Session: The Leadership Algorithm: Applying AI Principles to Build Better Teams
What if the principles we use to train AI models could also shape how we lead and manage engineering teams? From iterative feedback loops to continuous learning, the parallels between effective AI systems and successful leadership are striking.
In this thought-provoking talk, we’ll explore how engineering managers can apply AI-inspired strategies to improve team dynamics, decision-making, and outcomes. Drawing from Topaz's extensive experience leading AI and algorithm teams, and as a VP at the forefront of cutting-edge AI product development, key takeaways will include:
Feedback as a Dataset: How to collect, process, and act on feedback to create a high-performing, resilient team.
Predictive Leadership: Identifying patterns and using them to anticipate challenges before they become blockers.
Balancing Bias and Exploration: Encouraging diversity of thought while maintaining focus on team goals.
Continuous Learning Pipelines: Building team cultures that prioritize upskilling and adaptability in an ever-evolving tech landscape.
This session offers a fresh perspective on leadership by blending the technical with the human, inspiring engineering managers to think like data scientists for their teams.
Bio
Topaz Gilad is an R&D manager specializing in AI, machine learning, and computer vision, leading production-oriented innovative research.
With experience in large companies as well as startups, in various industries, from space imaging and semiconductor microscopy to sports tech, and the wellness industry, she has developed methodologies to scale up while improving quality, delivery, and teamwork.
Currently VP R&D at Voyage81, ODDITY’s innovation core for vision-based AI. Previously head of AI at Pixellot, a leading AI-automated sports production company.
Topaz is also an advocate for women in tech.