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Andre Nakkab

3 accepted papers

2025

VeriLoC: Line-of-Code Level Prediction of Hardware Design Quality from Verilog Code

NeurIPS 2025poster

Modern chip design is complex, and there is a crucial need for early-stage prediction of key design-quality metrics like timing and routing congestion directly from Verilog code (a commonly used programming language for hardware design). It is especially important yet complex to predict individual…

Cited by 0SourceScholar
2025

VeriThoughts: Enabling Automated Verilog Code Generation using Reasoning and Formal Verification

NeurIPS 2025poster

This paper introduces VeriThoughts, a novel dataset designed for reasoning-based Verilog code generation. We establish a new benchmark framework grounded in formal verification methods to evaluate the quality and correctness of generated hardware descriptions. Additionally, we present a suite of spe…

Cited by 0SourcecodeScholar
2024

BioTrove: A Large Curated Image Dataset Enabling AI for Biodiversity

NeurIPS 2024spotlight

We introduce BioTrove, the largest publicly accessible dataset designed to advance AI applications in biodiversity. Curated from the iNaturalist platform and vetted to include only research-grade data, BioTrove contains 161.9 million images, offering unprecedented scale and diversity from three prim…

Cited by 2SourcePDFScholar