Leadership Team
Gavin Klondike |
Position: Workshops Lead
Bio: Gavin Klondike (GTKlondike) is a senior security consultant and researcher specializing in network security and penetration testing. He is the founder of NetSec Explained, a blog and YouTube channel, where he shares intermediate to advanced level network security topics in an easy-to-understand way. As a consultant, he has honed his skills both offensively and defensively, giving him a unique perspective on how to best secure an organization’s most critical assets. Gavin is dedicated to sharing his knowledge with the next generation of cybersecurity professionals to help them level up their skills. His current research focus is in finding ways to address the cybersecurity skills gap, by utilizing AI/ML to augment the capabilities of current security resources. |
Lauren Putvin |
Position: Steering Committee Lead
Bio: Lauren Putvin began her security journey as a data scientist in GRC creating data driven security metrics and policy changes. She has most recently worked in security product development at various companies. She has a PhD in biomedical engineering (classifying sensor data). |
Ravin Kumar |
Position: Steering Committee Member
Affiliation: Google Expertise: Applied Generative Modeling Bio: Ravin is security minded statistician and/or data scientist. His focus in applied generative modeling. Previously he worked at SpaceX and Sweetgreen using Bayesian Statistics to assess and improve orbital rocket launches and optimize avocado preparation (among many other ingredients). He now works at Google on large scale generative models, with a focus on safety and security. He has a masters in Manufacturing Engineering from University of Wisconsin Madison |
Rich Harang |
Position: CFP Lead, Steering Committee Member
Affiliation: NVIDIA Expertise: Network Intrusion Detection, ML for Offense Bio: Rich Harang is a Principal Security Architect at NVIDIA, specializing in ML/AI systems, with over a decade of experience at the intersection of computer security, machine learning, and privacy. He received his PhD in Statistics from the University of California Santa Barbara in 2010. Prior to joining NVIDIA, he led the Algorithms Research team at Duo, led research on using machine learning models to detect malicious software, scripts, and web content at Sophos AI, and worked as a Team Lead at the US Army Research Laboratory. His research interests include adversarial machine learning, addressing bias and uncertainty in machine learning, and ways to use machine learning to support human analysis. Richard’s work has been presented at USENIX, BlackHat, IEEE S&P workshops, and DEF CON AI Village, among others, and has also been featured in The Register and KrebsOnSecurity. |
Sven Cattell |
Position: Founder
Affiliation: nbhd.ai Expertise: ML Defense, Geometric data analysis Bio: Sven founded the AI Village in 2018 and has been running it ever since. He was the principal organizer of AIV’s Generative Red Team at DEFCON 31. Sven is also the founder of nbhd.ai, a startup focused on the security and integrity of datasets and the AI they build. He was previously a senior data scientist at Elastic where he built the malware model training pipeline. He has a PhD in Algebraic Topology, and a postdoc in geometric machine learning where he focused on anomaly and novelty detection. |
Will Pearce |
Position: CTF Lead, Steering Committee Member
Affiliation: NVIDIA Expertise: ML Threat Detection Bio: Will Pearce is one of the founders of dreadnode.io a startup that is building AI cyber ranges. He focuses on attacking machine learning systems and developing ML-enabled red team capabilities. Previously, he was Senior Security Researcher on the AI Red Team at NVIDIA and the Red Team Lead for the Azure Trustworthy ML team at Microsoft, and a Senior Security Consultant at Silent Break Security. His work on offensive machine learning has appeared at industry conferences including Blackhat, Defcon AI Village, WWHF, DerbyCon, LabsCon, and academic appearances at the SAI Conference on Computing and IEEE. |