About This Panel
Presenters
Narcisse Zekpa
Sr. Solutions Architect, Amazon AWS
Narcisse Zekpa is a Sr. Solutions Architect at AWS. He helps organizations accelerate their business transformation through innovative, and scalable solutions, on the AWS Cloud. He is passionate about enabling businesses to transform themselves, using data and AI.
Sandra Mau
Vice President - Cloud & IP Government Solutions, Clarivate
Sandra Mau is Vice President of Product at Clarivate’s Intellectual Property division (NYSE: CLVT), joining through the acquisition of her AI and computer vision startup, TrademarkVision. The company pioneered one of the first commercial SaaS image search engines for trademarks and design patents, now used by governments, law firms, and corporations worldwide. Sandra previously worked as a Senior Computer Vision Research Engineer at National ICT Australia and has over a decade of experience in AI, computer vision, and tech commercialization. She actively volunteers, holding prior positions on INTA and IEEE committees and has degrees in Robotics (Carnegie Mellon), Aerospace Engineering (University of Toronto), and an MBA (QUT).
Samantha Wylatowska
Solutions Architect, Amazon AWS
Samantha Wylatowska is a Solutions Architect at AWS, specializing in DevSecOps and generative AI security. She partners with organizations to architect secure, automated cloud solutions while helping them navigate the evolving landscape of AI technologies. Her passion lies in guiding organizations towards operational excellence through the thoughtful integration of security automation and AI governance frameworks.
Klaudia Kloc
CEO, Vidoc Security
Klaudia Kloc is the CEO and co-founder of Vidoc Security Lab, a Silicon Valley-based startup building LLM-based tool to secure complex codebases. Before founding Vidoc, she ethically hacked companies like Microsoft, Yahoo, and Uber, uncovering critical vulnerabilities as part of her offensive security research. Nowadays her work focuses on the security risks of AI-generated code and applying large language models (LLMs) to automate code reviews at scale