Research / Research AreasIntelligent Devices
The Center of Engineering and Health's research in intelligent devices focuses on the design and development of power-efficient devices to improve mobile healthcare. Learn more about projects in this area via the links below.
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Aggelos Katsaggelos Lab
Conducting research in the fields of multimedia (image, video, speech) signal processing, multimedia communications, computer vision, computational photography, and machine learning.
Aggelos K. Katsaggelos, PhD, Katsaggelos and the members of the Image and Video Processing Laboratory (IVPL) he is directing have been conducting research in the fields of multimedia (image, video, speech) signal processing, multimedia communications, computer vision, computational photography, and machine learning. Within these fields he has been working on a variety of problems (e.g., image and video recovery, compression, analysis, segmentation, and speech and speaker recognition) and application areas (e.g., biological, molecular, medical, health, multi-spectral, astronomical, and DNA-based digital signal processing). IVPL has been funded by both governmental and industrial sources. Some of the technology he has developed has been patented and adopted by industry and international standards (e.g., video compression standards).
Examples of their recent work include the use of sparsity to develop solutions to important problems in signal processing and machine learning. For example, they have developed cutting-edge technology to acquire passive millimeter-wave images with a portable single-pixel camera, and developed algorithms to fuse EEG and fMRI signals in order to accurately determine brain activity when a specific task is performed. As another example they have developed three-dimensional image segmentation techniques that will unambiguously identify nuclear positions and shapes and accurately measure single cell protein expression dynamics from confocal images of fluorescently-tagged transcription factors in the developing Drosophila eye.
We are working on a connected medication adherence system. This system tracks a user's adherence patterns using a specialized medication container, and communicates this data wirelessly to our servers. There, the data gets processed and is used to create an interface for both the patient and his doctor through both a website and a mobile application. In this way, we have a closed feedback system that reacts to the user's actual adherence patterns and creates the best personalized interventions to ensure the highest level of compliance.
Seda Ogrenci-Memik Lab
Exploring design and run-time management methods to build energy-efficient and thermally bounded systems of all shapes an sizes; ranging from smart phones and smart health technologies to high performance multicore processors to manycore processors in supercomputers.
Seda Ogrenci-Memik, PhD, research interests include thermal-aware design and management of high performance system, embedded and reconfigurable computing, and thermal sensing technologies.
Dr. Ogrenci-Memik explores design and run-time management methods to build energy-efficient and thermally bounded systems of all shapes an sizes; ranging from smart phones and smart health technologies to high performance multicore processors to manycore processors in supercomputers. She develops design methods that effectively tie the physical phenomena such as power consumption and heat dissipation to the logic structures inside these systems as well as component-level management, e.g., memory management. She also develops predictors to embed into the software stack to better anticipate the actions of the hardware components and plan ahead for their energy and thermal response. Recently, Dr. Ogrenci-Memik is applying her expertise in power and thermal modeling onto smartphones and portable devices for maximizing user comfort and satisfaction with these devices.