Panel

Kamelia Aryafar

Head of AI for Members, Netflix

Kamelia Aryafar is a senior technology executive with extensive experience building and scaling AI-driven products and platforms. She currently operates as Head of AI for Members at Netflix. Prior to Netflix, she was at Google, where she co-founded and led engineering for major AI products, including Gemini Enterprise and Business, Google Agentspace, and Vertex AI Search and Platform. She also served as EVP, Chief Algorithms and Analytics Officer, and a board member at Overstock.com (Bed Bath & Beyond), where she oversaw engineering, AI, and product. Earlier in her career, she worked at Etsy, helping embed machine learning and AI across several products throughout the organization.

Mehdi Bahrami

Senior Research Manager, Fujitsu Research of America

Dr. Mehdi Bahrami is a Senior Research Manager at Fujitsu Research of America, where he leads research on Agentic AI, LLM-based agents, and AI for software engineering. His recent work includes Kozuchi Agent, an open-weight agent framework for autonomous software engineering and repair. His broader research interests include generative AI, LLMs, and applied machine learning.

Dr. Bahrami has over 15 years of experience in software engineering and industrial AI research, with 30+ technical publications and 34+ granted U.S. patents. He is an ACM Distinguished Speaker and Senior Member of ACM and IEEE, and a recipient of the 2024 IEEE Outstanding Engineer Award for pioneering contributions to generative AI and API automation. His work has also been recognized with multiple industry awards and featured by leading technology media, including MIT Technology Review.

Shivam Patel

Member of the Technical Staff, OpenAI

Shivam Patel is a Member of the Technical Staff at OpenAI, where he works on AI safety, evaluation, and abuse prevention. Previously, he was a Senior Machine Learning Engineer at Apple, working on retrieval and ranking for retrieval-augmented generation and agentic question-answering systems. At Google, he worked on large-scale recommendation systems, neural architecture search, and privacy-preserving machine learning. His research internship at Adobe focused on multimodal models for video understanding.

He previously held visiting research appointments at the University of Cambridge, Mila, Caltech, and MIT, with work spanning agent-based modeling, reinforcement learning, computer vision, and mathematical methods for machine learning. His interests include the development and evaluation of reliable AI agents and applications of AI to scientific and mathematical problems.

Maarten Van Segbroeck

Director of Research, NVIDIA

Maarten Van Segbroeck is director of research at NVIDIA, where he leads initiatives at the intersection of synthetic data, privacy, and trustworthy AI. His team develops methods and evaluation frameworks that enable organizations to safely generate, assess, and deploy high-quality synthetic datasets for advanced AI systems. Before joining NVIDIA, Maarten was VP of applied science at Gretel, helping enterprises adopt synthetic data solutions across regulated domains. He previously drove research efforts at Amazon across AWS and Alexa AI. Maarten holds a Ph.D. in electrical engineering from KU Leuven and completed postdoctoral research at the University of Southern California.