CRYPTANITE: A New Look to the World of Social Networks Using Deep Learning. - Vinayshekhar Bannihatti Kumar; Tanisha Rajesh Baadkar; Vinay Joshi (SITIS, 2016)

Phase-Change Memory Models for Deep Learning Training and Inference. - S. R. Nandakumar; Irem Boybat; Vinay Joshi; Christophe Piveteau; Manuel Le Gallo; Bipin Rajendran; Abu Sebastian; Evangelos Eleftheriou (ICECS, 2019)

Computational memory-based inference and training of deep neural networks. - Abu Sebastian; Irem Boybat; Martino Dazzi; Iason Giannopoulos; Vara Prasad Jonnalagadda; Vinay Joshi; Geethan Karunaratne; Benedikt Kersting; Riduan Khaddam-Aljameh; S. R. Nandakumar; Anastasios Petropoulos; Christophe Piveteau; et al. (VLSI Circuits, 2019)

Accurate deep neural network inference using computational phase-change memory. - Vinay Joshi; Manuel Le Gallo; Irem Boybat; Simon Haefeli; Christophe Piveteau; Martino Dazzi; Bipin Rajendran; Abu Sebastian; Evangelos Eleftheriou (CoRR, 2019)

Deep learning acceleration based on in-memory computing. - Evangelos Eleftheriou; Manuel Le Gallo; S. R. Nandakumar; Christophe Piveteau; Irem Boybat; Vinay Joshi; Riduan Khaddam-Aljameh; Martino Dazzi; Iason Giannopoulos; Geethan Karunaratne; Benedikt Kersting; Milos Stanisavljevic; et al. (IBM J. Res. Dev., 2019)

ESSOP: Efficient and Scalable Stochastic Outer Product Architecture for Deep Learning. - Vinay Joshi; Geethan Karunaratne; Manuel Le Gallo; Irem Boybat; Christophe Piveteau; Abu Sebastian; Bipin Rajendran; Evangelos Eleftheriou (ISCAS, 2020)

Mixed-precision deep learning based on computational memory. - S. R. Nandakumar; Manuel Le Gallo; Christophe Piveteau; Vinay Joshi; Giovanni Mariani; Irem Boybat; Geethan Karunaratne; Riduan Khaddam-Aljameh; Urs Egger; Anastasios Petropoulos; Theodore Antonakopoulos 001; Bipin Rajendran; et al. (CoRR, 2020)

Hybrid In-Memory Computing Architecture for the Training of Deep Neural Networks. - Vinay Joshi; Wangxin He; Jae-sun Seo; Bipin Rajendran (ISCAS, 2021)

A 64-core mixed-signal in-memory compute chip based on phase-change memory for deep neural network inference. - Manuel Le Gallo; Riduan Khaddam-Aljameh; Milos Stanisavljevic; Athanasios Vasilopoulos; Benedikt Kersting; Martino Dazzi; Geethan Karunaratne; Matthias Braendli; Abhairaj Singh; Silvia M. Mueller; Julian Büchel; Xavier Timoneda Comas; et al. (CoRR, 2022)

Towards Robust mmWave-based Human Activity Recognition using Large Simulated Dataset for Model Pretraining. - Vinay Joshi; Shengkai Xu; Qiming Cao; Yi Zhu 012; Pu Wang 001; Hongfei Xue (IEEE Big Data, 2024)

CiMNet: Towards Joint Optimization for DNN Architecture and Configuration for Compute-In-Memory Hardware. - Souvik Kundu 002; Anthony Sarah; Vinay Joshi; Om Ji Omer; Sreenivas Subramoney (CoRR, 2024)

QCQA: Quality and Capacity-aware grouped Query Attention. - Vinay Joshi; Prashant Laddha; Shambhavi Sinha; Om Ji Omer; Sreenivas Subramoney (CoRR, 2024)

TaDA: Training-free recipe for Decoding with Adaptive KV Cache Compression and Mean-centering. - Vinay Joshi; Pratik Prabhanjan Brahma; Zicheng Liu; Emad Barsoum (CoRR, 2025)

Geak: Introducing Triton Kernel AI Agent & Evaluation Benchmarks. - Jianghui Wang; Vinay Joshi; Saptarshi Majumder; Xu Chao; Bin Ding; Ziqiong Liu; Pratik Prabhanjan Brahma; Dong Li; Zicheng Liu; Emad Barsoum (CoRR, 2025)