Matheus Maldaner

Research Affiliations

University of Florida

Research at the University of Florida focusing on the fusion of symbolic reasoning with neural networks to enhance AI explainability.

Carnegie Mellon University

Research at Carnegie Mellon University focusing on the ethical and societal effects of generative text-to-image AI models.

Microsoft

Research at Microsoft Research's AI Frontiers group focusing on human-centered multi-agent systems and long-running web agents.

Research Papers

Research Posters

Neuro Symbolic AI: Bridging Neural Networks and Symbolic Reasoning for Enhanced AI Transparency

Ethical Horizons in the field of Neuro Symbolic AI

Uniting Symbolic and Neural Paradigms for Transparent AI

MIRAGE: Multi-model Interface for Reviewing and Auditing GEnerative Text-to-Image AI

Side-by-Side Multi-Models T2I Comparisons Unveiling Problems in AI

eXpLogic: Explaining Logic Types and Patterns in DiffLogic Networks

MIRAGE: Multi-model Interface for Reviewing and Auditing GEnerative Text-to-Image AI

Side-by-Side Multi-Models T2I Comparisons Unveiling Problems in AI

Accelerating Real-Time Inference with FPGA-Implemented Logic Gate Neural Networks

The Ineffectiveness of the Information Maximization Algorithm on Spectrally Sparse Signals

Enhancing AI Security with FPGA-Accelerated Differentiable Logic Gate Networks

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Matheus Kunzler Maldaner

Neuro Symbolic AI: Bridging Neural Networks and Symbolic Reasoning for Enhanced AI Transparency

Neuro Symbolic AI: Bridging Neural Networks and Symbolic Reasoning for Enhanced AI Transparency

Ethical Horizons in the field of Neuro Symbolic AI

Ethical Horizons in the field of Neuro Symbolic AI

Uniting Symbolic and Neural Paradigms for Transparent AI

MIRAGE: Multi-model Interface for Reviewing and Auditing GEnerative Text-to-Image AI

MIRAGE: Multi-model Interface for Reviewing and Auditing GEnerative Text-to-Image AI

Side-by-Side Multi-Models T2I Comparisons Unveiling Problems in AI

eXpLogic: Explaining Logic Types and Patterns in DiffLogic Networks

MIRAGE: Multi-model Interface for Reviewing and Auditing GEnerative Text-to-Image AI

Side-by-Side Multi-Models T2I Comparisons Unveiling Problems in AI

Accelerating Real-Time Inference with FPGA-Implemented Logic Gate Neural Networks

The Ineffectiveness of the Information Maximization Algorithm on Spectrally Sparse Signals

Enhancing AI Security with FPGA-Accelerated Differentiable Logic Gate Networks

Neuro Symbolic AI: Bridging Neural Networks and Symbolic Reasoning for Enhanced AI Transparency

Neuro Symbolic AI: Bridging Neural Networks and Symbolic Reasoning for Enhanced AI Transparency

Ethical Horizons in the field of Neuro Symbolic AI

Ethical Horizons in the field of Neuro Symbolic AI

Uniting Symbolic and Neural Paradigms for Transparent AI

MIRAGE: Multi-model Interface for Reviewing and Auditing GEnerative Text-to-Image AI

MIRAGE: Multi-model Interface for Reviewing and Auditing GEnerative Text-to-Image AI

Side-by-Side Multi-Models T2I Comparisons Unveiling Problems in AI

eXpLogic: Explaining Logic Types and Patterns in DiffLogic Networks

MIRAGE: Multi-model Interface for Reviewing and Auditing GEnerative Text-to-Image AI

Side-by-Side Multi-Models T2I Comparisons Unveiling Problems in AI

Accelerating Real-Time Inference with FPGA-Implemented Logic Gate Neural Networks

The Ineffectiveness of the Information Maximization Algorithm on Spectrally Sparse Signals

Enhancing AI Security with FPGA-Accelerated Differentiable Logic Gate Networks

Deploying Learned Logic Gates onto FPGAs for Increased Efficiency

Seeing Twice: How Side-by-Side T2I Comparison Changes Auditing Strategies

Sentinel Steps: Towards Longer Running AI Agents