Vahid Seydi is a Research Fellow in the School of Ocean Science at Bangor University in Data Science (DS) and Machine Learning (ML). Prior to Bangor, Vahid was an Assistant Professor at the Department of AI at Azad University South Tehran Branch (Feb 2014 - Sep 2020) and was an award-winning lecturer (Oct 2010 – Feb 2014). He received a B.Sc.(2005) in software engineering, M.Sc. (2007) and PhD(2014) in AI, from the Department of Computer Science at Science and Research University, Tehran Iran. He has been awarded Global Talen endorsement from the UK Royal Society (2023); his current research fellowship(2020); a merit-based scholarship for attending the school of AI, Rome, Italy(2019); a full scholarship Award from Azad University(2010-2014); and KNTU ISLAB Research Fellowship (2007-2010). Throughout his studies, he consistently achieved grades above 18 out of 20 in nearly all modules, and I often secured the first-ranked student. He possesses 15 years of extensive experience in diverse areas of Data Science (DS) and Machine Learning (ML). (university homepage)

Research Interests

Academic Positions

  • Sep 2020-present

    Research fellow in Data Science

    School of Ocean Sciences, Bangor Universirt (Bangor, UK)

  • Apr 2019-Jun 2019

    Machine Learning Expert and Data Scientist

    Pi Campus, (Rome, Italy)

  • Oct 2017-Apr 2019

    Head of Department of AI

    Azad University,South Tehran Branch, (Tehran, Iran)

  • Feb 2014-Sep 2021

    Assistant professor in AI Department

    Azad University, South Tehran Branch, (Tehran, Iran)

  • Oct 2010-Feb 2014

    Lecturer in Computer Eng. Department

    Azad University, South Tehran Branch, (Tehran, Iran)

  • Oct 2007-Jun 2010

    Research Fellowship

    KNTU, ISLAB (Tehran, Iran)


  • September 2007-February 2014

    Ph.D. in Artificial intelligence

    Azad University, Science and Research Branch, Tehran Iran

    Jobs interaction theory to train hyper-parameters of the cultural optimization algorithm.

    professor Mohammad Teshnehlab.



    cultural optimization algorithm, neural network, multi-agent system, derivative-free learning algorithm, feature extraction.

  • September 2005-September 2007

    M.Sc in Artificial intelligence

    multi-objective optimization to train neural networks and neuro-fuzzy systems.

    professor Mohammad Teshnehlab.



    multi-objective optimization, neural network and fuzzy system, combination of both derivative-base and derivative-free learning algorithms to prevent vanishing and exploding of gradient, and overfitting.

  • September 2001-July 2005

    B.Sc. in Computer Software Engineering

    implementation of an automation system for the dairy industry.



    RUP methodology,data base management, SQL, object oriented programing, designing algorithm, data structure, Java, Visual C++.





Machine Learning

Mining of Massive Data Sets

Advanced Artificial Intelligence (Reinforcement learning and PGM)

Artificial Neural Networks

Natural Language Processing



Artificial Intelligence(Search, CSP, Adversarial Search, Logic Programming)

Foundation of Programming(C / Python)

Object-Oriented Programming(Java)

formal language and automata theory


Python Java C/C++ MATLAB ProLog react

PyTorch, Keras, TensorFlow, Gensim, NLTK, NumPy, Pandas, SiKit-Learn, SciPy, Scrapy, Matplotlib, Seaborn, ...