M.M.A. Hashem

M.M.A. Hashem

Dr. M.M.A. Hashem received the Bachelor’s degree in Electrical and Electronic Engineering from Khulna University of Engineering and Technology (KUET), Khulna, Bangladesh in 1988, Master’s degree in Computer Science from Asian Institute of Technology (AIT), Bangkok, Thailand in 1993 and PhD degree in Artificial Intelligence Systems from Saga University, Japan in 1999. He received the "Institute Gold Medal" of BIT, Khulna (Now KUET) in recognition of outstanding performance in his Bachelor’s Degree. Currently, He is a Professor in the Dept. of Computer Science and Engineering, Khulna University of Engineering and Technology (KUET), Bangladesh.

His research interest includes Distributed Evolutionary Computations, Intelligent Computer Networking, Grid/Cloud Computing, Wireless Networking, Soft-Computing, Evolutionary Cluster Computing etc. He has published more than 100+ refereed articles in international Journals and Conferences. He is a Life Fellow of Institution of Engineers, Bangladesh (IEB). He is a co-author of a book titled “Evolutionary Computations: New Algorithms and their Applications to Evolutionary Robots”, Series: Studies in Fuzziness and Soft Computing, Vol. 147, Springer-Verlag, Berlin/New York, ISBN: 3-540-20901-8, (2004). He has served as an Organizing Chair, IEEE 2008 11th International Conference on Computer and Information Technology (ICCIT 2008) and Workshops, held during 24-27 December, 2008 at KUET.

He also has worked as a Technical Support Team (TST) Consultant for Bangladesh Research and Education Network (BdREN)--a World Bank Funded Project-- of University Grants Commission (UGC) of Bangladesh from November 3, 2009 to January 31, 2013. His major responsibilities included the design and implementation of countrywide 40G/10G DWDM based Optical Transmission Network using OPGW, 10G IP/MPLS based Data Network, NOC and Private Cloud based Tier-3 Data Center infrastructure, HD VC system based Virtual Classroom and Unified Communication Systems.


Posters: Development of a Novel Computer-Aided COVID-19 Diagnosis System Using Python