TAKO Lab

Trustworthy AI through Knowledge and Optimization Lab

Directed by Prof. Zhe Zeng

We perform research in artificial intelligence (AI) and machine learning (ML) with focus on neurosymbolic AI. Our goal is to enable and support decision-making in the real world in the presence of probabilistic uncertainty and symbolic knowledge (graph structures, logical, arithmetic, and physical constraints, etc) to achieve trustworthy AI and aid scientific discoveries.

Department of Computer Science

University of Virginia

Email: zhez@virginia.edu

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Recent Publications

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Recent Talks

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Invited Talk — Oct 2025

Constraining Deep Generative Models with Neurosymbolic Approach

AI/ML Seminar at UVA

Slides

Constraining Deep Generative Models with Neurosymbolic Approach

Guest Lecture — Sep 2025

Neurosymbolic Learning and Reasoning for Trustworthy AI

CS6190 at UVA

Slides

Neurosymbolic Learning and Reasoning for Trustworthy AI

Invited Talk — Aug 2024

Neurosymbolic Learning and Reasoning for Trustworthy AI

Seminar on Artificial Intelligence and Logics (SNAIL) at University of São Paulo

Invited Talk — Oct 2023

Weighted Model Integration

Probabilistic Circuits and Logic Workshop at Simons Institute, UC Berkeley

Slides Video

Weighted Model Integration

Research Sponsors