Edgar Lobaton
Biography
Dr. Lobaton received the B.S. degree in mathematics and the B.S. degree in electrical engineering from Seattle University in 2004. He completed his Ph.D. in electrical engineering and computer sciences from the University of California, Berkeley in 2009.
He is currently an Associate Professor in the Department of Electrical and Computer Engineering at North Carolina State University. Dr. Lobaton joined the department in 2011.
His research focuses on the development of pattern recognition, estimation theory, and statistical and topological-data-analysis tools applied to wearable health monitoring, robotics and computer vision. He was awarded the NSF CAREER Award in 2016. Prior to joining NCSU, he was awarded the 2009 Computer Innovation Fellows post-doctoral fellowship award and conducted research in the Department of Computer Science at the University of North Carolina at Chapel Hill. He was also engaged in research at Alcatel-Lucent Bell Labs in 2005 and 2009.
Education
-
Ph.D.
2009
Electrical Engineering and Computer Sciences
University of California, Berkeley -
Bachelor's
2004
Mathematics
Seattle University -
Bachelor's
2004
Electrical Engineering
Seattle University
Highlighted Awards
- NSF CAREER Award (2016)
Awards & Honors
- 2009-2011 - Computer Innovation Fellows Postdoctoral Award
- 2004-2008 - Bell Labs Graduate Research Fellowship
Recent Publications
- Computer vision approach to characterize size and shape phenotypes of horticultural crops using high-throughput imagery (2021)
- Environmental Context Prediction for Lower Limb Prostheses With Uncertainty Quantification (2021)
- Drought Stress Detection Using Low-Cost Computer Vision Systems and Machine Learning Techniques (2020)
- Enhancing the morphological segmentation of microscopic fossils through Localized Topology-Aware Edge Detection (2020)
- Localization of Biobotic Insects Using Low-Cost Inertial Measurement Units (2020)
- Activity-Aware Wearable System for Power-Efficient Prediction of Physiological Responses (2019)
- Automated species-level identification of planktic foraminifera using convolutional neural networks, with comparison to human performance (2019)
- LNSNet: Lightweight Navigable Space Segmentation for Autonomous Robots on Construction Sites (2019)
- Vision-based integrated mobile robotic system for real-time applications in construction (2018)
- A Framework for mapping with biobotic insect networks: from local to global maps (2017)
Recent News
Low-Cost Cameras Could Be Sensors to Remotely Monitor Crop Stress
Posted on June 10, 2020 | Filed Under: Research
Being able to identify crop problems early can make the difference between saving a crop and losing it, but high-tech solutions can be costly. An interdisciplinary team is leveraging existing technology for a solution.
GRIP4PSI seed grant winners announced
Posted on February 15, 2020 | Filed Under: Research
Two interdisciplinary research teams with significant ECE involvement have entered the next phase of the Game-Changing Research Incentive Program to tackle plant science challenges
$10M Grant to Advance Cover Crops includes Machine Learning
Posted on November 26, 2019 | Filed Under: Research
USDA $10-million grant to improve the sustainability of agriculture through the use of cover crops features cutting-edge tech, such as autonomous data collection and machine learning from ECE.
Recent Media Mentions
What’s Creepy, Crawly And A Champion Of Neuroscience?
October 22, 2013
NC State professor is in the simulation phase of using swarms of up to 1,000 cockroaches to assist in search-and-rescue operations. Edgar Lobaton, electrical and computer engineering, featured.