| 2021 | AISTATS | Associative Convolutional Layers. | Hamed Omidvar, Vahideh Akhlaghi, Hao Su, Massimo Franceschetti, Rajesh K. Gupta |
| 2019 | DATE | Accelerating Local Binary Pattern Networks with Software-Programmable FPGAs. | Jeng-Hau Lin, Atieh Lotfi, Vahideh Akhlaghi, Zhuowen Tu, Rajesh K. Gupta |
| 2018 | DAC | LEMAX: learning-based energy consumption minimization in approximate computing with quality guarantee. | Vahideh Akhlaghi, Sicun Gao, Rajesh K. Gupta |
| 2018 | DATE | Energy-efficient neural networks using approximate computation reuse. | Xun Jiao, Vahideh Akhlaghi, Yu Jiang, Rajesh K. Gupta |
| 2018 | ISCA | SnaPEA: Predictive Early Activation for Reducing Computation in Deep Convolutional Neural Networks. | Vahideh Akhlaghi, Amir Yazdanbakhsh, Kambiz Samadi, Rajesh K. Gupta, Hadi Esmaeilzadeh |
| 2016 | DATE | Resistive Bloom filters: From approximate membership to approximate computing with bounded errors. | Vahideh Akhlaghi, Abbas Rahimi, Rajesh K. Gupta |
| 2013 | DATE | An efficient network on-chip architecture based on isolating local and non-local communications. | Vahideh Akhlaghi, Mehdi Kamal, Ali Afzali-Kusha, Massoud Pedram |