Proceedings of Academia-Industry Consortium for Data Science

This book gathers high-quality papers presented at Academia-Industry Consortium for Data Science (AICDS 2020), held in Wenzhou, China during 19 20 December 2020. The book presents views of academicians and also how companies are approaching these challenges organizationally. The topics covered in the book are data science and analytics, natural language processing, predictive analytics, artificial intelligence, machine learning, deep learning, big data computing, cognitive computing, data visualization, image processing, and optimization techniques.

Presents research works in the field of intelligent systems and data science Discusses results of AICDS 2020 held in Wenzhou, China Serves as a reference for researchers and practitioners in academia and industry

Auteur

Dr Gaurav Gupta is an Assistant Professor and Department Chair of Mathematics at the Wenzhou-Kean University, Wenzhou, China. He is having 13 years of teaching and research experience. From 2007-2010, he worked for Indian Space Research Organization (ISRO). He obtained more than $120,000 in grant funding from Wenzhou-education bureau. His research focus is in the area of Data Analytics, Image Processing, Computer vision and soft Computing. Dr. Gupta has published 31 research papers in reputed journals and conferences. He has guided two PhD students, 9 Masters Dissertations and 3 undergraduate Projects. He has participated and contributed in many conferences and workshops as keynote speaker, technical committee and session chair.

Dr Lipo Wang received a Bachelor degree from National University of Defense Technology (China) and PhD from Louisiana State University (USA). He is presently on the faculty of the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore. His research interest is an artificial intelligence with applications to image/video processing, biomedical engineering, and data mining. He has 340+ publications, a U.S. patent in neural networks and a patent in systems. He has co-authored 2 monographs and (co-)edited 15 books. He has 8,800+ Google Scholar citations, with H-index 43. He was a keynote speaker for 36 international conferences. He is/was Associate Editor/Editorial Board Member of 30 international journals, including 4 IEEE Transactions, and guest editor for 10 special journal issues. He was a member of the Board of Governors of the International Neural Network Society, IEEE Computational Intelligence Society (CIS), and the IEEE Biometrics Council. He served as CIS Vice President for Technical Activities and Chair of Emergent Technologies Technical Committee, as well as Chair of Education Committee of the IEEE Engineering in Medicine and Biology Society (EMBS). He was President of the Asia-Pacific Neural Network Assembly (APNNA, recently renamed as APNNS - "Society") and received the APNNA Excellent Service Award. He was founding Chair of both the EMBS Singapore Chapter and CIS Singapore Chapter. He serves/served as chair/committee members of over 200 international conferences.

Dr Anupam Yadav, Assistant Professor, Department of Mathematics, Dr. BR Ambedkar National Institute of Technology Jalandhar, India. His research area includes numerical optimization, soft computing, and artificial intelligence, he has more than ten years of research experience in the areas of soft computing and optimization. Dr. Yadav has done a Ph.D. in soft computing from the Indian Institute of Technology Roorkee and he had worked as a research professor at Korea University. He has published more than twenty-five research articles in journals of international repute, has published more than fifteen research articles in conference proceedings. Dr. Yadav has authored atextbook entitled "An introduction to neural network methods for differential equations. He has edited three books which are published by AISC, Springer Series. Dr. Yadav was the General Chair, Convener and member of the steering committee of several international conferences. He is a member of various research societies.

Dr Puneet Rana is working as an Assistant Professor of Mathematics at the Wenzhou-Kean University, Wenzhou, China. He has more than ten years of teaching and research experience. He has received his PhD degree in the field of applied mathematics with specialization in "nanofluids" from Indian Institute of Technology Roorkee, INDIA in 2013. His research interest includes nanotechnology, soft computing, numerical methods, thermal stability analysis etc. He was awarded "research fellowship" for pursuing higher education by CSIR, INDIA and travel grant for attending various international conferences by INSA and DST, INDIA. He has also guided two Ph.D. students in the field of "nanotechnology" and published more than 60+ research papers in international journal and conferences of high impact with more than 1800+ Google and Scopus citation. He was also invited to the school of mathematical sciences, Universiti Sains Malaysia, Penang, Malaysia for collaborative research work. One of his paper is recognized by Science-Direct as a most cited paper published in Communications in Nonlinear Science and Numerical Simulation, Elsevier in 2012. He has participated and contributed in many conferences and workshops as a keynote speaker and technical committee member. He served as a reviewer of several Top ISI journals including Scientific reports, Physics of fluids, IJHMT, IJTS and many more.

Dr. Zhenyu Wang is the Director of the NRIAT, Wenzhou. He obtained his DPhil Degree from the Department of Computer Science, University of Oxford, and he was a member of Linacre College. Dr. Wang graduated from East China TeachingUniversity, holding a BSc in Computer Science and Technology. He received his Msc in Natural Computation from the School of Computer Science at University of Birmingham. His current research areas include fuzzy rule-based systems, ensemble Learning, evolutionary algorithms, natural inspired optimizations, applications of intelligent system in cancer diagnosis and bioinformatics.

Contenu
Neural Artistic Style Transfer using Deep Neural Networks.- Choice Based One-Time Pad Approach Using Hybrid Cellular Automata.- Novel Imaging Approach for Mental Stress Detection using EEG Signals.- Classification of Fundus Images for Diabetic Retinopathy using Machine Learning: A Brief Review.- Wearable Sensor and Machine Learning Model based Fall Detection System for Safety of Elders and Movement Disorders.