Ramesh Karri

Artificial Intelligence · 2004–2023

A researcher in the Science corpus: 18 papers; trusts 68 researchers and is trusted by 12 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 102 citations into it; #35,331 of 35,345 by trust here, #12,761 by citations
• Hardware and Architecture — 65 citations into it; #448 of 1,551 by trust here, #378 by citations
• Information Systems — 64 citations into it; #7,082 of 8,771 by trust here, #6,770 by citations
• Electrical and Electronic Engineering — 47 citations into it; #4,354 of 16,539 by trust here, #7,422 by citations
• Software — 43 citations into it
• Natural Language Processing — 39 citations into it
• Signal Processing — 38 citations into it
• Large Language Models — 36 citations into it

Whom Ramesh Karri trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Alec Radford
2. Yier Jin
3. Farinaz Koushanfar
4. Hammond A. Pearce
5. Ashish Vaswani
6. M. Tehranipoor
7. Nick L. Petroni Jr.
8. Jacob Devlin
9. Martin Sundermeyer
10. Rolf Drechsler

Who trusts Ramesh Karri overall

1. Muhammad Yasin
2. Jeyavijayan Rajendran
3. Masoud Rostami
4. Stephen E. McLaughlin
5. Kaveh Shamsi
6. Rashid Tahir
7. Yongbin Zhou
8. Ozgur Sinanoglu

Papers from Ramesh Karri's perspective

Ordered by how strongly the researchers Ramesh Karri trusts endorse each paper. Same corpus, a different order for every researcher.

1. Attention is All you Need (Neural Information Processing Systems)
2. ImageNet classification with deep convolutional neural networks
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Long Short-Term Memory
5. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Gradient-based learning applied to document recognition
8. Language Models are Unsupervised Multitask Learners
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. ImageNet: A large-scale hierarchical image database

Their papers

• Asleep at the Keyboard? Assessing the Security of GitHub Copilot’s Code Contributions (2021) — 856 citations
• Security analysis of integrated circuit camouflaging (2013) — 392 citations
• Security analysis of logic obfuscation (2012) — 486 citations
• Trustworthy Hardware: Identifying and Classifying Hardware Trojans (2010) — 510 citations
• Fault Analysis-Based Logic Encryption (2015) — 425 citations
• On Improving the Security of Logic Locking (2016) — 310 citations
• On design vulnerability analysis and trust benchmarks development (2013) — 296 citations
• DAVE: Deriving Automatically Verilog from English (2020) — 100 citations
• Chip-Chat: Challenges and Opportunities in Conversational Hardware Design (2023) — 313 citations
• VeriGen: A Large Language Model for Verilog Code Generation (2023) — 389 citations
• Lost at C: A User Study on the Security Implications of Large Language Model Code Assistants (2022) — 184 citations
• An Empirical Cybersecurity Evaluation of GitHub Copilot's Code Contributions (2021) — 51 citations
• Examining Zero-Shot Vulnerability Repair with Large Language Models (2021) — 339 citations
• The Cybersecurity Landscape in Industrial Control Systems (2016) — 343 citations
• A Primer on Hardware Security: Models, Methods, and Metrics (2014) — 606 citations
• NumChecker: Detecting kernel control-flow modifying rootkits by using Hardware Performance Counters (2013) — 118 citations
• Secure scan: a design-for-test architecture for crypto chips (2005) — 319 citations
• Scan based side channel attack on dedicated hardware implementations of Data Encryption Standard (2004) — 374 citations