Subrahmanya Swamy Peruru

Subrahmanya Swamy Peruru is an Assistant Professor in the Department of Electrical Engineering at the Indian Institute of Technology Kanpur (IIT Kanpur). His research focuses on wireless networks, artificial intelligence, and probabilistic graphical models, contributing significantly to the field of network optimization and machine learning applications in communication systems.

Dr. Peruru completed his educational journey with excellence:

• PhD in Electrical Engineering from Indian Institute of Technology Madras (2018)
• M.S. (by Research) from Indian Institute of Technology Madras (2018)
• B.Tech in Electronics and Communication Engineering from Sastra University (2011)

Dr. Peruru's research interests lie at the intersection of wireless communications and artificial intelligence. His work primarily focuses on developing efficient algorithms for wireless network scheduling, leveraging reinforcement learning and graph neural networks to optimize network throughput and minimize delays. He has made significant contributions to CSMA (Carrier Sense Multiple Access) protocols, particularly in adapting them to SINR (Signal-to-Interference-plus-Noise Ratio) models using advanced approximation techniques from statistical physics. His research on probabilistic graphical models has enabled more efficient network resource allocation and has potential applications in 5G and beyond wireless systems. Dr. Peruru's interdisciplinary approach bridges theoretical computer science, electrical engineering, and machine learning to solve practical challenges in modern communication networks.

His publication record demonstrates a consistent focus on wireless network optimization, with a recent shift toward incorporating machine learning techniques. Starting with foundational work on CSMA protocols and regional approximations (2015-2018), his research has evolved to include reinforcement learning (2023) and graph neural networks (2021) for network scheduling. This progression reflects the broader trend in networking research toward data-driven and AI-enhanced approaches. His work spans both theoretical contributions (approximation algorithms, convergence analysis) and practical implementations (scheduling algorithms with throughput guarantees).

Dr. Peruru previously served as a Senior Research Engineer in the Machine Learning R&D team at Pramati Technologies, Chennai (2018-2020), where he likely applied his academic expertise to industry challenges before joining IIT Kanpur as faculty.