Ahmed Alsaaed Email and Phone Number

Our teams use state-of-the-art machine learning (ML) and artificial intelligence (AI) to solve real product/scalability problems by combining science and engineering. We work on all aspects of AI, from ideation to full deployment (including defining ML/optimization formulations, statistical modeling, and experimentation).

Head of the Growth and Ecosystem Relevance: Growth, Member Lifecycle, Communication, Anomaly Detection, and Anti-Abuse Relevance. Our teams combine science and engineering with sound product ideas and business strategy. Technical areas include: optimization methods, machine learning/data mining, and analytics.

Leading a team focused on improving LinkedIn products through optimization, algorithms, and analytics by leveraging great datasets. Primary areas include: machine learning/data mining, multi-objective optimization applied to communication relevance (e.g.; email, push-notification), computational advertising, feed relevance, growth, and anomaly detection.

Data-centric product science. Large-scale prediction modeling for display advertising (personalized click/conversion rate estimation/optimization). Statistical data analysis, machine learning, optimization, applied algorithm development - including algorithms for distributed computing.

Design, development, and research of machine learning (ML) models and algorithms for analysis of text, images, and structured data from health records. Project/product management. Business development. Patent portfolio management.

Probabilistic Inference Research. Approximation algorithms for inference in large (intractable) Graphical Models.