Shruti R. Kulkarni is a Research Scientist in the Learning Systems group at Oak Ridge National Laboratory (ORNL). Her primary research focus is in neuromorphic computing, where she studies bio-inspired learning algorithms and evolutionary algorithms for Spiking Neural Networks (SNNs), and their application to diverse class of problems ranging from graph analysis, autonomous navigation and in smart instrumentation in High Energy Physics experiments. Some of her work also involves studying explainability of SNNs and exploring causal representations and learning in neuroscience models. She is also involved in the co-design effort for optimal realization of neuromorphic algorithms coherently with the design of energy efficient analog hardware platforms such as memristive crossbar arrays and digital FPGAs. She is also involved in developing performant neuromorphic simulator – SuperNeuro that can be run on HPC platforms, and also used for neuromorphic hardware co-design.
Links
Publications
Sep, 2026
Conference Paper
Predicting Band-Gap of Inorganic Materials Using Neuromorphic Graph Learning
Sep, 2026
Conference Paper
NeuroCoreX: An Open-Source FPGA-Based Spiking Neural Network Emulator with On-Chip Learning
News
January 26, 2023
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