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Citations & Research

FEAGI (Framework for Evolutionary Artificial General Intelligence) is grounded in peer-reviewed research published across IEEE and ACM journals and conferences. If you use FEAGI in academic work, please cite the relevant paper(s) below. Each entry links to its publisher DOI landing page and includes a ready-to-use BibTeX entry.

A Brain-Inspired Framework for Evolutionary Artificial General Intelligence

M. Nadji-Tehrani and A. Eslami

IEEE Transactions on Neural Networks and Learning Systems

vol. 31, no. 12, pp. 5257–5271, Dec. 2020 — DOI: 10.1109/TNNLS.2020.2965567
Keywords: evolutionary algorithms, genetic programming, indirect encoding, spiking neural networks
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@article{nadji2020brain,
  title   = {A Brain-Inspired Framework for Evolutionary Artificial General Intelligence},
  author  = {Nadji-Tehrani, Mohammad and Eslami, Ali},
  journal = {IEEE Transactions on Neural Networks and Learning Systems},
  volume  = {31},
  number  = {12},
  pages   = {5257--5271},
  year    = {2020},
  doi     = {10.1109/TNNLS.2020.2965567},
  publisher = {IEEE}
}

FEAGI: A Deterministic and Composable Neuromorphic Framework

S. S. Mondal, M. Nadji-Tehrani and H. Das

2026 IEEE 19th Dallas Circuits and Systems Conference (DCAS)

Dallas, TX, USA, 2026, pp. 1–4 — DOI: 10.1109/DCAS69364.2026.11544706
Keywords: composable cognitive architectures, deterministic execution, audit and replay, hardware export, ASIC co-design, real-time systems
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@inproceedings{mondal2026feagi,
  title     = {FEAGI: A Deterministic and Composable Neuromorphic Framework},
  author    = {Mondal, Soumik Sarkar and Nadji-Tehrani, Mohammad and Das, Hrishikesh},
  booktitle = {2026 IEEE 19th Dallas Circuits and Systems Conference (DCAS)},
  pages     = {1--4},
  year      = {2026},
  doi       = {10.1109/DCAS69364.2026.11544706},
  organization = {IEEE}
}

A Homeostatic Plasticity-Enabled CMOS Neuron for Energy-Efficient Neuromorphic Application

S. S. Mondal, M. Nadji-Tehrani, M. H. Kabir, N. N. Chakraborty and H. Das

Proceedings of the Great Lakes Symposium on VLSI 2026 (GLSVLSI '26)

Canandaigua, NY, USA, 2026, pp. 790–795 — DOI: 10.1145/3787109.3816390
Keywords: homeostatic plasticity, CMOS neuron, neuromorphic computing, energy efficiency
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@inproceedings{mondal2026homeostatic,
  title     = {A Homeostatic Plasticity-Enabled CMOS Neuron for Energy-Efficient Neuromorphic Application},
  author    = {Mondal, Soumya Swaraj and Nadji-Tehrani, Mohammad and Kabir, Md Humaun and Chakraborty, Nishith Nirjhar and Das, Hritom},
  booktitle = {Proceedings of the Great Lakes Symposium on VLSI 2026},
  pages     = {790--795},
  year      = {2026},
  doi       = {10.1145/3787109.3816390},
  address   = {Canandaigua, NY, USA},
  publisher = {ACM}
}

A Configurable CPG Controller using Connectome based SNN on FPGA for Robot Locomotion

J. Ereifej, K. Araujo, M. Nadji-Tehrani, and R. Kubendran

2024 IEEE International Conference on Rebooting Computing (ICRC)

pp. 1–7, IEEE, 2024 — DOI: 10.1109/ICRC64395.2024.10937017
Keywords: CPG, connectome, SNN, FPGA, robot locomotion
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@inproceedings{ereifej2024cpg,
  title     = {A Configurable CPG Controller using Connectome based SNN on FPGA for Robot Locomotion},
  author    = {Ereifej, Joseph and Araujo, Kevin and Nadji-Tehrani, Mohammad and Kubendran, Rajkumar},
  booktitle = {2024 IEEE International Conference on Rebooting Computing (ICRC)},
  pages     = {1--7},
  year      = {2024},
  doi       = {10.1109/ICRC64395.2024.10937017},
  organization = {IEEE}
}