Jonathan H. Manton is affiliated with the University of Melbourne in Australia. The primary fields of study in their research include Computer Science and Engineering, with a focus on multiple subfields such as Artificial Intelligence, Electrical and Electronic Engineering, Computational Mechanics, Computer Networks and Communications, and Computer Vision and Pattern Recognition.
The scientist's research covers various core topics, including Domain Adaptation and Few-Shot Learning, Optical Network Technologies, Machine Learning and Algorithms, Machine Learning and Extreme Learning Machines (ELM), Sparse and Compressive Sensing Techniques, Advanced Photonic Communication Systems, and Photonic and Optical Devices.
Jonathan H. Manton has published extensively, with significant contributions to numerous scientific venues. The most frequent publication platforms include arXiv (Cornell University), Journal of Lightwave Technology, IEEE Transactions on Signal Processing, IEEE Transactions on Information Theory, and IFAC-PapersOnLine.
Their recent notable papers include the following:
Frequent collaborators in Jonathan H. Manton's work include Xuetong Wu, Uwe Aickelin, Jingge Zhu, Zhaopeng Xu, and William Shieh. This network of collaboration has contributed to a body of work in diverse research areas related to signal processing, machine learning, and optical communication.
Jonathan H. Manton's recognition includes being named an IEEE Fellow in 2016. The citation for this honor highlighted contributions to geometric methods in signal processing and wireless communications.
J.H. Manton
Minyi Huang;Jonathan H. Manton
L. T. Hall;G. C. G. Beart;E. A. Thomas;D. A. Simpson
Minyi Huang;J.H. Manton
S. Shahbazpanahi;A.B. Gershman;J.H. Manton
K. Abed-Meraim;Yong Xiang;J.H. Manton;Yingbo Hua
Minyi Huang;Subhrakanti Dey;Girish N. Nair;Jonathan H. Manton
Salem Said;Lionel Bombrun;Yannick Berthoumieu;Jonathan H. Manton
J.H. Manton;R. Mahony;Yingbo Hua
J.H. Manton
J.H. Manton
Lin Li;A. Scaglione;J. H. Manton
J. Lu;E. Kazmierczak;J. H. Manton;R. Sinclair
Minyi Huang;J.H. Manton
J.H. Manton;I.Y. Mareels;Yingbo Hua
J.H. Manton;H.V. Poor
Rudrasis Chakraborty;Jose Bouza;Jonathan Manton;Baba C Vemuri
Shiro Ikeda;Jonathan H. Manton
Minyi Huang;J.H. Manton
Levin Kuhlmann;Dean R. Freestone;Jonathan H. Manton;Bjorn Heyse
Haitong Sun;J.H. Manton;Zhi Ding
Zhaopeng Xu;Chuanbowen Sun;Tonghui Ji;Jonathan H. Manton
If you think any of the details on this page are incorrect, let us know.
Studying Computer Science in the USA opens up a range of educational and career opportunities, especially with the growth of online learning. Whether you're a recent high school graduate or a working professional seeking to advance your skills, there's a program to meet your needs.
Many students start with online associates programs, which provide a flexible and cost-effective way to gain foundational knowledge and job-ready skills. For those looking to deepen their expertise, some of the most useful graduate degrees are in technology and related fields, making advanced study in Computer Science a valuable investment.
Affordability is a top concern. The good news is that there are affordable online colleges offering high-quality Computer Science programs for various budgets. Additionally, applicants who worry about their academic record can take heart: many of the best online colleges that accept low gpa still provide pathways to a degree and a rewarding tech career.
Qingdao University
Kōchi University
GlobalFoundries (United States)
Okayama University
University of Illinois at Chicago
University of Helsinki
Federal University of Toulouse Midi-Pyrénées
Hebrew University of Jerusalem
University of California, Riverside
Université Paris Cité
University of California, San Francisco
University of Milan
Naval Postgraduate School
Freie Universität Berlin
National University of Colombia
University of Queensland
