Research Output per year
Personal profile
Education/Academic qualification
PHD, University of Minnesota-Minneapolis
… → 2001
MS, University of Virginia
… → 1998
BS, Florida Institute of Technology
… → 1995
Fingerprint Fingerprint is based on mining the text of the experts' scientific documents to create an index of weighted terms, which defines the key subjects of each individual researcher.
- 2 Similar Profiles
Fading channels
Engineering & Materials Science
Antennas
Engineering & Materials Science
Channel estimation
Engineering & Materials Science
Sensors
Engineering & Materials Science
Wireless sensor networks
Engineering & Materials Science
Orthogonal frequency division multiplexing
Engineering & Materials Science
Fusion reactions
Engineering & Materials Science
Communication
Engineering & Materials Science
Network
Recent external collaboration on country level. Dive into details by clicking on the dots.
Research Output 1997 2018
8
Citations
A brief survey of machine learning methods and their sensor and IoT applications
Shanthamallu, U. S., Spanias, A., Tepedelenlioglu, C. & Stanley, M., Mar 14 2018, 2017 8th International Conference on Information, Intelligence, Systems and Applications, IISA 2017. Institute of Electrical and Electronics Engineers Inc., Vol. 2018-January, p. 1-8 8 p.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
learning method
Learning systems
Internet
Sensors
learning
5
Citations
A cyber-physical system approach for photovoltaic array monitoring and control
Rao, S., Katoch, S., Turaga, P., Spanias, A., Tepedelenlioglu, C., Ayyanar, R., Braun, H., Lee, J., Shanthamallu, U., Banavar, M. & Srinivasan, D., Mar 14 2018, 2017 8th International Conference on Information, Intelligence, Systems and Applications, IISA 2017. Institute of Electrical and Electronics Engineers Inc., Vol. 2018-January, p. 1-6 6 p.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Learning systems
monitoring
Monitoring
renewable energy
learning method
Distributed center and coverage region estimation in wireless sensor networks using diffusion adaptation
Zhang, S., Tepedelenlioǧlu, C. & Spanias, A., Apr 10 2018, Conference Record of 51st Asilomar Conference on Signals, Systems and Computers, ACSSC 2017. Matthews, M. B. (ed.). Institute of Electrical and Electronics Engineers Inc., Vol. 2017-October, p. 1353-1357 5 p.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Wireless Sensor Networks
Wireless sensor networks
Coverage
sensors
Radius
Distributed Network Center and Size Estimation
Zhang, S., Tepedelenlioglu, C. & Spanias, A., May 22 2018, (Accepted/In press) In : IEEE Sensors Journal.Research output: Contribution to journal › Article
Parallel algorithms
radii
Convex optimization
sensors
Sensor nodes
Distributed Network Structure Estimation using Consensus Methods
Zhang, S., Tepedelenlioglu, C., Spanias, A. & Banavar, M., Jan 1 2018, In : Synthesis Lectures on Communications. 10, 1, p. 1-88 88 p.Research output: Contribution to journal › Article
Wireless sensor networks
Parallel algorithms
Military applications
Graph theory
Sensor nodes
Projects 2002 2018
SenSIP Project: Sequential Localization in Low Power Wireless Sensor Networks with experiments on LTE
Tepedelenlioglu, C. & Spanias, A.
INDUSTRY: Various Consortium Members
10/27/16 → 9/30/18
Project: Research project
SenSIP Project: Cloud Computing and Signal Processing for Solar Energy Analytics and Power Optimization
Tepedelenlioglu, C., Spanias, A. & Scaglione, A.
INDUSTRY: Various Consortium Members
7/1/17 → 6/30/18
Project: Research project
SenSIP Project: Minimally Supervised Machine Learning for Condition Monitoring of Machinery
Spanias, A., Berisha, V. & Tepedelenlioglu, C.
INDUSTRY: Various Consortium Members
9/30/16 → 8/15/18
Project: Research project
SenSIP Project: Sensors and Machine Learning for Monitoring Machinery
Spanias, A. & Tepedelenlioglu, C.
INDUSTRY: Various Consortium Members
8/2/15 → 8/1/16
Project: Research project
SenSIP Project: Minimally Supervised Machine Learning for Condition Monitoring of Machinery
Spanias, A., Berisha, V., Tepedelenlioglu, C. & Turaga, P.
INDUSTRY: Various Consortium Members
8/8/14 → 9/30/16
Project: Research project