CE 401 Grad News

🎤 Talk Announcement — Causal Machine Learning & Causal Representation Learning I’m excited to share that I’ll be giving a talk on Causal Machine Learning and Causal Representation Learning. In recent years, machine learning has achieved remarkable success in learning patterns and making predictions from data. But an important question remains: Can we move beyond correlation and learn the underlying causal structure of the world? In this talk, I’ll introduce the key ideas behind causal machine learning and explore how causal representation learning aims to uncover meaningful, disentangled representations that can help us reason about interventions, mechanisms, and cause-and-effect relationships. We’ll discuss some of the fundamental concepts, current challenges, and exciting directions at the intersection of causal inference, representation learning, and modern AI. I’m looking forward to sharing ideas, discussing perspectives, and learning from the audience. 📌 Topic: Causal Machine Learning & Causal Representation Learning 🎙 Speaker: [Fariborz Sadeghi ] 📅 Date: [October 9,2026 / 17 Mehr,1405 ] 🕐 Time: [7 PM Tehran / 11 : 30 AM EST] 📍 Location / Link: [ https://drexel.zoom.us/j/9088759448 ] Everyone interested in Machine Learning, Causal Inference, Representation Learning, and AI is warmly invited. Hope to see you there! 🚀 #MachineLearning #CausalML #CausalInference #CausalRepresentationLearning #ArtificialIntelligence #DeepLearning #RepresentationLearning #AI