Kaushallya Adhikari

Kaushallya Adhikari serves as an Associate Professor in the Department of Electrical, Computer and Biomedical Engineering at the University of Rhode Island's College of Engineering. Her research bridges theoretical signal processing with practical applications in sonar, radar, and biomedical systems through innovative array design and algorithm development.

Her academic credentials include:

• Ph.D. in Electrical Engineering, University of Massachusetts Dartmouth (2016)
• M.S. in Electrical Engineering, University of Massachusetts Dartmouth (2012)
• B.E. in Electronics and Communication Engineering, Tribhuwan University, Nepal (2008)

Dr. Adhikari's research centers on array signal processing with emphases on sparse array configurations, direction of arrival estimation, and information-theoretic approaches to detection. She leads the ASPIRE lab (Array Signal Processing for Information REtrieval), which explores statistical signal processing, machine learning integration, and sensor array optimization. Her work demonstrates consistent innovation in transforming circular arrays to linear configurations, developing subspace estimation techniques, and applying neural networks to traditional signal processing challenges.

Analysis of her 15 most recent publications reveals a decisive shift toward deep learning integration with classical array processing methods, particularly for direction of arrival estimation in sonar systems. While maintaining strong foundations in estimation theory and information metrics, her recent work increasingly focuses on convolutional neural networks for signal classification, sparse sampling optimization, and biomedical applications like tEEG-based cortical mapping. This evolution reflects her strategic expansion from theoretical frameworks to real-world implementation challenges.

Her scientific recognition includes:

• Office of Naval Research Young Investigator Program (YIP) Award (2020)

Dr. Adhikari has secured competitive funding including multiple Office of Naval Research grants for sonar array optimization (2020, 2023) and a NE Big Data Innovation Hub grant for neural network-based cortical mapping (2021). She actively mentors graduate researchers in the ASPIRE lab, where current projects span sonar signal processing, EEG/tEEG analysis, and renewable energy system modeling through autoregressive techniques.

The ASPIRE lab maintains a cohesive research program focused on sensor array design, statistical signal processing, and machine learning applications across defense, biomedical, and energy domains, with particular expertise in coprime/nested array configurations and direction of arrival estimation algorithms.