KANNURU SRINADH

• Multimodal Image Super-Resolution: Researching RGB–NIR and RGB–Thermal image enhancement.
• Deep Learning Architectures: Developing Model-Based and Sparse-Enabled neural networks.
• High-Resolution Reconstruction: Focused on surveillance and remote sensing applications.
• Object Detection: Implementing real-time detection in high-resolution scenes.
• Sparse Signal Processing: Utilizing sparse representation for image restoration.
• Medical Imaging: Enhancement and bias field correction for MRI data.

Research Experience

• Doctoral Fellow (PhD) - National Institute of Technology Rourkela (July 2022 - Present)
  Supervisor: Prof. Upendra Kumar Sahoo & Prof. Santos Kumar Das
  • Conducting research on Sparse Enabled Model based Deep Learning for Multimodal Image Superresolution
  • Developed novel deep learning architectures for multimodal sensor fusion
  • Implementing sparse representation techniques for high-fidelity image reconstruction
  • Analyzing model-based deep learning frameworks for various imaging modalities

Teaching Experience

• Teaching Assistant - National Institute of Technology Rourkela (July 2022 - Present)
  Course: Advanced Wireless Communications
  • Conducted weekly tutorial sessions for 40+ undergraduate students on MIMO, OFDM, and channel coding
  • Assisted in developing lab exercises and grading assignments
  • Provided one-on-one mentorship to students
• Assistant Professor - Anurag Engineering College (A), Telangana (Sep 2017 - July 2022) - 4.10 years
  • Taught multiple courses in Electronics and Communication Engineering
  • Conducted practical laboratory sessions
  • Mentored undergraduate students in their projects

Peer-Reviewed Journal Articles

Peer-Reviewed Conference Papers

Awards

• 🏆 Best Paper Award - International Conference on Range Technology (ICORT '25) for the paper "Performance Analysis of FSO Communication under Foggy Conditions" (2025)
  Conducted by Integrated Test Range (ITR) DRDO, Ministry of Defence, Government of India, Chandipur
• NIT Rourkela Research Fellowship - Awarded for outstanding academic performance and research potential during PhD studies (2022-Present)

Professional Service & Affiliations

• Reviewer - IEEE International Conference on Acoustics, Speech, and Signal Processing (2025-Present)
• Reviewer - Elsevier Ad Hoc Networks (2023-Present)
• Organizing Committee Member - National Conference on Advanced Computing and Communication (NCACC'23), NIT Rourkela (2023)
• Member - IEEE Council on RFID and IEEE Sensor Council
• Student Member - Association for Computing Machinery (ACM)

Workshop Coordination

• Tech. Workshop Coordinator - "Python for Beginners" Workshop, NIT Rourkela (April 2025)
  Organized and taught a 2-day hands-on lab for 50+ students

• Multimodal Image Super-Resolution using Deep Learning (2023-Present)
  Developing novel sparse-enabled model-based deep learning approaches for enhancing image resolution using multiple modalities. Implemented using Python, TensorFlow, and PyTorch.
• IoT-based Smart Monitoring System (2022-2023)
  Designed and implemented an IoT-enabled monitoring system for real-time data collection and analysis. Technologies: Arduino, Raspberry Pi, MQTT, Node.js.
• Signal Processing for Wireless Communications (2021-2022)
  Developed adaptive signal processing algorithms for improving wireless communication performance. Implemented in MATLAB and C++.
• Machine Learning for Network Optimization (2020-2021)
  Applied machine learning techniques to optimize network resource allocation and improve QoS. Technologies: Python, scikit-learn, NumPy.
• Computer Vision for Object Detection (2019-2020)
  Implemented deep learning models for real-time object detection and classification. Used CNN architectures with TensorFlow and OpenCV.