Assistant Professor

Dr Medipelly Rampavan

Department of Computer Science and Engineering

Interests

  1. Computer Vision
  2. Deep Learning
  3. Evolutionary Computation

Education

2013

Nalla Malla Reddy Engineering College (JNTUH University), Hyderabad
India
BTech

2016

PDPM Indian Institute of Information Technology, Design and Manufacturing (IIITDM), Jabalpur
India
MTech

2024

National Institute of Technology (NIT), Warangal
India

PhD

Experience

  • December 2021 to April 2024 – Senior Research Fellow, National Institute of Technology, Warangal
  • December 2019 to November 2021 – Junior Research Fellow, National Institute of Technology, Warangal
  • January 2017 to December 2019 – Assistant Professor, Aurora’s Technological and Research Institute, Hyderabad

Research Interest

  • Image and video understanding through Computer vision-based techniques such as object detection, tracking and re-identification
  • To automate the design of Machine learning and Deep learning models
  • Soft computing techniques

Awards & Fellowships

  • 2024 – Won first prize for Poster presentation in Research Confluence – NIT Warangal
  • December 2019 to April 2024 – Ph.D. Fellowship – Ministry of Human Resource Development

Publications

Journals:

  • Medipelly Rampavan, Earnest Paul Ijjina, “Genetic brake-net: Deep learning based brake light detection for collision avoidance using genetic algorithm.” in: Knowledge-Based Systems, Elsevier, vol. 264, pp.110338 (SCI Indexed, Q1, 2023, IF: 8.8)
  • Medipelly Rampavan, Earnest Paul Ijjina, “Brake Light Detection of Vehicles Using Differential Evolution Based Neural Architecture Search” in: Applied Soft Computing, Elsevier, 147, pp.110839 (SCI Indexed, Q1, 2023, IF: 8.7)

Book Chapters:

  • Medipelly Rampavan, Earnest Paul Ijjina. “A Fast Garbage Classification Model Based on Deep Learning” in: IoT-Based Smart Waste Management for Environmental Sustainability, CRC Press, pp. 171-182 (2022)

Conferences:

  • MKumar, Gobind, Medipelly Rampavan, and Earnest Paul Ijjina. “Deep Learning based Brake Light Detection for Two Wheelers” in Proc. of IEEE International Conference on Computing Communication and Networking Technologies (ICCCNT),
    pp. 1-4 (2021)

Contact Details

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