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Aniruddha Rajendra Rao

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Machine Learning Researcher at Hitachi America with a Ph.D. in Statistics from Pennsylvania State University. My experiences from working, interning, consulting, and collaborating with scientists across the industry and academic settings have taught me the importance of practical domain knowledge and effective communication.


Area of interest includes Functional data, Machine learning, Deep learning, and Time Series.

Recent Works:
• An ensemble of convolution-based methods for fault detection using vibration signals
• A Functional approach for Two Way Dimension Reduction in Time Series
• Modern non-linear function-on-function regression
• Non-linear Functional Modeling using Neural Networks
• Modern Multiple Imputation with Functional Data
• A Non-linear Function-on-Function Model for Regression with Time Series Data
• Spatio-Temporal Functional Neural Networks
• Comparison of Different Density Estimators for Infinite Dimensional Exponential Families

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