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Address 1 :
Address 2 :
Title : Dr.
First Name : AMIR H
Last Name : GANDOMI
Email ID : [email protected]
Country : United States
State : New jersey
Zipcode : 07030
Department : School of Business
Area of Research
Data Mining and Optimization
Area of Expertise
Brief Description of Research Interest :

1. Data Mining/ Data Interpretation

2. Big Data Analysis 

3. Artificial Intelligence

4. Evolutionary Computation

5. Large-Scale Optimization

6. Statistical and Probabilistic Methods

Publisher's Note:

Dr. Gandomi has published over one hundred and thirty journal papers and four books. Some of those publications are now among the hottest papers in the field and collectively have been cited more than 8,500 times (h-index = 47). Recently, he was recognized as the Highly Cited Researcher (top 1%) for 2017, and one of the most influential minds in the world. Dr. Gandomi is currently ranked 20th in GP bibliography among more than 10,000 researchers. He has also served as associate editor, editor and guest editor in several prestigious journals and has delivered several keynote/invited talks. Dr Gandomi is part of a NASA technology cluster on Big Data, Artificial Intelligence, and Machine Learning. His research interests are global optimization and (big) data mining using machine learning and evolutionary computations in particular.

Representative Publications :

Gandomi, A. H., & Goldman, B. W. (2018). Parameter-less population pyramid for large-scale tower optimization. Expert Systems with Applications96, 175-184.

Gandomi, A. H., & Kashani, A. R. (2018). Construction Cost Minimization of Shallow Foundation Using Recent Swarm Intelligence Techniques. IEEE Transactions on Industrial Informatics, 14(3),1099-1106.

Mirjalili, S., Gandomi, A. H., Mirjalili, S. Z., Saremi, S., Faris, H., & Mirjalili, S. M. (2017). Salp swarm algorithm: a bio-inspired optimizer for engineering design problems. Advances in Engineering Software114, 163-191.

Gandomi, A. H., Kashani, A. R., Roke, D. A., & Mousavi, M. (2017). Optimization of retaining wall design using evolutionary algorithms. Structural and Multidisciplinary Optimization55(3), 809-825.