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
Funded Research
- SenSE: AI-Driven, Resilient and Adaptive Monitoring of Sleep (AI-DReAMS)
- SCH: INT: Collaborative Research: A Data-Driven Approach for Enhancing Wearable Device Performance – A Study on Early Detection of Asthma Exacerbation
- Collaborative Research: Improving the Performance and Design of Potentiometric Biosensors for the Detection of Extracellular Histones in Blood with Deep Learning
- Proof-of-Concept Study for Integrated Patch Recorder for Fetal Health Monitoring
- CPS:Medium:Multimodal Sensing for Early Detection and Real-Time Correction of Water Stress and Nutritional Needs in Plants
- Collaborative Research: FORABOT: An Autonomous and Accessible System for Sorting Foraminifera
- Robotics Awake: Promoting the Diffusion of Innovation through Curriculum Development and a Technician Training Community College Extension Model
- Collaborative Research: A Visual System for Autonomous Foraminifera Identification
- Power-Efficient Respiratory Rate Estimation via Minimal Sensing
- CAREER: Data Representation and Modeling for Unleashing the Potential of Multi-Modal Wearable Sensing Systems
Highlighted Awards
- NSF CAREER Award (2016)
Awards & Honors
- 2009-2011 - Computer Innovation Fellows Postdoctoral Award
- 2004-2008 - Bell Labs Graduate Research Fellowship
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.
Researchers Incorporate Computer Vision, Uncertainty into AI for Robotic Prosthetics
Posted on May 28, 2020 | Filed Under: Life and Research and Smart
Lobaton’s lab leverages AI to create a software integration for existing hardware to enable people using robotic prosthetics to walk in a safer, more natural manner on different types of terrain.
This post was originally published in NC State News.
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
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.
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)