The Speakers

Prof. Ajay Gupta

Western Michigan University, Kalamazoo, MI

Ajay Gupta is a Professor of Computer Science at Western Michigan University. He is quite active in IEEE-Computer Society being the Vice-Chair of the Technical Activities Committees in 2015-2016 and elected twice as the Chair of the Technical committee on Parallel Processing from 2011 to 2015. From 1998 to 2002, he was the Chairman of the Computer Science Department at Western Michigan University. Dr. Gupta received his Ph.D. in Computer Science from Purdue University in 1989, his M.S. in Mathematics and Statistics from the University of Cincinnati in 1984, and his B.E. (Honors) in Electrical and Electronics Engineering from Birla Institute of Technology and Sciences, Pilani, India in 1982.

Keynote Title: High Performance and Big Data Proteogenomics: Challenges and Opportunities

Proteogenomics is an area of systems biology research at the interface of proteomics and genomics. Thanks to the emergence of high-throughput next generation sequencing technologies such as RNA-Seq and dramatic improvements in the depths and throughput of mass spectrometry-based proteomics, the pace of proteogenomics computational research has greatly accelerated. Analyzing mass spectrometry-based proteomics data using customized protein sequence databases, for example, enables the discovery of novel peptides, provides peptide-level evidence of gene expression, and assists in refining gene models.

Dr. Al-Sakib Khan Pathan

Southeast University, Bangladesh

Al-Sakib Khan Pathan received PhD degree in Computer Engineering in 2009 from Kyung Hee University, South Korea and B.Sc. degree in Computer Science and Information Technology from Islamic University of Technology (IUT), Bangladesh in 2003. He is currently an Associate Professor at the Computer Science and Engineering department, Southeast University (SEU), Bangladesh. He is a recipient of several awards/best paper awards and has several notable publications in these areas.

Keynote Title: Can we rely on Blockchain?

Blockchain is a relatively new technology in the field of Information and Communication Technology. Though the term is frequently used by many, there is some clear knowledge gap about it among general readers and learners. While some researchers are often citing it for their research works and linking it with many of their works, some confusion about it still remains. Some users are suggesting using it for regular businesses and financial transactions though they may not understand it fully. There is some difference between the terms 'security' and 'trust' but they are very much interrelated. Hence, we need to know what are the implications of these terms on Blockchain technology. In this talk, we would explore the basics of Blockchain and then would try to assess whether such a technology could be trusted or relied upon especially when financial issues and transactions are associated with this. As finance is very sensitive area that can directly impact the livelihood of human beings or business organizations, we need to know how reliable this technology is and what has been achieved so far.

Phayung Meesad

King Mongkut’s University of Technology, Bangkok, Thailand

Phayung Meesad currently is an Associate Professor at the Faculty of Information Technology, King Mongkut’s University of Technology North Bangkok (KMUTNB), Thailand. He also serves as the Dean of the Faculty of Information Technology at KMUTNB. His research of interests are Business Intelligence, Computational Intelligence, Artificial Intelligence, Machine Learning, Deep Learning, Data Analytics, Data Science, Data Mining, Digital Signal Processing, Image Processing, Time Series Analysis, and Natural Language Processing. He has been general chair and co-chair of many international conferences.

Keynote Title: Trends of Deep Learning for Big Data and Applications

Due to the implementation of Internet of Things and storage capability, Big Data are exponentially increased. It is very crucial that Big Data must be analyzed and drawn the hidden knowledge for further decision support. Machine Learning play an important role in knowledge extraction from data for decision-making and control. In particular, Deep Learning will play an important role for to learn from Big Data. Deep Learning has been extremely successful in many fields such as image processing and natural language processing. This talk gives brief reviews about trends of deep learning for big data and applications. Convolutional Neural Network, Recurrent Neural Network, Long Short- Term Neural Network, Gated Recurrent Unit will be covered.