Dynamic Queuing Model for the Secondary Users in a Cognitive Radio Network for Improvement of QoS. - Kaushik Dutta; Rishav Mukherjee; Anindita Kundu; Shamik Kundu (ANTS, 2018)

Classification of Short-Texts Generated During Disasters: A Deep Neural Network Based Approach. - Shamik Kundu; P. K. Srijith; Maunendra Sankar Desarkar (ASONAM, 2018)

High-level Modeling of Manufacturing Faults in Deep Neural Network Accelerators. - Shamik Kundu; Ahmet Soyyigit; Khaza Anuarul Hoque; Kanad Basu (IOLTS, 2020)

Analyzing the Efficiency of Machine Learning Classifiers in Hardware-Based Malware Detectors. - Abraham Peedikayil Kuruvila; Shamik Kundu; Kanad Basu (ISVLSI, 2020)

Secure Logic Locking with Strain-Protected Nanomagnet Logic. - Naimul Hassan; Alexander J. Edwards; Dhritiman Bhattacharya; Mustafa M. Shihab; Varun Venkat; Peng Zhou; Xuan Hu 002; Shamik Kundu; Abraham Peedikayil Kuruvila; Kanad Basu; Jayasimha Atulasimha; Yiorgos Makris; et al. (DAC, 2021)

HardCompress: A Novel Hardware-based Low-power Compression Scheme for DNN Accelerators. - Ayush Arunachalam; Shamik Kundu; Arnab Raha; Suvadeep Banerjee; Suriyaprakash Natarajan; Kanad Basu (ISQED, 2021)

Application of Machine Learning in Hardware Trojan Detection. - Shamik Kundu; Xingyu Meng; Kanad Basu (ISQED, 2021)

Special Session: Reliability Analysis for AI/ML Hardware. - Shamik Kundu; Kanad Basu; Mehdi Sadi; Twisha Titirsha; Shihao Song; Anup Das 001; Ujjwal Guin (VTS, 2021)

Special Session: Reliability Analysis for ML/AI Hardware. - Shamik Kundu; Kanad Basu; Mehdi Sadi; Twisha Titirsha; Shihao Song; Anup Das 001; Ujjwal Guin (CoRR, 2021)

Defending Hardware-Based Malware Detectors Against Adversarial Attacks. - Abraham Peedikayil Kuruvila; Shamik Kundu; Kanad Basu (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2021)

Toward Functional Safety of Systolic Array-Based Deep Learning Hardware Accelerators. - Shamik Kundu; Suvadeep Banerjee; Arnab Raha; Suriyaprakash Natarajan; Kanad Basu (IEEE Trans. Very Large Scale Integr. Syst., 2021)

Detecting Functional Safety Violations in Online AI Accelerators. - Shamik Kundu; Kanad Basu (IOLTS, 2022)

Design and Logic Synthesis of a Scalable, Efficient Quantum Number Theoretic Transform. - Chao Lu; Shamik Kundu; Abraham Peedikayil Kuruvila; Supriya Margabandhu Ravichandran; Kanad Basu (ISLPED, 2022)

Fault Resilience of DNN Accelerators for Compressed Sensor Inputs. - Ayush Arunachalam; Shamik Kundu; Arnab Raha; Suvadeep Banerjee; Kanad Basu (ISVLSI, 2022)

Unsupervised Learning-based Early Anomaly Detection in AMS Circuits of Automotive SoCs. - Ayush Arunachalam; Athulya Kizhakkayil; Shamik Kundu; Arnab Raha; Suvadeep Banerjee; Robert Jin; Fei Su; Kanad Basu (ITC, 2022)

RIBoNN: Designing Robust In-Memory Binary Neural Network Accelerators. - Shamik Kundu; Akul Malhotra; Arnab Raha; Sumeet Kumar Gupta; Kanad Basu (ITC, 2022)

Special Session: Effective In-field Testing of Deep Neural Network Hardware Accelerators. - Shamik Kundu; Suvadeep Banerjee; Arnab Raha; Kanad Basu (VTS, 2022)

Explainable Machine Learning for Intrusion Detection via Hardware Performance Counters. - Abraham Peedikayil Kuruvila; Xingyu Meng; Shamik Kundu; Gaurav Pandey 004; Kanad Basu (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2022)

RTL-ConTest: Concolic Testing on RTL for Detecting Security Vulnerabilities. - Xingyu Meng; Shamik Kundu; Arun K. Kanuparthi; Kanad Basu (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2022)

Application Profiling Using Register-Instruction Hardware Performance Counters. - Anand Menon; Amisha Srivastava; Shamik Kundu; Kanad Basu (ISVLSI, 2023)

Bottlenecks in Secure Adoption of Deep Neural Networks in Safety-Critical Applications. - Sanjay Das; Shamik Kundu; Kanad Basu (MWSCAS, 2023)

Analysis and Mitigation of DRAM Faults in Sparse-DNN Accelerators. - Shamik Kundu; Arnab Raha; Suvadeep Banerjee; Suriyaprakash Natarajan; Kanad Basu (IEEE Des. Test, 2023)

A Novel Low-Power Compression Scheme for Systolic Array-Based Deep Learning Accelerators. - Ayush Arunachalam; Shamik Kundu; Arnab Raha; Suvadeep Banerjee; Suriyaprakash Natarajan; Kanad Basu (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2023)

SeqL+: Secure Scan-Obfuscation With Theoretical and Empirical Validation. - Seetal Potluri; Shamik Kundu; Akash Kumar 001; Kanad Basu; Aydin Aysu (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2023)

Trouble-Shooting at GAN Point: Improving Functional Safety in Deep Learning Accelerators. - Shamik Kundu; Suvadeep Banerjee; Arnab Raha; Fei Su; Suriyaprakash Natarajan; Kanad Basu (IEEE Trans. Computers, 2023)

Graph Learning-based Fault Criticality Analysis for Enhancing Functional Safety of E/E Systems. - Sanjay Das; Shamik Kundu; Pooja Madhusoodhanan; Viswanathan Pillai Prasanth; Rubin A. Parekhji; Arnab Raha; Suvadeep Banerjee; Suriya Natarajan; Kanad Basu (DAC, 2024)

MENDNet: Just-in-time Fault Detection and Mitigation in AI Systems with Uncertainty Quantification and Multi-Exit Networks. - Shamik Kundu; Mirazul Haque; Sanjay Das; Wei Yang 013; Kanad Basu (DAC, 2024)

Explainability to the Rescue: A Pattern-Based Approach for Detecting Adversarial Attacks. - Sanjay Das; Shamik Kundu; Kanad Basu (HOST, 2024)

QNAD: Quantum Noise Injection for Adversarial Defense in Deep Neural Networks. - Shamik Kundu; Navnil Choudhury; Sanjay Das; Arnab Raha; Kanad Basu (HOST, 2024)

RTL-Spec: RTL Spectrum Analysis for Security Bug Localization. - Samit Shahnawaz Miftah; Shamik Kundu; Austin Mordahl; Shiyi Wei; Kanad Basu (HOST, 2024)

SwiSS: Switchable Single-Sided Sparsity-based DNN Accelerators. - Shamik Kundu; Soumendu Kumar Ghosh; Arnab Raha; Deepak A. Mathaikutty (ISLPED, 2024)

QuEST: Quantum Circuit Output Estimation using Gaussian Distribution Analysis. - Shamik Kundu; Navnil Choudhury; Kanad Basu (ISQED, 2024)

RASH: Reliable Deep Learning Acceleration using Sparsity-based Hardware. - Shamik Kundu; Arnab Raha; Deepak A. Mathaikutty; Kanad Basu (ISQED, 2024)

Machine Learning Intervened RIS-Based RF Interference Management for IoT. - Sakib Reza; Sanjay Das; Shamik Kundu; Kanad Basu; Ifana Mahbub (ISVLSI, 2024)

HARVEST: Towards Efficient Sparse DNN Accelerators using Programmable Thresholds. - Soumendu Kumar Ghosh; Shamik Kundu; Arnab Raha; Deepak A. Mathaikutty; Vijay Raghunathan (VLSID, 2024)

Analyzing and Mitigating Circuit Aging Effects in Deep Learning Accelerators. - Sanjay Das; Shamik Kundu; Anand Menon; Yihui Ren 001; Shubha R. Kharel; Kanad Basu (VTS, 2024)

FlexNN: A Dataflow-aware Flexible Deep Learning Accelerator for Energy-Efficient Edge Devices. - Arnab Raha; Deepak A. Mathaikutty; Soumendu Kumar Ghosh; Shamik Kundu (CoRR, 2024)

AttentionBreaker: Adaptive Evolutionary Optimization for Unmasking Vulnerabilities in LLMs through Bit-Flip Attacks. - Sanjay Das; Swastik Bhattacharya; Souvik Kundu 009; Shamik Kundu; Anand Menon; Arnab Raha; Kanad Basu (CoRR, 2024)

Bit-by-Bit: Investigating the Vulnerabilities of Binary Neural Networks to Adversarial Bit Flipping. - Shamik Kundu; Sanjay Das; Sayar Karmakar; Arnab Raha; Souvik Kundu 009; Yiorgos Makris; Kanad Basu (Trans. Mach. Learn. Res., 2024)

DiagNNose: Toward Error Localization in Deep Learning Hardware-Based on VTA-TVM Stack. - Shamik Kundu; Suvadeep Banerjee; Arnab Raha; Suriyaprakash Natarajan; Kanad Basu (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2024)

CONCEAL: Covert NoC Exploitation in In-Memory Computing-based DNN Accelerators. - Sanjay Das; Shamik Kundu; Sumit Kumar Mandal; Kanad Basu (COINS, 2025)

LLM-NPU: Towards Efficient Foundation Model Inference on Low-Power Neural Processing Units. - Arnab Raha; Souvik Kundu 009; Sharath Nittur Sridhar; Shamik Kundu; Soumendu Kumar Ghosh; Alessandro Palla; Arghadip Das; Darren Crews; Deepak A. Mathaikutty (COINS, 2025)

Enhancing AMS Circuit Reliability: An Anomaly Dataset for Functional Safety Research in Automotive SoCs. - Sanjay Das; Anand Menon; Omar Abiola Abioye; Afreen Fatimah Khazi-Syed; Jonathan Edward Lee; Ayush Arunachalam; Shamik Kundu; Pooja Madhusoodhanan; Prasanth Viswanathan Pillai; Rubin A. Parekhji; Arnab Raha; Suvadeep Banerjee; et al. (ACM Great Lakes Symposium on VLSI, 2025)

Efficient Explainable Boosting Machine for RF Active Metasurface Array Synthesis. - Sakib Reza; Sanjay Das; Shamik Kundu; Kanad Basu; Ifana Mahbub (RWS, 2025)

OpenAssert: Towards Secure Assertion Generation using Large Language Models. - Anand Menon; Samit Shahnawaz Miftah; Amisha Srivastava; Shamik Kundu; Shovik Kundu; Arnab Raha; Suvadeep Banerjee; Deepak Mathaikutty; Kanad Basu (VTS, 2025)

GraNNite: Enabling High-Performance Execution of Graph Neural Networks on Resource-Constrained Neural Processing Units. - Arghadip Das; Shamik Kundu; Arnab Raha; Soumendu Kumar Ghosh; Deepak Mathaikutty; Vijay Raghunathan (CoRR, 2025)

XAMBA: Enabling Efficient State Space Models on Resource-Constrained Neural Processing Units. - Arghadip Das; Arnab Raha; Shamik Kundu; Soumendu Kumar Ghosh; Deepak Mathaikutty; Vijay Raghunathan (CoRR, 2025)

Enhancing Large Language Models for Hardware Verification: A Novel SystemVerilog Assertion Dataset. - Anand Menon; Samit S. Miftah; Shamik Kundu; Souvik Kundu 009; Amisha Srivastava; Arnab Raha; Gabriel Theodor Sonnenschein; Suvadeep Banerjee; Deepak Mathaikutty; Kanad Basu (CoRR, 2025)

Accelerating LLM Inference with Flexible N:M Sparsity via A Fully Digital Compute-in-Memory Accelerator. - Akshat Ramachandran; Souvik Kundu 009; Arnab Raha; Shamik Kundu; Deepak A. Mathaikutty; Tushar Krishna (CoRR, 2025)