Full name: Seyed Jalaleddin Mousavirad (in short: Jalal, and in Persian: سید جلال الدین موسوی راد).

Independent Consultant and Researcher on Optimization, Machine Learning, and Image Processing

Research Interests:
     Computational Intelligence
     Evolutionary Computation
     Large-Scale Optimization
     Multi-objective Optimization
     Pattern Recognition and Machine Learning
     Image Processing

My pages on other websites:

Linkedin, Researchgate, Publons, Academia, Google Scholar

Recent Updates:

[23/04/2021] Accepted paper in ICONIP2021

Our paper entitled ” An LSTM-based Plagiarism Detection via Attention Mechanism and a Population-based Approach for Pre-Training Parameters with imbalanced Classes” is accepted at The 28th International Conference on Neural Information Processing (ICONIP2021), BALI, Indonesia.

[23/03/2021] Accepted paper in SMC2021

Our paper entitled ” An Enhanced Differential Evolution Algorithm Using a Novel Clustering-based Mutation Operator” is accepted at IEEE International Conference on Systems, Man, and Cybernetics (IEEE SMC 2021), Melbourne, Australia, 2021

[7/14/2021] A newly published book chapter

Our book chapter entitled “Optimising Connection Weights in Neural Networks Using a Memetic Algorithm Incorporating Chaos Theory” is published as a chapter of springer book entitled ” Metaheuristics in Machine Learning: Theory and Applications

[20/06/2021] Two accepted papers in GECCO2021!

The titles are as follows:

  1. HCS-BBD: an effective population-based approach for multi-level thresholding
  2. A population-based automatic clustering algorithm for image segmentation

[23/04/2021] Accepted paper in Expert System with Applications.

Our paper entitled “An Efficient Method to Minimize Cross-Entropy for Selecting Multi-Level Threshold Values using an Improved Human Mental Search Algorithm” is accepted for inclusion in Expert System With Application (IF=6.95).

[13/04/2021] Accepted paper in CEC2021!

Our paper entitled ” Differential Evolution-based Neural Network Training Incorporating a Centroid-based Strategy and Dynamic Opposition-based Learning” is accepted on IEEE Congress on Evolutionary Computation (CEC2021), Krakow, Poland.

[20/01/2021] Accepted paper in EvoApps2021!

Our paper entitled ” RDE-OP: A Region-based Differential Evolution Algorithm Incorporation Opposition-Based Learning for Optimising the Learning Process of Multi-Layer Neural Networks” is accepted on 24th International Conference on the Applications of Evolutionary Computation, Seville, Spain

[04/11/20] Two accepted paper in IEEE Symposium Series on Computational Intelligence (SSCI2020), Canberra, Australia

The titles are as below.

  1. Evolving Feedforward Neural Networks Using a Quasi-Opposition-Based Differential Evolution for Data Classification

2. Enhancing SHADE and L-SHADE Algorithms Using Ordered Mutation

[24/10/2020] Accepted paper in ICPR2020.

Our paper entitled “An Effective Approach for Neural Network Training Based on Comprehensive Learning ” is accepted in 25th International Conference on Pattern Recognition (ICPR2020), Milan, Italy.

[13/10/2020] Accepted paper in ICONIP2021!

Our paper entitled “Neural Network Training using a Biogeography-based Learning Strategy” is accepted in 27th International Conference on Neural Information Processing (ICONIP2021), Bangkok, Thailand.

[30/09/2020] Four Accepted Papers in International Conference on Systems, Man, and Cybernetics (SMC), Toronto, Canada.

The titles are as follows.

CenPSO: A Novel Center-based Particle Swarm Optimization Algorithm for Large-scale Optimization

One-array Differential Evolution Algorithm with a Novel Replacement Strategy for Numerical Optimization

Towards Solving Large-scale Expensive Optimization Problems Efficiently Using Coordinate Descent Algorithm

Colour Quantisation using Human Mental Search and Local Refinement

[28/09/2020] Accepted paper in ICCKE conference

Our paper entitled “An Evolutionary Hybrid Feature Selection Approach for Biomedical Data Classification” has been accepted in The International Conference on Computer and Knowledge Engineering (ICCKE), Mashhad, Iran.

[26/09/2020] A New Published Book Chapter

Our book chapter entitled “The Human Mental Search Algorithm for Solving Optimisation Problems” is published as a chapter of springer book entitled ” Enabling AI Applications in Data Science

[11/08/2020] A New Published Paper

Our new paper entitled “Automated Clustering Using a Local-Search-based Human Mental Search for Image Segmentation” is published in Applied Soft Computing.

[08/05/2020] Five accepted papers in The Genetic and Evolutionary Computation Conference (GECCO2020) in Cancun, Mexico.

Titles are as follows:

1) A Benchmark of Recent Population-Based Metaheuristic Algorithms for Multi-Layer Neural Network Training

2) High-Dimensional Multi-Level Maximum Variance Threshold Selection for Image Segmentation: A Benchmark of Recent Population-based Metaheuristic Algorithms

3) High-Dimensional Multi-Level Image Thresholding using Self-Organizing Migrating Algorithm

4) Colour Quantisation using Self-Organizing Migrating Algorithm

5) Effective Image Clustering using Self-Organizing Migrating Algorithm

[17/04/2020] Two accepted papers in The Eleventh International Conference on Swarm Intelligence (ICSI 2020) , Belgrade, Serbia.

  1. A Novel Image Segmentation Based on Clustering and Population-Based Optimisation
  2. Colour Quantisation by Human Mental Search

[21/3/2020] Three accepted papers in IEEE World Congress on Computational Intelligence (WCCI2020), Glasgow, UK.

1. On Improvements of the Human Mental Search Algorithm for Global Optimisation

2. A Novel Center-based Differential Evolution Algorithm

3. Many-level Image Thresholding using a Center-Based Differential Evolution Algorithm

[01/20/2020] Scientific Committee Member in MVIP2020

It is my honour to select as a Scientific Committee Member in the 11-th Iranian and the First International Conference on Machine Vision and Image Processing (MVIP2020 ), Tehran University, Iran.