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Dr. Srinivas Rahul Sapireddy

Assistant Professor
Srinivas Rahul's Profile Image
Office
WIH Williams Hall 102
  • About

Biography

Srinivas Rahul Sapireddy is an Assistant Professor in the Department of Electrical Engineering at Illinois State University. His research focuses on communication signal processing and the development of efficient machine learning methods for wireless signal analysis. His work emphasizes lightweight algorithms and hardware-aware approaches that enable efficient signal classification and processing on resource-constrained platforms.

Dr. Sapireddy received his Ph.D. in Electrical and Computer Engineering and M.S. in Electrical Engineering from the University of Missouri-Kansas City. He also holds an M.S. in Computer Science from the University of Illinois Springfield and an Advanced Diploma in Artificial Intelligence from the National Institute of Electronics and Information Technology (NIELIT), India.

Prior to joining Illinois State University, he served as an Instructor at the University of Missouri-Kansas City from Spring 2023 to Fall 2025, where he taught courses including ASIC Physical Design and Testing, Engineering Computation, Analog IC Design, and Logic Design. From 2021 to 2022, he also worked as a Research Assistant at the Missouri Institute for Defense and Energy, where he contributed to research in signal processing and machine learning.

His research integrates statistical signal processing techniques with machine learning to analyze and classify radio-frequency signals. His work focuses on modulation classification methods based on envelope statistics and cyclostationary signal properties. He is also interested in hardware-efficient neural network architectures and algorithmic techniques that improve computational efficiency for communication and signal processing applications.

Teaching Interests & Areas

Digital Logic Design
Communication Systems
Digital Signal Processing
Wireless Communications
ASIC Design

Research Interests & Areas

Communication Signal Processing
RF Modulation Classification
Cyclostationary Signal Analysis
Statistical Signal Processing
Machine Learning for Wireless Signals
Hardware-Aware Machine Learning
Energy-Efficient Signal Processing Systems