A Two-Stage Approximation Methodology for Efficient DNN Hardware Implementation
A.H. Hadipour, A. Jafari, M. Awais, M. Platzner, in: 2025 IEEE 28th International Symposium on Design and Diagnostics of Electronic Circuits and Systems (DDECS), IEEE, 2025.

DeepApprox: Rapid Deep Learning based Design Space Exploration of Approximate Circuits via Check-pointing
M. Awais, H. Ghasemzadeh Mohammadi, M. Platzner, in: To Apear in IEEE ISVLSI 2024, 2024.

LDAX: A Learning-based Fast Design Space Exploration Framework for Approximate Circuit Synthesis
M. Awais, H. Ghasemzadeh Mohammadi, M. Platzner, in: Proceedings of the ACM Great Lakes Symposium on VLSI (GLSVLSI) 2021, ACM, 2021, pp. 27–32.

MCTS-Based Synthesis Towards Efficient Approximate Accelerators
M. Awais, M. Platzner, in: Proceedings of IEEE Computer Society Annual Symposium on VLSI, IEEE, 2021, pp. 384–389.

A Hybrid Synthesis Methodology for Approximate Circuits
M. Awais, H. Ghasemzadeh Mohammadi, M. Platzner, in: Proceedings of the 30th ACM Great Lakes Symposium on VLSI (GLSVLSI) 2020, ACM, 2020, pp. 421–426.

CIRCA: Towards a Modular and Extensible Framework for Approximate Circuit Generation
L.M. Witschen, T. Wiersema, H. Ghasemzadeh Mohammadi, M. Awais, M. Platzner, Microelectronics Reliability 99 (2019) 277–290.

CIRCA: Towards a Modular and Extensible Framework for Approximate Circuit Generation
L.M. Witschen, T. Wiersema, H. Ghasemzadeh Mohammadi, M. Awais, M. Platzner, Third Workshop on Approximate Computing (AxC 2018) (n.d.).

An MCTS-based Framework for Synthesis of Approximate Circuits
M. Awais, H. Ghasemzadeh Mohammadi, M. Platzner, in: 26th IFIP/IEEE International Conference on Very Large Scale Integration (VLSI-SoC), 2018, pp. 219–224.