Amirmohammad Farzaneh is a Lecturer in Engineering Science at Oriel College and a Postdoctoral Research Associate in the Department of Engineering at King’s College London. He received his PhD in Engineering Science from the University of Oxford, and his B.Sc. in Electrical Engineering from Sharif University of Technology, Tehran, Iran.
Amirmohammad’s research lies at the intersection of Information Theory, Artificial Intelligence, and Network Science. His work develops rigorous statistical and information-theoretic tools to assess and guarantee the reliability of AI systems, with particular emphasis on their deployment in high-stakes domains such as engineering, telecommunications, and healthcare. Beyond theoretical foundations, his research also explores practical applications, including hyperparameter selection methods for machine learning, conformal prediction for uncertainty quantification, and counterfactual inference for decision-making under uncertainty. Ultimately, his goal is to establish principled frameworks for building dependable, adaptable, and safe AI systems.
Research Interests
Communication systems, Information theory, Machine learning
Selected Publications
- Farzaneh, Amirmohammad, Justin P. Coon, and Mihai-Alin Badiu. “Kolmogorov basic graphs and their application in network complexity analysis.” Entropy 23.12 (2021): 1604.
- Farzaneh, Amirmohammad, and Justin P. Coon. “An information theory approach to network evolution models.” Journal of Complex Networks 10.3 (2022): cnac020.
- Farzaneh, Amirmohammad, Mihai-Alin Badiu, and Justin P. Coon. “TreeExplorer: a coding algorithm for rooted trees with application to wireless and ad hoc routing.” 2022 IEEE 96th Vehicular Technology Conference (VTC2022-Fall). IEEE, 2022.