| 2023 | ICLR | ZiCo: Zero-shot NAS via inverse Coefficient of Variation on Gradients. | Guihong Li, Yuedong Yang, Kartikeya Bhardwaj, Radu Marculescu |
| 2023 | ICML | TIPS: Topologically Important Path Sampling for Anytime Neural Networks. | Guihong Li, Kartikeya Bhardwaj, Yuedong Yang, Radu Marculescu |
| 2022 | DATE | Super-Efficient Super Resolution for Fast Adversarial Defense at the Edge. | Kartikeya Bhardwaj, Dibakar Gope, James Ward, Paul N. Whatmough, Danny Loh |
| 2021 | CVPR | How Does Topology Influence Gradient Propagation and Model Performance of Deep Networks With DenseNet-Type Skip Connections? | Kartikeya Bhardwaj, Guihong Li, Radu Marculescu |
| 2020 | CVPR | A Hardware Prototype Targeting Distributed Deep Learning for On-device Inference. | Allen-Jasmin Farcas, Guihong Li, Kartikeya Bhardwaj, Radu Marculescu |
| 2020 | DAC | INVITED: New Directions in Distributed Deep Learning: Bringing the Network at Forefront of IoT Design. | Kartikeya Bhardwaj, Wei Chen, Radu Marculescu |
| 2020 | ICASSP | On Network Science and Mutual Information for Explaining Deep Neural Networks. | Brian Davis, Umang Bhatt, Kartikeya Bhardwaj, Radu Marculescu, Jos M. F. Moura |
| 2018 | PAKDD | Dimensionality Reduction via Community Detection in Small Sample Datasets. | Kartikeya Bhardwaj, Radu Marculescu |
| 2017 | DIS | Discovering Hidden Knowledge in Carbon Emissions Data: A Multilayer Network Approach. | Kartikeya Bhardwaj, HingOn Miu, Radu Marculescu |
| 2013 | VLSID | K-Algorithm: An Improved Booth's Recoding for Optimal Fault-Tolerant Reversible Multiplier. | Kartikeya Bhardwaj, Bharat M. Deshpande |