Proceedings of International Joint Conference on Computational Intelligence

Dr. Mohammad Shorif Uddin is a Professor at Jahangirnagar University, Bangladesh. He completed his Master of Technology Education at Shiga University, Japan in 1999, his Doctor of Engineering in Information Science at Kyoto Institute of Technology, Japan, in 2002, and an MBA at Jahangirnagar University in 2013. He is the Editor-in-Chief of ULAB Journal of Science and Engineering, an Associate Editor of IEEE Access, and has served as General Chair or Co-Chair of various conferences, including the IJCCI 2018, EICT 2017 and IWCI 2016. He holds two patents for his scientific inventions, is a senior member of several academic associations, and has published extensively in international journals and conference proceedings. Dr. Jagdish Chand Bansal is an Assistant Professor at South Asian University, New Delhi, India and a Visiting Research Fellow at Liverpool Hope University, UK. A leading researcher in the field of swarm intelligence, he has published numerous research papers in respected national and international journals.

Factorial Analysis of Biological Datasets.- Leveraging Machine Learning Approach to Setup Software Defined Network(SDN) Controller Rules During DDoS Attack.- Routing Protocol Selection for Intelligent Transport System (ITS) of VANET in High Mobility Areas of Bangladesh.- Computer-aided Speckle Noise Analysis in Ultrasound Images through Fusion of Convolutional Neural Network and Wavelet Transform with Linear Discriminate Analysis.- A Machine Learning Approach to Detect Diabetic Retinopathy using Convolutional Neural Network.- Issues of Internet of Things (IoT) and an Intrusion Detection System for IoT Using Machine Learning Paradigm.- D-CARE: A Non-invasive Glucose Measuring Technique for Monitoring Diabetes Patients.- Initial Point Prediction based Parametric Active Contour Model for Left Ventricle Segmentation of CMRI Images.- Vehicle Tracking & Monitoring System for Security Purpose Based on Thermo Electric Generator (TEG).- Developing a Technique for Overcoming the Searching Limitations of Documents.