational biology projects with Eric Xing, Carlos Guestrin, Geoff Gordon and Jeff Schneider. Right before he joined Georgia Tech, he spent some time as a research scientist at Fernando Pereira's group at Google Research.


Georgia Tech Hotel and Conference Center
800 Spring St. NW
Atlanta, GA, 30308
+1 404.347.9440

Hotel Reservation Deadline: Monday, April 10, 2018

USENIX has negotiated a special room rate of $189 for conference attendees. Book your room online or call +1 800.706.2899 or +1 404.838.2100 and mention USENIX or ScAINet '18.


Overnight parking is $15 per night. For unlimited in-and-out access to the garage, an $18 pass is available.

Georgia Tech Hotel and Conference Center


Registration: or +1 510.528.8649
Membership: or +1 510.528.8649
Sponsorship: or +1 510.528.8649 x17
Student Grants: or +1 510.528.8649

Conference Organizing Committee

Duen Horng (Polo) Chau
Georgia Institute of Technology

Duen Horng (Polo) Chau is an Assistant Professor at Georgia Tech, in the School of Computational Science and Engineering. He co-directs the MS Analytics program. His research bridges data mining and human-computer interaction (HCI) to create scalable interactive tools for making sense of massive datasets and solving real world problems. His Ph.D. in Machine Learning from Carnegie Mellon University won CMU's Computer Science Dissertation Award, Honorable Mention.

He received faculty awards from Google, Yahoo, LexisNexis; Raytheon Faculty Fellowship; Edenfield Faculty Fellowship; Outstanding Junior Faculty Award; Symantec fellowship (twice); Best Student Paper Awards at SDM’14 and KDD’16 (runner-up). He published over 100 refereed articles.

He is a steering committee member of ACM IUI conference, IUI’15 co-chair, and IUI’19 program co-chair.

His research led to deployed technologies by Facebook, Symantec (protects 120M people from malware), and Atlanta Fire Rescue Department; he holds 3 patents. His security and fraud detection research made headlines.

Andrew Gardner

Andrew Gardner founded and leads the Center for Advanced Machine Learning (CAML) at Symantec, where his team conducts research and development in core machine learning, deep learning and other techniques.

His career spans over 20 years across enterprise, clinical and academic settings. Past roles range from software architect to machine learning consultant to chief data scientist. Gardner is an active researcher with more than 20 peer-reviewed papers and a dozen filed patents. He teaches a graduate course in machine learning annually at the Georgia Institute of Technology, and frequently presents technical topics around the country.

Gardner received degrees in electrical engineering from the University of Tennessee–Knoxville (BSEE), and the Georgia Institute of Technology (MSEE and Ph.D.)

Anisha Mazumder

Anisha Mazumder is an Applied Machine Learning Engineer at Microsoft working on developing machine learning models for detection of security threats in Azure. Her interests lie in application of state-of-the-art machine learning solutions powered up to the industry scale to solve the most interesting and pressing problems. She completed her Bachelors' degree from Jadavpur University, India in 2012 and her PhD degree from Arizona State University in 2016. Her dissertation focused on application of algorithms, machine learning and graph theory to solve optimization problems in different types of networks such as social networks, storage networks among others.

Alina Oprea
Northeastern University

Alina Oprea is an Associate Professor at Northeastern University’s College of Computer and Information Science since August 2016. Alina is interested in extracting meaningful intelligence from different data sources for various security applications, designing resilient machine learning techniques for applications in different domains, and understanding the challenges of securing machine learning against advanced attacks. Prior to her position at Northeastern, Alina was a consultant research scientist at RSA Laboratories. Alina received a BS in mathematics and computer science from the University of Bucharest in Romania and M.Sc. and Ph.D. degrees in computer science from Carnegie Mellon University in 2003 and 2007, respectively. She is currently an associate editor for the ACM Transactions on Privacy and Security (TOPS) journal and co-chair of the Network and Distributed System Security (NDSS ) conference in 2018. She is the recipient of the Best Paper Awards at the 2005 NDSS Conference and 2017 AISEC Conference. In 2011 Alina received the Technology Review TR35 award for her research in cloud security.

Aleatha Parker-Wood

Aleatha Parker-Wood is a researcher/manager in the Center for Advanced Machine Learning at Symantec, and leads a research team focused on protecting users and their data through advanced machine learning. She received a Ph.D. in Computer Science from University of California, Santa Cruz for her work on scientific data management. Her work currently focuses on differential privacy for ML and using deep learning for code analysis, with previous work in file system search, forensics, and AI for Go. She has authored several books and articles as well as numerous patent filings, and most recently served as research co-chair of MSST 2017.

Nikolaos Vasiloglou
Georgia Institute of Technology

Nikolaos Vasiloglou holds a PhD from the department of Electrical and Computer Engineering at Georgia Institute of Technology. His thesis was focused on scalable machine learning over massive datasets. After graduating from Georgia Tech he founded Analytics1305 LLC and Ismion Inc. He has architected and developed the PaperBoat machine learning library which has been successfully integrated and used in the LogicBlox and HPCCSystems platforms. He has also served as a machine learning consultant for Predictix, Revolution Analytics, Damballa, Tapad and LexisNexis.  He is currently a technical director at Symantec Center for Advanced Machine Learning. Nikolaos Vasiloglou teaches at the Executive Education and Computational Science and Engineering programs at Georgia Tech. He is also involved in the organization of the UAI conference and MLTrain workshops.

Founding Sponsor


USENIX welcomes corporate sponsorship of our events. Your sponsorship exposes your brand to highly qualified and targeted attendees, funds our grant award program, supports the USENIX open access policy, and keeps USENIX conferences affordable.

For details on how you can help, please contact the Sponsorship Department via email or call +1 510.528.8649.