Andre Nakkab

According to our database, Andre Nakkab authored at least 7 papers between 2023 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2025

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

Raghu Vamshi Hemadri, Jitendra Bhandari, Andre Nakkab, Johann Knechtel, Badri P. Gopalan, Ramesh Narayanaswamy, Ramesh Karri, Siddharth Garg

CoRR, June, 2025

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

Patrick Yubeaton, Andre Nakkab, Weihua Xiao, Luca Collini, Ramesh Karri, Chinmay Hegde, Siddharth Garg

CoRR, May, 2025

Large Language Models (LLMs) for Verification, Testing, and Design.

Chandan Kumar Jha, Muhammad Hassan, Khushboo Qayyum, Sallar Ahmadi-Pour, Kangwei Xu, Ruidi Qiu, Jason Blocklove, Luca Collini, Andre Nakkab, Ulf Schlichtmann, Grace Li Zhang, Ramesh Karri, Bing Li, Siddharth Garg, Rolf Drechsler

Proceedings of the IEEE European Test Symposium, 2025

2024

Arboretum: A Large Multimodal Dataset Enabling AI for Biodiversity.

Chih-Hsuan Yang, Benjamin Feuer, Zaki Jubery, Zi K. Deng, Andre Nakkab, Md. Zahid Hasan, Shivani Chiranjeevi, Kelly O. Marshall, Nirmal Baishnab, Asheesh K. Singh, Arti Singh, Soumik Sarkar, Nirav C. Merchant, Chinmay Hegde, Baskar Ganapathysubramanian

CoRR, 2024

BioTrove: A Large Curated Image Dataset Enabling AI for Biodiversity.

Chih-Hsuan Yang, Benjamin Feuer, Talukder Zaki Jubery, Zi K. Deng, Andre Nakkab, Md. Zahid Hasan, Shivani Chiranjeevi, Kelly O. Marshall, Nirmal Baishnab, Asheesh Kumar Singh, Arti Singh, Soumik Sarkar, Nirav C. Merchant, Chinmay Hegde, Baskar Ganapathysubramanian

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Rome was Not Built in a Single Step: Hierarchical Prompting for LLM-based Chip Design.

Andre Nakkab, Sai Qian Zhang, Ramesh Karri, Siddharth Garg

Proceedings of the 2024 ACM/IEEE International Symposium on Machine Learning for CAD, 2024

2023

LiT Tuned Models for Efficient Species Detection.

Andre Nakkab, Benjamin Feuer, Chinmay Hegde

CoRR, 2023