Energy-aware Adaptive Approximate Computing for Deep Learning Applications. - Nima TaheriNejad; Salar Shakibhamedan (ISVLSI, 2022)

OPTIMA: Design-Space Exploration of Discharge-Based In-SRAM Computing: Quantifying Energy-Accuracy Trade-offs. - Saeed Seyedfaraji; Severin Jager; Salar Shakibhamedan; Asad Aftab; Semeen Rehman (DAC, 2024)

RecogNoise: Machine-Learning-Based Recognition of Noisy Segments in Electrocardiogram Signals. - Amin Aminifar; Soheil Khooyooz; Anice Jahanjoo; Salar Shakibhamedan; Nima TaheriNejad (ISCAS, 2024)

Harnessing Approximate Computing for Machine Learning. - Salar Shakibhamedan; Amin Aminifar; Luke Vassallo; Nima TaheriNejad (ISVLSI, 2024)

IMPLY-based Approximate Full Adders for Efficient Arithmetic Operations in Image Processing and Machine Learning. - Melanie Qiu; Caoyueshan Fan; Gulafshan; Salar Shakibhamedan; Fabian Seiler; Nima TaheriNejad (CoRR, 2024)

Adaptive approximate computing in edge AI and IoT applications: A review. - Hans Jakob Damsgaard; Antoine Grenier; Dewant Katare; Zain Taufique; Salar Shakibhamedan; Tiago Troccoli; Georgios Chatzitsompanis; Anil Kanduri; Aleksandr Ometov; Aaron Yi Ding; Nima Taherinejad; Georgios Karakonstantis; et al. (J. Syst. Archit., 2024)

ACE-CNN: Approximate Carry Disregard Multipliers for Energy-Efficient CNN-Based Image Classification. - Salar Shakibhamedan; Nima Amirafshar; Ahmad Sedigh Baroughi; Hadi Shahriar Shahhoseini; Nima TaheriNejad (IEEE Trans. Circuits Syst. I Regul. Pap., 2024)

FairTabGen: Unifying Counterfactual and Causal Fairness in Synthetic Tabular Data Generation. - Nitish Nagesh; Salar Shakibhamedan; Mahdi Bagheri; Ziyu Wang; Nima TaheriNejad; Axel Jantsch; Amir M. Rahmani (CoRR, 2025)