SEIR: A Stackelberg game based approach for energy-aware and incentivized routing in selfish Opportunistic Networks. - Anshuman Chhabra; Vidushi Vashishth; Deepak Kumar Sharma (CISS, 2017)

A game theory based secure model against Black hole attacks in Opportunistic Networks. - Anshuman Chhabra; Vidushi Vashishth; Deepak Kumar Sharma (CISS, 2017)

An Energy Efficient Routing Protocol for Wireless Internet-of-Things Sensor Networks. - Anshuman Chhabra; Vidushi Vashishth; Anirudh Khanna; Deepak Kumar Sharma; Jyotsna Singh (CoRR, 2018)

A fuzzy logic and game theory based adaptive approach for securing opportunistic networks against black hole attacks. - Anshuman Chhabra; Vidushi Vashishth; Deepak Kumar Sharma (Int. J. Commun. Syst., 2018)

A Machine Learning Approach Using Classifier Cascades for Optimal Routing in Opportunistic Internet of Things Networks. - Vidushi Vashishth; Anshuman Chhabra; Deepak Kumar Sharma (SECON, 2019)

GMMR: A Gaussian mixture model based unsupervised machine learning approach for optimal routing in opportunistic IoT networks. - Vidushi Vashishth; Anshuman Chhabra; Deepak Kumar Sharma (Comput. Commun., 2019)

RLProph: a dynamic programming based reinforcement learning approach for optimal routing in opportunistic IoT networks. - Deepak Kumar Sharma; Joel J. P. C. Rodrigues; Vidushi Vashishth; Anirudh Khanna; Anshuman Chhabra (Wirel. Networks, 2020)

Enabling security for the Industrial Internet of Things using deep learning, blockchain, and coalitions. - Mehul Sharma; Shrid Pant; Deepak Kumar Sharma; Koyel Datta Gupta; Vidushi Vashishth; Anshuman Chhabra (Trans. Emerg. Telecommun. Technol., 2021)

Beyond Prompts: Exploring the Design Space of Mixed-Initiative Co-Creativity Systems. - Zhiyu Lin; Upol Ehsan; Rohan Agarwal; Samihan Dani; Vidushi Vashishth; Mark O. Riedl (ICCC, 2023)

DynaQuant: Compressing Deep Learning Training Checkpoints via Dynamic Quantization. - Amey Agrawal; Sameer Reddy; Satwik Bhattamishra; Venkata Prabhakara Sarath Nookala; Vidushi Vashishth; Kexin Rong 001; Alexey Tumanov (CoRR, 2023)

Inshrinkerator: Compressing Deep Learning Training Checkpoints via Dynamic Quantization. - Amey Agrawal; Sameer Reddy; Satwik Bhattamishra; Venkata Prabhakara Sarath Nookala; Vidushi Vashishth; Kexin Rong 001; Alexey Tumanov (SoCC, 2024)

Beyond Following: Mixing Active Initiative into Computational Creativity. - Zhiyu Lin; Upol Ehsan; Rohan Agarwal; Samihan Dani; Vidushi Vashishth; Mark O. Riedl (EXAG@AIIDE, 2024)