Trust integrated link state routing protocol for Wireless Sensor Networks (TILSRP). - Arnab Raha; Shaik Sahil Babu; Mrinal Kanti Naskar; Omar Alfandi; Dieter Hogrefe (IEEE ANTS, 2011)

A Direct Trust dependent Link State Routing Protocol Using Route Trusts for WSNs (DTLSRP). - Shaik Sahil Babu; Arnab Raha; Mrinal K. Naskar (Wirel. Sens. Netw., 2011)

A fuzzy based trustworthy route selection method using LSRP in wireless sensor networks (FTRSP). - Arpita Chakraborty; Arnab Raha; Shovan Maity; Mrinal Kanti Naskar; Anupam Karmakar (CCSEIT, 2012)

An efficient sleep protocol for lifetime enhancement in multi covered and multi connected WSNs. - Shovan Maity; Arnab Raha; Souvik Kumar Mitra; Victor Seal; Mrinal Kanti Naskar; Amitava Mukherjee 001 (ICACCI, 2012)

An optimal sensor deployment scheme to ensure multi level coverage and connectivity in wireless sensor networks. - Arnab Raha; Shovan Maity; Mrinal Kanti Naskar; Omar Alfandi; Dieter Hogrefe (IWCMC, 2012)

A Novel Indirect Trust Based Link State Routing Scheme Using a Robust Route Trust Method for Wireless Sensor Networks. - Arnab Raha; Mrinal Kanti Naskar; Arpita Chakraborty; Omar Alfandi; Dieter Hogrefe (NTMS, 2012)

Fuzzy Logic Election of Node for Routing in WSNs. - Shaik Sahil Babu; Arnab Raha; Mrinal Kanti Naskar; Omar Alfandi; Dieter Hogrefe (TrustCom, 2012)

A Simple Flood Forecasting Scheme Using Wireless Sensor Networks - Victor Seal; Arnab Raha; Shovan Maity; Souvik Kumar Mitra; Amitava Mukherjee 001; Mrinal Kanti Naskar (CoRR, 2012)

Hypnos: An ultra-low power sleep mode with SRAM data retention for embedded microcontrollers! - Hrishikesh Jayakumar; Arnab Raha; Vijay Raghunathan (CODES+ISSS, 2014)

ASLAN: Synthesis of approximate sequential circuits. - Ashish Ranjan 001; Arnab Raha; Swagath Venkataramani; Kaushik Roy 001; Anand Raghunathan (DATE, 2014)

Powering the internet of things. - Hrishikesh Jayakumar; Kangwoo Lee; Woo Suk Lee; Arnab Raha; Younghyun Kim 001; Vijay Raghunathan (ISLPED, 2014)

QUICKRECALL: A Low Overhead HW/SW Approach for Enabling Computations across Power Cycles in Transiently Powered Computers. - Hrishikesh Jayakumar; Arnab Raha; Vijay Raghunathan (VLSID, 2014)

A Power Efficient Video Encoder Using Reconfigurable Approximate Arithmetic Units. - Arnab Raha; Hrishikesh Jayakumar; Vijay Raghunathan (VLSID, 2014)

Trust integrated node potential aware routing for WSNs. - Shaik Sahil Babu; Arnab Raha; Omar Alfandi; Dieter Hogrefe; Mrinal Kanti Naskar (Int. J. Trust. Manag. Comput. Commun., 2014)

Quality-aware data allocation in approximate DRAM? - Arnab Raha; Hrishikesh Jayakumar; Soubhagya Sutar; Vijay Raghunathan (CASES, 2015)

Quality configurable reduce-and-rank for energy efficient approximate computing. - Arnab Raha; Swagath Venkataramani; Vijay Raghunathan; Anand Raghunathan (DATE, 2015)

VIDalizer: An energy efficient video streamer. - Arnab Raha; Subrata Mitra; Vijay Raghunathan; Sanjay G. Rao (WCNC, 2015)

QuickRecall: A HW/SW Approach for Computing across Power Cycles in Transiently Powered Computers. - Hrishikesh Jayakumar; Arnab Raha; Woo Suk Lee; Vijay Raghunathan (ACM J. Emerg. Technol. Comput. Syst., 2015)

Energy-efficient system design for IoT devices. - Hrishikesh Jayakumar; Arnab Raha; Younghyun Kim 001; Soubhagya Sutar; Woo Suk Lee; Vijay Raghunathan (ASP-DAC, 2016)

D-PUF: an intrinsically reconfigurable DRAM PUF for device authentication in embedded systems. - Soubhagya Sutar; Arnab Raha; Vijay Raghunathan (CASES, 2016)

Energy-Aware Memory Mapping for Hybrid FRAM-SRAM MCUs in IoT Edge Devices. - Hrishikesh Jayakumar; Arnab Raha; Vijay Raghunathan (VLSID, 2016)

Sleep-Mode Voltage Scaling: Enabling SRAM Data Retention at Ultra-Low Power in Embedded Microcontrollers. - Hrishikesh Jayakumar; Arnab Raha; Vijay Raghunathan (ACM Trans. Embed. Comput. Syst., 2016)

Input-Based Dynamic Reconfiguration of Approximate Arithmetic Units for Video Encoding. - Arnab Raha; Hrishikesh Jayakumar; Vijay Raghunathan (IEEE Trans. Very Large Scale Integr. Syst., 2016)

Ultrafast embedded explicit model predictive control for nonlinear systems. - Arnab Raha; Ankush Chakrabarty; Vijay Raghunathan; Gregery T. Buzzard (ACC, 2017)

Towards Full-System Energy-Accuracy Tradeoffs: A Case Study of An Approximate Smart Camera System. - Arnab Raha; Vijay Raghunathan (DAC, 2017)

Approximate memory compression for energy-efficiency. - Ashish Ranjan 001; Arnab Raha; Vijay Raghunathan; Anand Raghunathan (ISLPED, 2017)

Synergistic Approximation of Computation and Memory Subsystems for Error-Resilient Applications. - Arnab Raha; Vijay Raghunathan (IEEE Embed. Syst. Lett., 2017)

Quality Configurable Approximate DRAM. - Arnab Raha; Soubhagya Sutar; Hrishikesh Jayakumar; Vijay Raghunathan (IEEE Trans. Computers, 2017)

Energy-Aware Memory Mapping for Hybrid FRAM-SRAM MCUs in Intermittently-Powered IoT Devices. - Hrishikesh Jayakumar; Arnab Raha; Jacob R. Stevens; Vijay Raghunathan (ACM Trans. Embed. Comput. Syst., 2017)

qLUT: Input-Aware Quantized Table Lookup for Energy-Efficient Approximate Accelerators. - Arnab Raha; Vijay Raghunathan (ACM Trans. Embed. Comput. Syst., 2017)

Energy-Efficient Reduce-and-Rank Using Input-Adaptive Approximations. - Arnab Raha; Swagath Venkataramani; Vijay Raghunathan; Anand Raghunathan (IEEE Trans. Very Large Scale Integr. Syst., 2017)

Dual Mode Ferroelectric Transistor based Non-Volatile Flip-Flops for Intermittently-Powered Systems. - Sandeep Krishna Thirumala; Arnab Raha; Hrishikesh Jayakumar; Kaisheng Ma; Narayanan Vijaykrishnan; Vijay Raghunathan; Sumeet Kumar Gupta (ISLPED, 2018)

D-PUF: An Intrinsically Reconfigurable DRAM PUF for Device Authentication and Random Number Generation. - Soubhagya Sutar; Arnab Raha; Devadatta M. Kulkarni; Rajeev Shorey; Jeffrey D. Tew; Vijay Raghunathan (ACM Trans. Embed. Comput. Syst., 2018)

Memory-Based Combination PUFs for Device Authentication in Embedded Systems. - Soubhagya Sutar; Arnab Raha; Vijay Raghunathan (IEEE Trans. Multi Scale Comput. Syst., 2018)

Designing Energy-Efficient Intermittently Powered Systems Using Spin-Hall-Effect-Based Nonvolatile SRAM. - Arnab Raha; Akhilesh Jaiswal 001; Syed Shakib Sarwar; Hrishikesh Jayakumar; Vijay Raghunathan; Kaushik Roy 001 (IEEE Trans. Very Large Scale Integr. Syst., 2018)

Approximating Beyond the Processor: Exploring Full-System Energy-Accuracy Tradeoffs in a Smart Camera System. - Arnab Raha; Vijay Raghunathan (IEEE Trans. Very Large Scale Integr. Syst., 2018)

Approximate Systems: Synergistically Approximating Sensing, Computing, Memory, and Communication Subsystems for Energy Efficiency. - Arnab Raha; Vijay Raghunathan (Approximate Circuits, 2019)

Automatic Synthesis Techniques for Approximate Circuits. - Ashish Ranjan 001; Swagath Venkataramani; Shubham Jain; Younghoon Kim; Shankar Ganesh Ramasubramanian; Arnab Raha; Kaushik Roy 001; Anand Raghunathan (Approximate Circuits, 2019)

WSe2 based Valley-Coupled-Spintronic Devices for Low Power Non-Volatile Memories. - Sandeep Krishna Thirumala; T. Hung; Arnab Raha; Niharika Thakuria; K. Cho; Vijay Raghunathan; Zhihong Chen; Sumeet Kumar Gupta (DRC, 2019)

Non-volatile Logic and Memory based on Reconfigurable Ferroelectric Transistors. - Sandeep Krishna Thirumala; Arnab Raha; Vijaykrishnan Narayanan; Vijay Raghunathan; Sumeet Kumar Gupta (NANOARCH, 2019)

Valley-Coupled-Spintronic Non-Volatile Memories with Compute-In-Memory Support. - Sandeep Krishna Thirumala; Yi-Tse Hung; Shubham Jain; Arnab Raha; Niharika Thakuria; Vijay Raghunathan; Anand Raghunathan; Zhihong Chen; Sumeet Kumar Gupta (CoRR, 2019)

IPS-CiM: Enhancing Energy Efficiency of Intermittently-Powered Systems with Compute-in-Memory. - Sandeep Krishna Thirumala; Arnab Raha; Vijay Raghunathan; Sumeet Kumar Gupta (ICCD, 2020)

Approximate inference systems (AxIS): end-to-end approximations for energy-efficient inference at the edge. - Soumendu Kumar Ghosh; Arnab Raha; Vijay Raghunathan (ISLPED, 2020)

Energy-Efficient Edge Detection using Approximate Ramanujan Sums. - Archisman Ghosh; K. Gaurav Kumar; Debaprasad De; Arnab Raha; Mrinal Kanti Naskar (ISQED, 2020)

Energy-Efficient IoT-Health Monitoring System using Approximate Computing. - Avrajit Ghosh; Arnab Raha; Amitava Mukherjee (Internet Things, 2020)

Embedding Approximate Nonlinear Model Predictive Control at Ultrahigh Speed and Extremely Low Power. - Arnab Raha; Ankush Chakrabarty; Vijay Raghunathan; Gregery T. Buzzard (IEEE Trans. Control. Syst. Technol., 2020)

Approximate Memory Compression. - Ashish Ranjan 001; Arnab Raha; Vijay Raghunathan; Anand Raghunathan (IEEE Trans. Very Large Scale Integr. Syst., 2020)

Special Session: Approximate TinyML Systems: Full System Approximations for Extreme Energy-Efficiency in Intelligent Edge Devices. - Arnab Raha; Soumendu Kumar Ghosh; Debabrata Mohapatra; Deepak A. Mathaikutty; Raymond Sung; Cormac Brick; Vijay Raghunathan (ICCD, 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)

PreSyNC: Hardware realization of the Presynaptic Region of a Biologically Extensive Neuronal Circuitry. - Rounak Chatterjee; Souradeep Chowdhury; Soham Mondal; Arnab Raha; Janet Paluh; Amitava Mukherjee 001 (VLSID, 2021)

HIPER: Low Power, High Performance and Area-Efficient Hardware Accelerators for Hidden Periodicity Detection using Ramanujan Filter Banks. - Arghadip Das; Chandrachur Majumder; Debaprasad De; Arnab Raha; Mrinal Kanti Naskar (VLSID, 2021)

Design Considerations for Edge Neural Network Accelerators: An Industry Perspective. - Arnab Raha; Sang Kyun Kim; Deepak Mathaikutty; Guruguhanathan Venkataramanan; Debabrata Mohapatra; Raymond Sung; Cormac Brick; Gautham N. Chinya (VLSID, 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)

Improving Network Throughput by Hardware Realization of a Dynamic Content Caching Scheme for Information-Centric Networking (ICN). - Archisman Ghosh; Biswadeep Chakraborty; Arnab Raha; Amitava Mukherjee 001 (Wirel. Pers. Commun., 2021)

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)

SCENIC: An Area and Energy-Efficient CNN-based Hardware Accelerator for Discernable Classification of Brain Pathologies using MRI. - Bodepu Sai Tirumala Naidu; Shreya Biswas; Rounak Chatterjee; Sayak Mandal; Srijan Pratihar; Ayan Chatterjee; Arnab Raha; Amitava Mukherjee 001; Janet Paluh (VLSID, 2022)

2.4GHz, Double-Buffered, 4kb Standard-Cell-Based Register File with Low-Power Mixed-Frequency Clocking for Machine Learning Accelerators. - Steven Hsu; Amit Agarwal 001; Mark A. Anders 001; Arnab Raha; Raymond Sung; Deepak Mathaikutty; Ram Krishnamurthy 001; James W. Tschanz; Vivek De (VLSI Technology and Circuits, 2022)

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

Exploring the Design of Energy-Efficient Intermittently Powered Systems Using Reconfigurable Ferroelectric Transistors. - Sandeep Krishna Thirumala; Arnab Raha; Sumeet Gupta 001; Vijay Raghunathan (IEEE Trans. Very Large Scale Integr. Syst., 2022)

ENROUTE: An Entropy Aware Routing Scheme for Information-Centric Networks (ICN). - Bitan Banerjee; Sibendu Paul; Omar Alfandi; Arnab Raha; Amitava Mukherjee 001 (Wirel. Pers. Commun., 2022)

Enhanced ML-Based Approach for Functional Safety Improvement in Automotive AMS Circuits. - Ayush Arunachalam; Sanjay Das; Monikka Rajan; Fei Su; Xiankun Jin; Suvadeep Banerjee; Arnab Raha; Suriyaprakash Natarajan; Kanad Basu (ITC, 2023)

VPU-EM: An Event-based Modeling Framework to Evaluate NPU Performance and Power Efficiency at Scale. - Charles Qi; Yi Wang; Hui Wang; Yang Lu; Shiva Shankar Subramanian; Finola Cahill; Conall Tuohy; Victor Li; Xu Qian; Darren Crews; Ling Wang; Shivaji Roy; et al. (CoRR, 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)

Energy-Efficient Approximate Edge Inference Systems. - Soumendu Kumar Ghosh; Arnab Raha; Vijay Raghunathan (ACM Trans. Embed. Comput. 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)

HIPEDAP: Energy-Efficient Hardware Accelerators for Hidden Periodicity Detection. - Arghadip Das; Chandrachur Majumder; Debaprasad De; Arnab Raha; Mrinal Kanti Naskar (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)

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

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

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

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

Enhancing Functional Safety in Automotive AMS Circuits through Unsupervised Machine Learning. - Ayush Arunachalam; Ian Kintz; Suvadeep Banerjee; Arnab Raha; Xiankun Jin; Fei Su; Viswanathan Pillai Prasanth; Rubin A. Parekhji; Suriyaprakash Natarajan; Kanad Basu (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)

PArtNNer: Platform-Agnostic Adaptive Edge-Cloud DNN Partitioning for Minimizing End-to-End Latency. - Soumendu Kumar Ghosh; Arnab Raha; Vijay Raghunathan; Anand Raghunathan (ACM Trans. Embed. Comput. Syst., 2024)

Toward Energy-Efficient Collaborative Inference Using Multisystem Approximations. - Arghadip Das; Soumendu Kumar Ghosh; Arnab Raha; Vijay Raghunathan (IEEE Internet Things J., 2024)

PRISM: Toward Energy-Efficient AIoT with Processing-In-Sensor+Memory in Battery-Free Devices. - Arghadip Das; Yatharth Agarwal; Chunguang Wang; Arnab Raha; Sandeep Krishna Thirumala; Sumeet Kumar Gupta; Vijay Raghunathan (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)

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)

StruM: Structured Mixed Precision for Efficient Deep Learning Hardware Codesign. - Michael Wu 001; Arnab Raha; Deepak A. Mathaikutty; Martin Langhammer; Nihat Engin Tunali (CoRR, 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)

Towards Energy-Accuracy Scalable Multimodal Cognitive Systems. - Soumendu Kumar Ghosh; Arghadip Das; Arnab Raha; Vijay Raghunathan (IEEE Embed. Syst. Lett., 2025)