Center for Signal Processing, Imaging, Reasoning, and Learning (SPIRAL)
SPIRAL conducts fundamental and interdisciplinary applied research in the areas of computational modeling, computer vision, distributed computing, image analysis, machine learning, optimization, and signal processing, with application areas spanning affective computing, biomedical imaging, modeling, and simulation, cyber-human systems including brain interfaces and human robot collaboration, geolocalization and positioning systems, neuroscience, wireless communications and networks. SPIRAL is a federation of collaborating research laboratories that jointly strive to conduct rigorous application-driven computational modeling and inference research in diverse contexts, and are committed to providing an inclusive research, academic, and personal development environment for a diverse group of talented individuals at undergraduate, graduate, and postdoctoral training stages.
The following laboratories currently participate in SPIRAL:
|Augmented Cognition Laboratory||Sarah Ostadabbas|
|Biomedical Imaging and Signal Processing Laboratory||Dana Brooks|
|Brain Stimulation & Simulation Laboratory||Sumientra Rampersad|
|Cognitive Systems Laboratory||Deniz Erdogmus|
|Data, Networks, and Algorithms Laboratory||Stratis Ioannidis|
|Efficient and robust distributed machine learning lab||Lili Su|
|Information Processing Laboratory||Pau Closas|
|Machine Learning Laboratory||Jennifer Dy|
SPIRAL has been generously funded by the following government agencies, industry, and foundations:
Advanced Robotics for Manufacturing Institute, ARL, DARPA, DHHS, DHS, IARPA, NIH, NSF, ONR, Amazon Cloud Services, Analog Devices, Biogen, Google Research, Honeywell Labs, Intel Labs, Mathworks, NVIDIA, Unilever Corporation, Brigham & Womens’ Hospital, Boston Children’s Hospital, Massachusetts General Hospital, Nancy Lurie Marks Family Foundation, Simons Foundation, and Northeastern University.
For more information please contact the center co-directors:
Statistical and array signal processing; estimation and detection theory; Bayesian inference; stochastic filtering; robust statistics; and game theory, with applications to positioning systems (GNSS and indoor technologies); wireless communications, and mathematical biology
Computer Vision; Machine Learning; Artificial Intelligence; Augmented Cognition with Medical Applications; Augmented/Virtual Reality
Recent SPIRAL News
SPIRAL Receives 2 Best Paper Awards at PETRA
Two papers from SPIRAL researchers received best paper awards at PErvasive Technologies Related to Assistive Environments (PETRA) conference.