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Dr. Mohandu Anjaneyulu

Dr. Mohandu Anjaneyulu View All

Assistant Professor

School of Technology

Dr. Anjaneyulu holds a Bachelor’s degree in Computer Science and Engineering from Anna University, Chennai, and a Master’s degree in Technology in the same field from Jawaharlal Nehru Technological University, Kakinada, AP. He earned his Ph.D. in Computer Science and Engineering from Vellore Institute of Technology, Vellore.

With over 7.5 years of teaching experience at reputed institutions such as Sri Venkateswara College of Engineering and Technology, Chittoor, and Priyadarshini Institute of Technology, Tirupati, Dr. Anjaneyulu brings strong academic expertise and practical knowledge to TAU. He has published five research articles in national and international journals.

His core competencies include Python Programming, Data Mining, Deep Learning, and Artificial Intelligence. He is adept at guiding students in practical coding, problem-solving, and application-oriented learning. His expertise in developing data-driven solutions and implementing machine learning models adds value to both teaching and research activities in the department.

    • Graduation In :

      Computer Science and Engineering

    • Graduation From :

      C. Abdul Hakeem College of Engineering & Technology, Vellore, TN

    • Graduation Year :

      2010

    • Post Graduation In :

      Computer Science and Engineering

    • Post Graduation From :

      BVC Engineering College, Odalarevu, Andhra Pradesh

    • Post Graduation Year :

      2014

    • Doctorate In :

      Computer Science and Engineering

    • Doctorate From :

      Vellore Institute of Technology

    • Doctorate Year :

      2023

    • 7.5 Yrs

  • Publications in Journals

    • Anjaneyulu, M., & Kubendiran, M. (2023). Short Term Traffic Flow Prediction Using Hybrid Deep Learning. CMC-Computers Materials & Continua, vol. 75, no.1, pp.1641-1656. [SCI, Impact Factor – 3.86]. DOI: https://doi.org/10.32604/cmc.2023.035056.
    • Anjaneyulu, M., & Kubendiran, M. (2022). Short-Term Traffic Congestion Prediction Using Hybrid Deep Learning Technique. Sustainability, vol. 15, no. 1, pp.74. [SCI, Impact Factor – 3.88].
      DOI: https://doi.org/10.3390/su15010074
    • Anjaneyulu, M., & Kubendiran, M. (2023) “Long-Term Traffic Flow Prediction using Hybrid Deep Learning Technique,” International Journal of Engineering Trends and Technology, vol. 71, no. 5, pp. 156-165. DOI: https://doi.org/10.14445/22315381/IJETT-V71I5P216
    • Mohandu, A., G Sateesh, K Thayagarajan, Anburaj A and Gopi K. (2024). A Comprehensive Review of Anomaly Detection in Road Traffic Analysis. International Journal of Computing and Digital Systems, vol. 18, no.1, pp.1-14. DOI: http://dx.doi.org/10.12785/ijcds/1571111482

    Publications in Conferences