IARE Best Engineering College In Hyderabad
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It is a matter of great pride that the Institute of Aeronautical Engineering (IARE) is ranked one among the Top 200 best Engineering colleges as per NIRF (National Institutional Ranking Framework), Ministry of Education (MoE), Govt. of India since 2017.

Handbook - CSE (Data Science)

Recognized Research Supervisors

The following faculty are recognised as Research (PhD) Supervisors / Co-Supervisors / External Supervisors:

S.no Name College / Organisation Research Area PhD Guiding PhD Produced
1 Dr. K Rajendra Prasad
  • Jawaharlal Nehru Technological University, Hyderabad
Cyber Security, Machine Learning, Image Processing, Information Security, Artificial Intelligence and Data Science
  • Machine Learning - Disease Detection using supervised and unsupervised techniques
  • Cybersecurity - Penetration testing and providing security
  • Image Processing - Image Compression and fusion
  • Data Science - Computing systems for data intensive applications
4 2
2 Dr R Obula Konda Reddy
  • Jawaharlal Nehru Technological University, Hyderabad
Image Processing and Computer Vision
  • Image segmentation and pattern recognition for accurate identification and classification of visual data.
  • Deep learning-based architectures such as CNNs and GANs for image generation, restoration, and object detection.
  • Video analytics and motion tracking for intelligent surveillance and behavior analysis
  • Medical image processing for disease detection, diagnostics, and healthcare automation.
  • Scene understanding and 3D reconstruction for augmented reality and robotic vision applications.
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3 Dr. P Ramadevi
  • Jawaharlal Nehru Technological University, Hyderabad
Wireless Ad Hoc Networks
  • Routing Protocols for Energy Efficient and QoS routing.
  • Security for Networks, routing protocols and Privacy of Users.
  • Applications of the Wireless Adhoc networks for Sensor Networks.
  • Integration with 5G and beyond.
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4 Dr. D Mahammad Rafi
  • Visvesvaraya Technological University (VTU)
Artificial Intelligence and Machine Learning - Data pattern discovery and anomaly detection for enhancing data-driven business intelligence and cybersecurity systems.
  • Deep neural network optimization for image recognition, speech processing, and natural language understanding.
  • Hybrid machine learning frameworks integrating supervised and unsupervised models for robust classification and forecasting tasks.
  • Feature engineering and dimensionality reduction for improving model accuracy and computational efficiency.
  • Smart automation and cognitive computing applications in domains such as healthcare analytics, IoT-based monitoring, and financial prediction.
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