Impact of process-variations in STTRAM and adaptive boosting for robustness. - Seyedhamidreza Motaman; Swaroop Ghosh; Nitin Rathi (DATE, 2015)

Data privacy in non-volatile cache: Challenges, attack models and solutions. - Nitin Rathi; Swaroop Ghosh; Anirudh Iyengar; Helia Naeimi (ASP-DAC, 2016)

Side channel attacks on STTRAM and low-overhead countermeasures. - Anirudh Iyengar; Swaroop Ghosh; Nitin Rathi; Helia Naeimi (DFT, 2016)

Cache Bypassing and Checkpointing to Circumvent Data Security Attacks on STTRAM. - Nitin Rathi; Asmit De; Helia Naeimi; Swaroop Ghosh (CoRR, 2016)

Side Channel Attacks on STTRAM and Low-Overhead Countermeasures. - Nitin Rathi; Helia Naeimi; Swaroop Ghosh (CoRR, 2016)

Magnetic Tunnel Junction Reliability Assessment Under Process Variations and Activity Factors and Mitigation Techniques. - Anirudh Srikant Iyengar; Swaroop Ghosh; Nitin Rathi (J. Low Power Electron., 2018)

STDP-Based Pruning of Connections and Weight Quantization in Spiking Neural Networks for Energy-Efficient Recognition. - Nitin Rathi; Priyadarshini Panda; Kaushik Roy 001 (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2019)

Cache Bypassing and Checkpointing to Circumvent Data Security Attacks on STTRAM. - Seyedhamidreza Motaman; Swaroop Ghosh; Nitin Rathi (IEEE Trans. Emerg. Top. Comput., 2019)

Inherent Adversarial Robustness of Deep Spiking Neural Networks: Effects of Discrete Input Encoding and Non-linear Activations. - Saima Sharmin; Nitin Rathi; Priyadarshini Panda; Kaushik Roy 001 (ECCV (29), 2020)

Enabling Deep Spiking Neural Networks with Hybrid Conversion and Spike Timing Dependent Backpropagation. - Nitin Rathi; Gopalakrishnan Srinivasan; Priyadarshini Panda; Kaushik Roy 001 (ICLR, 2020)

DIET-SNN: Direct Input Encoding With Leakage and Threshold Optimization in Deep Spiking Neural Networks. - Nitin Rathi; Kaushik Roy 001 (CoRR, 2020)

Exploring Spike-Based Learning for Neuromorphic Computing: Prospects and Perspectives. - Nitin Rathi; Amogh Agrawal; Chankyu Lee; Adarsh Kumar Kosta; Kaushik Roy 001 (DATE, 2021)

Accurate and Accelerated Neuromorphic Network Design Leveraging A Bayesian Hyperparameter Pareto Optimization Approach. - Maryam Parsa; Catherine D. Schuman; Nitin Rathi; Amirkoushyar Ziabari; Derek C. Rose; J. Parker Mitchell; J. Travis Johnston; Bill Kay; Steven R. Young; Kaushik Roy 001 (ICONS, 2021)

IMPULSE: A 65nm Digital Compute-in-Memory Macro with Fused Weights and Membrane Potential for Spike-based Sequential Learning Tasks. - Amogh Agrawal; Mustafa Fayez Ali; Minsuk Koo; Nitin Rathi; Akhilesh Jaiswal 001; Kaushik Roy 001 (CoRR, 2021)

One Timestep is All You Need: Training Spiking Neural Networks with Ultra Low Latency. - Sayeed Shafayet Chowdhury; Nitin Rathi; Kaushik Roy 001 (CoRR, 2021)

STDP Based Unsupervised Multimodal Learning With Cross-Modal Processing in Spiking Neural Networks. - Nitin Rathi; Kaushik Roy 001 (IEEE Trans. Emerg. Top. Comput. Intell., 2021)

Efficiency attacks on spiking neural networks. - Sarada Krithivasan; Sanchari Sen; Nitin Rathi; Kaushik Roy 001; Anand Raghunathan (DAC, 2022)

Towards Ultra Low Latency Spiking Neural Networks for Vision and Sequential Tasks Using Temporal Pruning. - Sayeed Shafayet Chowdhury; Nitin Rathi; Kaushik Roy 001 (ECCV (11), 2022)

DIET-SNN: A Low-Latency Spiking Neural Network With Direct Input Encoding and Leakage and Threshold Optimization. - Nitin Rathi; Kaushik Roy 001 (IEEE Trans. Neural Networks Learn. Syst., 2023)

Exploring Neuromorphic Computing Based on Spiking Neural Networks: Algorithms to Hardware. - Nitin Rathi; Indranil Chakraborty; Adarsh Kosta; Abhronil Sengupta; Aayush Ankit; Priyadarshini Panda; Kaushik Roy 001 (ACM Comput. Surv., 2023)

LITE-SNN: Leveraging Inherent Dynamics to Train Energy-Efficient Spiking Neural Networks for Sequential Learning. - Nitin Rathi; Kaushik Roy 001 (IEEE Trans. Cogn. Dev. Syst., 2024)