ICMLCI 14th-15th, December, 2019

International Conference on Machine Learning and Computational Intelligence

Organized by: IRNet, Bhubaneswar, Odisha, India

Program Committee

Prof. Ishwar Sethi
Department of Computer Science and Engineering, Oakland University, Rochester, USA

Prof. Xin-She Yang
School of Science and Technology, Middlesex University, Hendon Campus, London, UK

Prof. Florin Popenţiu-Vlădicescu
Academy of Romanian Scientists, UNESCO Chair Department, University of Oradea, Romania

Prof. Kazumi Nakamatsu
School of Human Science and Environment, University of Hyogo, Shinzaike-hon-cho, Japan

Prof. Fatos Xhafa
Department of Languages and Informatics Systems, Technical University of Catalonia, Barcelona, Spain

Prof. Madjid Tavana
Professor and Distinguished Chair of Business Analytics, Chairman of the Business Systems and Analytics Department, La Salle University, Philadelphia, Pennsylvania, USA

Prof. Yeon-Mo Yang
National Institute of Technology; School of Electronic Engineering; Gyeongbuk,Gumi; Republic of Korea

Prof. JanuszKacprzyk
Polish Academy of Sciences, Warsaw, Poland

Prof. Lakhmi C. Jain
University of Canberra, Canberra, Australia

Prof. Jae Moon Lee
Hansung University, Republic of Korea

Prof. Baojiang Zhong
School of Computer Science and Technology; Soochow University, Suzhou 215006, China

Prof. Zhengtao Yu
Dean, School of Information Engineering and Automation, Kunming University of Science and Technology, 650500, China.

Dr. Xiaolong Li
Department of Electronics and Computer Engineering Technology, College of Technology, Indiana State University, USA.

Dr. Chan-Su Lee
Associate Professor, Department of Electronic Engineering, Yeungnam University, 280 Daehak-Ro, Gyeongsan, Gyeongbuk 712-749, Rep. of Korea (South Korea)

Prof. Apolloni, Bruno
UniversitàdegliStudi di Milano, Italy

Prof. Chen, Shyi-Ming
National Taiwan University of Science and Technology, Taiwan

Prof. CoulibalyYahaya
University Technology Malaysia, Malaysia

Prof. CuiZhihua
Taiyuan University of Science and Technology, China

Prof.Joseph Davis
The University of Sydney, Australia

Prof. De La EscaleraHueso
Arturo, Universidad Carlos III de Madrid, Spain

Prof. Mohammed ElMohajir
DharMahraz University, Morocco

Prof. AliHessami
Vega Systems, UK

Prof. Yen-TsengHsu
National Taiwan University of Science and Technology, Taiwan

Prof. Lakhmi C Jain
Bournemouth University, UK

Prof.Sanjay Jain
National University of Singapore, Singapore

Prof. Chidananda Khatua
Intel Corporation Inc., USA

Prof. AyseKiper
Middle East Technical University, Turkey

Prof.Ladislav J Kohout
Florida State University, USA

Prof.Abderrafiaa Koukam
Université de Technologie de Belfort Montbéliard, France

Prof. RezaLangari
Texas A&M University, USA

Prof. FengLiu
Wuhan University, China

Prof. MaodeMa
Nanyang Technological University, Singapore

Prof. N. P. Mahalik
California State University, Fresno, USA

Prof.Rabi N. Mahapatra
Texas A&M University, USA

Prof. Subhas CMisra
IIT Kanpur, India

Prof. PabitraMitra
Indian Institute of Technology Kharagpur, India

Gloria, Loyola University Maryland, USA

Prof.P. Krishna Reddy
International Institute of Information Technology, India

Prof.M. AdelSerhani
United Arab Emirates University, United Arab Emirates

Prof.M. HassanShafazand
ShahidBahonar University of Kerman, Iran

Prof. Tony C. Shan
Wachovia Bank, USA

Prof.Anupam Shukla
Indian Institute of Information Technology and Management, Gwalior (ABV-IIITM), India

Prof. PedroSoto Acosta
University of Murcia, Spain

Prof. RobertTrappl
Austrian Research Institute for Artificial Intelligence (OFAI), Austria

National Technical University, Greece

Auckland University of Technology, New Zealand

Nanjing Normal University, China

University of Trento, Italy

Sponsored by

IIMT, Bhubaneswar (INDIA)



Publication Partners
Submission Guidelines
  • The submissions may be of any form out of the following:
  • New algorithms with empirical, theoretical, psychological, or biological justification.
  • Experimental and/or theoretical studies yielding new insight into the design and behavior of learning in intelligent systems.
  • Applications of existing techniques that shed light on the strengths and weaknesses of the methods.
  • New learning tasks (e.g., in the context of new applications) and of methods for assessing performance on those tasks.
  • Development of new analytical frameworks that advance theoretical studies of practical learning methods.
  • Computational models of data from natural learning systems at the behavioral or neural level; or extremely well-written surveys of existing work.

Interscience Institute of Management Technology
Kantabada, Bhubaneswar, India

knowledge management