BCNM Project Publications

A BibTeX file containing bibliographic information for all publications listed here is also available.

Globally, this publication list is ordered in reverse chronological order. Within a given year, the ordering is alphabetical (by author name).

The primary sponsor of the DSPCAD Group's work in this research area is the US National Institutes of Health.

We are also grateful to the following sponsors, who have supported the research in Maryland DSPCAD Research Group at large: Agilent Technologies; Angeles Design Systems, Inc.; the Austrian Marshall Plan Foundation; Blue Halo / Intelligent Automation; CoolCAD Electronics; the Defense Advanced Research Projects Agency; the Department of Homeland Security; the Fulbright Specialists Program of the Council for International Exchange of Scholars; IGI Technologies; Intel; the Intelligence Advanced Research Projects Activity; the Laboratory for Physical Sciences; the Laboratory for Telecommunication Sciences; Management Communications and Control, Inc.; the Maryland Governor's Office of Crime Control and Prevention; the Maryland Industrial Partnerships (MIPS) Program; the National Institutes of Health; National Instruments; the National Institute of Standards and Technology; the National Radio Astronomy Observatory; Northrop Grumman Corp.; the Salisbury, Maryland Police Department; the Semiconductor Research Corporation; Techno-Sciences, Inc.; Texas Instruments, Inc.; Trident Systems, Inc.; the University of Maryland Graduate School; the US Air Force Office of Scientific Research under the Dynamic Data Driven Applications Systems (DDDAS) Program; the US Air Force Research Laboratory; the US Army Research Laboratory; the US Army Research Office; and the US National Science Foundation.

DSPCAD Group Website.

[xie2025x2]

J. Xie, Y. Yan, A. Saxena, Q. Qiu, J. Chen, H. Sun, R. Chen, and S. Bhattacharyya. ShaderNN: A lightweight and efficient inference engine for real-time applications on mobile GPUs. Neurocomputing, 611:1-14, 2025.

[lee2023x1]

Y. Lee. Design Techniques for Embedded Computer Vision and Signal Processing. PhD thesis, Department of Electrical and Computer Engineering, University of Maryland, College Park, 2023.

[wu2023x2]

X. Wu, D.-T. Lin, R. Chen, and S. S. Bhattacharyya. Jump-GRS: a multi-phase approach to structured pruning of neural networks for neural decoding. Journal of Neural Engineering, 20(4):1-17, July 2023.

[xie2023x2]

J. Xie. Methods and Tools for Real-Time Neural Image Processing. PhD thesis, Department of Electrical and Computer Engineering, University of Maryland, College Park, 2023.

[xie2023x3]

J. Xie, R. Chen, and S. S. Bhattacharyya. A parameter-optimization framework for neural decoding systems. Frontiers in Neuroinformatics, 17:1-15, 2023.

[wu2022x2]

X. Wu. Efficient Machine Learning Techniques for Neural Decoding Systems. PhD thesis, Department of Electrical and Computer Engineering, University of Maryland, College Park, 2022.

[wu2022x3]

X. Wu, D.-T. Lin, R. Chen, and S. Bhattacharyya. Learning compact DNN models for behavior prediction from calcium imaging of neural activity. Journal of Signal Processing Systems, 94:455-472, 2022.

[wu2021x4]

X. Wu, S. S. Bhattacharyya, and R. Chen. WGEVIA: A graph level embedding method for microcircuit data. Frontiers in Computational Neuroscience, 14:1-18, January 2021.

[lee2020x5]

K. Lee, X. Wu, Y. Lee, D.-T. Lin, S. S. Bhattacharyya, and R. Chen. Neural decoding on imbalanced calcium imaging data with a network of support vector machines. Advanced Robotics, pages 1-12, 2020. DOI: 10.1080/01691864.2020.1863259.

[lee2020x8]

Y. Lee, J. Xie, E. Lee, S. Sudarsanan, D.-T. Lin, R. Chen, and S. Bhattacharyya. Real-time neuron detection and neural signal extraction platform for miniature calcium imaging. Frontiers in Computational Neuroscience, 14:1-20, 2020.

[lee2020x1]

Y. Lee, J. Xie, E.-J. Lee, R. Chen, and S. S. Bhattacharyya. The neuron detection and signal extraction platform: Introduction to NDSEP version 1.0. Technical Report DSPCAD-TR-2020-01, Maryland DSPCAD Research Group, Department of Electrical and Computer Engineering, University of Maryland at College Park, April 2020.

[lee2019x3]

K. Lee, Y. Lee, D.-T. Lin, S. S. Bhattacharyya, and R. Chen. Real-time calcium imaging based neural decoding with a support vector machine. In Proceedings of the IEEE Biomedical Circuits and Systems Conference, Nara, Japan, October 2019. 4 pages in online proceedings.

[lee2017x5]

Y. Lee, S. C. Madayambath, Y. Liu, D. T. Lin, R. Chen, and S. S. Bhattacharyya. Online learning in neural decoding using incremental linear discriminant analysis. In Proceedings of the IEEE International Conference on Cyborg and Bionic Systems, pages 173-177, Beijing, China, October 2017.