Invited Speaker



Deep Learning for Big Data Applications - Challenges and Future Directions


Yi Pan, Ph.D.
Regents' Professor and Chair
Department of Computer Science
Georgia State University
Atlanta, Georgia, USA


Abstract:
Due to improvements in mathematical formulas and increasingly powerful computers, we can now model many more layers of virtual neurons (deep neural networks or deep learning) than ever before. Deep learning is now producing many remarkable recent successes in computer vision, automatic speech recognition, natural language processing, audio recognition, and medical imaging processing. Although various deep learning architectures have been applied to many big data applications, extending deep learning into more complicated applications such as bioinformatics will require more conceptual and software breakthroughs, not to mention many more advances in processing power. In this talk, I will outline the challenges and problems in existing deep learning methods when applying it to big data in general and bioinformatics in particular. I will describe a few novel architectures and algorithms recently proposed by us to improve the accuracies and learning speeds of the existing deep learning technologies. These new deep learning architectures and algorithms will be applied to several big data applications including image processing, DNA sequence annotation, long intergenic non-coding RNA detection, and gene structure prediction. The data encoding schemes, the choice of architectures and methods used will be described in details. Performance comparisons with other machine learning and existing deep learning methods will be reported. The experimental results show that deep learning is very promising for many big data applications, but requires selection of suitable models and a lot of tuning to be effective. Future research directions in this exciting area will also be outlined.

Biography:
Yi Pan is currently a Regents' Professor and Chair of Computer Science at Georgia State University, USA. He has served as an Associate Dean and Chair of Biology Department during 2013-2017 and Chair of Computer Science during 2006-2013. He is also a visiting Changjiang Chair Professor at Central South University, China. Dr. Pan received his B.Eng. and M.Eng. degrees in computer engineering from Tsinghua University, China, in 1982 and 1984, respectively, and his Ph.D. degree in computer science from the University of Pittsburgh, USA, in 1991. His profile has been featured as a distinguished alumnus in both Tsinghua Alumni Newsletter and University of Pittsburgh CS Alumni Newsletter. Dr. Pan's research interests include parallel and cloud computing, wireless networks, and bioinformatics. Dr. Pan has published more than 200 journal papers with over 80 papers published in various IEEE journals. In addition, he has published over 150 papers in refereed conferences. He has also co-authored/co-edited 43 books. His work has been cited more than 8000 times. Dr. Pan has served as an editor-in-chief or editorial board member for 15 journals including 7 IEEE Transactions. He is the recipient of many awards including IEEE Transactions Best Paper Award, several other conference and journal best paper awards, 4 IBM Faculty Awards, 2 JSPS Senior Invitation Fellowships, IEEE BIBE Outstanding Achievement Award, NSF Research Opportunity Award, and AFOSR Summer Faculty Research Fellowship. He has organized many international conferences and delivered keynote speeches at over 60 international conferences around the world.