Hariharan Muthusamy received a Ph.D. in Mechatronic Engineering (2010) from the University of Malaysia Perlis (Uni MAP), Malaysia, a Master of Engineering in Applied Electronics (2006) from the Government College of Technology, India, and a Bachelor of Engineering in Electrical and Electronics Engineering (2002) from Government College of Technology (Affiliated to Bharathiar University), India. He is an Associate Professor in the Department of Electronics Engineering, National Institute of Technology Uttarakhand, India. He has published over 150 papers in refereed journals and conference proceedings. His major research interests include speech signal processing, biomedical signal and image processing, machine learning, deep learning, and optimization algorithms. He has supervised 9 Ph.D. and 4 Masters (research) students in the field of his expertise.
Jan’os Botzheim earned his M.Sc. and Ph.D. degrees from the Budapest University of Technology and Economics in 2001 and 2008, respectively. He joined the Department of Automation at Szechenyi Istvan University, Gyor, Hungary in 2007 as a senior lecturer, in 2008 as an assistant professor, and in 2009 as an associate professor. He was a visiting researcher at the Graduate School of System Design at the Tokyo Metropolitan University from September 2010 to March 2011 and from September 2011 to February 2012. He was an associate professor in the Graduate School of System Design at the Tokyo Metropolitan University from April 2012 to March 2017. He was an associate professor in the Department of Mechatronics, Optics, and Mechanical Engineering Informatics at the Budapest University of Technology and Economics from February 2018 to August 2021. He is the Head of the Department of Artificial Intelligence at Eötvös Loránd University, Faculty of Informatics, Budapest, Hungary, since September 2021. His research interest areas are computational intelligence, automatic identification of fuzzy rule-based models and some neural network models, bacterial evolutionary algorithms, memetic algorithms, applications of computational intelligence in robotics, and cognitive robotics. He has about 180 papers in journals and conference proceedings.
Richi Nayak is the Leader of the Applied Data Science Program at the Centre for Data Science and a Professor of Computer science at Queensland University of Technology, Brisbane Australia. She has a driving passion to address pressing societal problems by innovating the Artificial Intelligence field underpinned by fundamental research in machine learning, data mining, and text mining. Her research has resulted in the development of novel solutions to address industry-specific problems in Marketing, K 12 Education, Agriculture, Digital Humanities, and Mining. She has made multiple advances in social media mining, deep neural networks, multi-view learning, matrix/tensor factorization, clustering, and recommender systems. She has authored over 180 high-quality refereed publications. Her research leadership is recognized by multiple best paper awards and nominations at international conferences, QUT Postgraduate Research Supervision awards, and the 2016 Women in Technology (Wi T) Infotech Outstanding Achievement Award in Australia. She holds a Ph.D. in Computer Science from the Queensland University of Technology and a Master in Engineering from IIT Roorkee.
8 E-böcker av Richi Nayak
Richi Nayak & Mohammed J. Zaki: Knowledge Discovery from XML Documents
The KDXD 2006 (Knowledge Discovery from XML Documents) workshop is the ?rst international workshop running this year in conjunction with the 10th Paci?c-Asia Conference on Knowledge Discovery and Dat …
PDF
Engelska
DRM
€57.78
N. Ichalkaranje & Richi Nayak: Evolution of the Web in Artificial Intelligence Environments
The Web has revolutionized the way we seek information on all aspects of education, entertainment, business, health and so on. The Web has evolved into a publishing medium, global electronic market a …
PDF
Engelska
DRM
€114.31
Basant Agarwal & Richi Nayak: Deep Learning-Based Approaches for Sentiment Analysis
This book covers deep-learning-based approaches for sentiment analysis, a relatively new, but fast-growing research area, which has significantly changed in the past few years. The book presents a co …
PDF
Engelska
€160.49
Yee Ling Boo & Anton Lord: Data Mining
This book constitutes the refereed proceedings of the 19th Australasian Conference on Data Mining, Aus DM 2021, held in Brisbane, Queensland, Australia, in December 2021.* The 16 revised full papers …
EPUB
Engelska
DRM
€83.60
B. Narendra Kumar Rao & R. Balasubramanian: Intelligent Computing and Applications
This book presents novel work of academicians, researchers, industry professionals, practitioners, and budding engineers to disseminate the most recent innovations, trends, and concerns along with th …
PDF
Engelska
€234.33
Hariharan Muthusamy & János Botzheim: Robotics, Control and Computer Vision
This book presents select peer-reviewed papers from the International Conference on Robotics, Control, and Computer Vision (ICRCCV 2022). The contents focus on the latest research in the field of Rob …
PDF
Engelska
€234.33
Richi Nayak & Khanh Luong: Multi-aspect Learning
This book offers a detailed and comprehensive analysis of multi-aspect data learning, focusing especially on representation learning approaches for unsupervised machine learning. It covers state-of-t …
PDF
Engelska
€149.79
Richi Nayak & Namita Mittal: Recent Advancements in Artificial Intelligence
This book features research papers presented at the Second International Conference on Recent Advancements in Artificial Intelligence (ICRAAI 2023), held at Poornima University, Jaipur, India during …
PDF
Engelska
€299.59