INSys Lab · Student Research · Mentoring

Scholars

This page highlights scholars who collaborate with me on research, publications, and project development. The group includes current students, alumni, and collaborators working across RF signal processing, hardware-aware AI, digital systems, and efficient computing.

Student Research Mentoring
RF Signal Classification
Hardware-Aware AI
Digital Circuit Optimization
Edge Intelligence
Publication-Oriented Projects
Student Research Mentoring
RF Signal Classification
Hardware-Aware AI
Digital Circuit Optimization
Edge Intelligence
Publication-Oriented Projects
Lead
Research Guidance
INSys Lab research direction
Current
Student Projects
Active mentoring and development
Alumni
Past Scholars
Research and publication outcomes
Pubs
Research Output
Manuscripts, submissions, and papers
📡

RF and Signal Intelligence

Student projects include modulation recognition, signal-domain feature extraction, envelope statistics, and lightweight RF classification.

🧠

Hardware-Aware AI

Research mentoring emphasizes efficient machine learning, model simplification, low-power inference, and deployment-aware evaluation.

⚙️

Digital Systems

Student work includes logic design, Boolean minimization, circuit optimization, and hardware-oriented computing foundations.

👥 Scholars Directory

Srinivas Rahul Sapireddy
Srinivas Rahul Sapireddy, Ph.D. LinkedIn
Assistant Professor, College of Engineering, Illinois State University
Research Lead Hardware-Aware AI RF Signal Classification
Research interests
  • Hardware-efficient deep learning models
  • Low-power RF signal classification
Active topics / papers
  • Efficient Deep Neural Networks
Sai Anirudh Godavarthi
Sai Anirudh Godavarthi
UMKC — M.S. Computer Science (Present)
Current RF Communications Antenna Design
Research interests
  • RF communications
  • Antenna design and simulation
Active topics / papers
  • RF communication and antenna design project in progress
Hemanth Bandi
Hemanth Bandi LinkedIn
UMKC — M.S. Computer Science (Spring 2023)
Alumni RF Deep Learning Reinforcement Learning
Research interests
  • RF modulation recognition
  • Reinforcement learning
Active topics / papers
  • Reinforcement Learning manuscript (Springer, To be submitted)
  • Benchmarking R-aware binning with envelope-feature baselines (IEEE, submitted)
Abreham Mesfin
Abreham Mesfin LinkedIn
UMKC — B.S. Electrical and Computer Engineering
Alumni Logic Design Engineering Computation
Research interests
  • Minimization techniques for Boolean functions
  • Low-power circuit implementations
Research topics / papers
  • Digital Circuit Optimization Techniques

🧭 Mentoring Pathways

Research Foundations

Students begin with literature review, technical reading, experimental setup, and reproducible research workflows.

Project Development

Students contribute to simulation, feature extraction, model evaluation, circuit optimization, or signal-processing pipelines.

Publication Preparation

Advanced students work toward manuscript development, result analysis, presentation preparation, and conference/journal submissions.

🤝 Interested in Joining?

Students interested in RF signal processing, hardware-aware AI, digital systems, low-power computing, or research-oriented engineering projects are welcome to reach out. Please include your research interests, relevant coursework, technical skills, and any prior project experience.