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Dr Ali Ghoroghi

Dr Ali Ghoroghi

Research Fellow

School of Engineering


Dr. Ghoroghi is working as a research fellow at the BRE Trust Centre for Sustainable Engineering Centre. His work focuses on forecasting and optimisation models using Artificial Intelligence.

Dr. Ghoroghi is an industrial engineer and computer scientist with over two decades of experience in technical, managerial and academic roles. He holds a BSc in Industrial Engineering from Tehran Amirkabir University of Technology. He also holds two MSc qualifications in both Industrial Engineering and Computer Science from Esfehan University of Technology and Imperial College respectively. Dr. Ghoroghi then obtained his PhD in Computer Science from Imperial College with a thesis in the field of Game Theory. He has held different teaching, supervision and research roles in academia over the years.

Dr. Ghoroghi's research interests include:

  • Forecasting
  • Supply Chain Management
  • Modelling, Simulation & Optimisation
  • Game Theory
  • Artificial Intelligence & Multi-agent Systems


Dr Ghoroghi obtained a BSc in Industrial Engineering in 1992 at Amirkabir University of Technology, Tehran. He then went onto obtain a masters at Esfahan University of Technology before beginning a career in the industry at Bahman Manufacturing Co. where he worked various roles from both technical and managerial. He innovated, planned and implemented Quality Assurance during his time there and redesigned assembly lines for the factory. He was also involved in technology transfers abroad (Cuba) and set up networks for engineering students to be able to gain valuable work experience in the industry. He was also a board member at Saipa Glass Co and later became a management consultant to Bahman Manufacturing Co.

During this time, Dr Ghoroghi was also teaching at the University of Science and Culture where he later became Head of the Industrial Engineering department and a Professor Assistant. In 2008, he came to the UK to pursue a PhD, before changing his field from industrial engineering to computer science and moving to Imperial College. From there he obtained an MSc and a PhD focusing on Game Theory and began teaching short crash courses in Iran while being involved in research in the UK.

Dr Ghoroghi is passionate about research, teaching and collaborations with industry in pioneering projects.


Dr. Ghoroghi has over two decades of experience in academia  He then taught at the School of Engineering, University of Science and Culture in Iran where he later became professor assistant.

Courses he has taught include:

  • University of Science and Culture, Tehran:
    • Artificial Intelligence, Simulation in Logistics, Management Information Systems, Simulation and Stochastic Models, Operations Research, Engineering Statistics, Engineering Economics,  Information Technology, Principal of Management, Human Factors or Ergonomics,  Statistical Quality Control, Quality Management. 
  • Islamic Azad University, Tehran:
    • Operations Research

Recent Publications and Talks from Dr. Ghoroghi include:

* Ghoroghi, Ali, Ioan Petri, Yacine Rezgui, and Ateyah Alzahrani  (forthcoming). “Prediction of cold room energy consumption and temperature: A neural network approach”. In: IEEE Transactions on Cybernetics.
* Abedinzadeh, Setareh, Ali Ghoroghi, and Hamid Reza Erfanian (2020). “Application of Hybrid GA-SA Heuristic for
Green Location Routing Problem with Simultaneous Pickup and Delivery”. In: Advances 1.1, pp. 1–10. doi:
* Alzahrani, Ateyah et al. (June 2020a). “Developing Smart Energy Communities around Fishery Ports: Toward
Zero-Carbon Fishery Ports”. In: Energies 13.11, pp. 1–22.
* Abedinzadeh, S., A. Mostofi, and A. Ghoroghi (2018). “Application of hybrid GA-SA heuristic for green location routing problem with simultaneous pickup and delivery”. In: 48th International Conference on Computers and Industrial Engineering (CIE48). Auckland, New Zealand.
* Edalat, A., S. Hossein Ghorban, and A. Ghoroghi (2018). “Multi-games for Decision Making in Multi-environments”. Journal of Games, (forthcoming).
* Abedinzadeh, S., S. Afshar, and A. Ghoroghi (2017). “A Two-Echelon Green Supply Chain with Simultaneous Pickup and Delivery”. In: International Journal of Transportation Engineering and Technology (IJTET) 3, pp. 12–18.
* Edalat, A., S. Hossein Ghorban, and A. Ghoroghi (2017). “Multi-games for Decision Making in Multi-environments”. In: MLSE. Maastricht University, Netherlands.
* Rafiefar, N. and A. Ghoroghi (2017a). “An efficient helicopter routing model for location and storage optimisation in Tehran’s earthquake disasters”. In: The first International Congress on Engineering Science (NCIES017). Shiraz, Iran.
* – (2017b). “Application of genetic algorithm for location routing problem with simultaneous pickup & delivery in emergencies”. In: The first national Conference on Applied Researches in Science and Engineering Science. Mashhad, Iran.
* Ghoroghi, A. (2015a). “Multi-Games and Bayesian Nash Equilibria”. PhD thesis. Imperial College London, UK.
* – (2015b). “Multi-Games and Bayesian Nash Equilibria”. Logic Seminar. Imperial College London, UK.
* Edalat, A. and A. Ghoroghi (2013a). Multi-Games. Poster presented at Imperial College London Google competition, UK.
* – (2013b). Multi-Games. Invited talk, Imperial College London Graduate School’s Summer Research Symposium, UK.
* Edalat, A., A. Ghoroghi, and G. Sakellariou (2012). “Multi-Games and a double game extension of the Prisoner’s
Dilemma”. In: 10th Conference on Logic, the Foundations of Game, and Decision Theory (LOFT). Seville, Spain.

Thesis Title: Multi-Games and Bayesian Nash Equilibria
* Proposed a new class of games, called Multi-Games. A Multi-game is one in which a given number of players play a fixed finite number of basic games simultaneously. The basic games in a multi-game can be regarded as different environments for the players. Furthermore, when the players’ weights for different games in the multi-game are classed as private information or as types with given conditional probability distributions. From this, a class of Bayesian games was obtained. The main contribution of this research was to illustrate how, for the class of so-called completely pure regular multi- games with
finite sets of types, the Nash equilibria of the basic games can be used to compute a Bayesian Nash equilibrium in multi-games, with complexity independent of the number of types.

Areas of expertise