APEX: Adaptive Ext4 File System for Enhanced Data Recoverability in Edge Devices. - Shreshth Tuli; Shikhar Tuli; Udit Jain; Rajkumar Buyya (CloudCom, 2019)

DHOOM: Reusing Design-for-Debug Hardware for Online Monitoring. - Neetu Jindal; Sandeep Chandran; Preeti Ranjan Panda; Sanjiva Prasad; Abhay Mitra; Kunal Singhal; Shubham Gupta; Shikhar Tuli (DAC, 2019)

Transformative effects of IoT, Blockchain and Artificial Intelligence on cloud computing: Evolution, vision, trends and open challenges. - Sukhpal Singh Gill; Shreshth Tuli; Minxian Xu; Inderpreet Singh; Karan Vijay Singh; Dominic Lindsay; Shikhar Tuli; Daria Smirnova; Manmeet Singh; Udit Jain; Haris Pervaiz; Bhanu Sehgal; et al. (Internet Things, 2019)

FogBus: A Blockchain-based Lightweight Framework for Edge and Fog Computing. - Shreshth Tuli; Md. Redowan Mahmud; Shikhar Tuli; Rajkumar Buyya (J. Syst. Softw., 2019)

RRAM-VAC: A Variability-Aware Controller for RRAM-based Memory Architectures. - Shikhar Tuli; Marco Rios; Alexandre Levisse; David Atienza (ASP-DAC, 2020)

Design of a Conventional-Transistor-Based Analog Integrated Circuit for On-Chip Learning in a Spiking Neural Network. - Shikhar Tuli; Debanjan Bhowmik (ICONS, 2020)

AVAC: A Machine Learning Based Adaptive RRAM Variability-Aware Controller for Edge Devices. - Shikhar Tuli; Shreshth Tuli (ISCAS, 2020)

Predicting the growth and trend of COVID-19 pandemic using machine learning and cloud computing. - Shreshth Tuli; Shikhar Tuli; Rakesh Tuli; Sukhpal Singh Gill (Internet Things, 2020)

Next generation technologies for smart healthcare: challenges, vision, model, trends and future directions. - Shreshth Tuli; Shikhar Tuli; Gurleen Wander; Praneet Wander; Sukhpal Singh Gill; Schahram Dustdar; Rizos Sakellariou; Omer F. Rana (Internet Technol. Lett., 2020)

Are Convolutional Neural Networks or Transformers more like human vision? - Shikhar Tuli; Ishita Dasgupta 001; Erin Grant; Tom Griffiths 001 (CogSci, 2021)

Generative Optimization Networks for Memory Efficient Data Generation. - Shreshth Tuli; Shikhar Tuli; Giuliano Casale; Nicholas R. Jennings (CoRR, 2021)

EdgeTran: Co-designing Transformers for Efficient Inference on Mobile Edge Platforms. - Shikhar Tuli; Niraj K. Jha (CoRR, 2023)

BREATHE: Second-Order Gradients and Heteroscedastic Emulation based Design Space Exploration. - Shikhar Tuli; Niraj K. Jha (CoRR, 2023)

FlexiBERT: Are Current Transformer Architectures too Homogeneous and Rigid? - Shikhar Tuli; Bhishma Dedhia; Shreshth Tuli; Niraj K. Jha (J. Artif. Intell. Res., 2023)

CODEBench: A Neural Architecture and Hardware Accelerator Co-Design Framework. - Shikhar Tuli; Chia-Hao Li; Ritvik Sharma; Niraj K. Jha (ACM Trans. Embed. Comput. Syst., 2023)

AccelTran: A Sparsity-Aware Accelerator for Dynamic Inference With Transformers. - Shikhar Tuli; Niraj K. Jha (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2023)

TransCODE: Co-Design of Transformers and Accelerators for Efficient Training and Inference. - Shikhar Tuli; Niraj K. Jha (IEEE Trans. Comput. Aided Des. Integr. Circuits Syst., 2023)

SLiM: Speculative Decoding with Hypothesis Reduction. - Chi-Heng Lin; Shikhar Tuli; James Seale Smith; Yen-Chang Hsu; Yilin Shen; Hongxia Jin (NAACL-HLT (Findings), 2024)

DynaMo: Accelerating Language Model Inference with Dynamic Multi-Token Sampling. - Shikhar Tuli; Chi-Heng Lin; Yen-Chang Hsu; Niraj K. Jha; Yilin Shen; Hongxia Jin (NAACL-HLT, 2024)

EdgeTran: Device-Aware Co-Search of Transformers for Efficient Inference on Mobile Edge Platforms. - Shikhar Tuli; Niraj K. Jha (IEEE Trans. Mob. Comput., 2024)

MoDeGPT: Modular Decomposition for Large Language Model Compression. - Chi-Heng Lin; Shangqian Gao; James Seale Smith; Abhishek Patel; Shikhar Tuli; Yilin Shen; Hongxia Jin; Yen-Chang Hsu (ICLR, 2025)

FlexiGPT: Pruning and Extending Large Language Models with Low-Rank Weight Sharing. - James Seale Smith; Chi-Heng Lin; Shikhar Tuli; Haris Jeelani; Shangqian Gao; Yilin Shen; Hongxia Jin; Yen-Chang Hsu (NAACL (Long Papers), 2025)