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Faculty

Home » Faculty » Mr. M.V. Phanindra
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Mr. M.V. Phanindra

Assistant Professor

Qualification
M. Tech (Ph. D)

Professional Exp.
14 years of Teaching Exp. and 4 years of Industry Exp.

Registration Number
4001-260610-113858

Email Address
phanindra.mv@aceec.ac.in

About

Having academic experience with over 14 years of teaching experience and 4 years of industry experience in software development. Expertise spans Computer Science, Software Engineering, Database Technologies, Machine Learning, Python Programming, and Big Data Analytics. Actively involved in teaching undergraduate engineering students, mentoring projects, conducting research, and contributing to academic administration. Research interests include Machine Learning, Deep Learning, Data Analytics, Artificial Intelligence, Human Action Recognition, and Healthcare Applications of AI. Published research papers in reputed journals and conferences and also contributed to innovative patent filings in emerging technologies.

Educational Details

  • Pursuing Ph.D. (Part-Time), Anurag University, Hyderabad (From March 2025)
  • M.Tech (SE), JNTU Hyderabad (2011–2013)
  • B.Tech (Computer Science & Information Technology), JNTU Hyderabad

Professional Background

  • Assistant Professor, Department of Data Science, Malla Reddy University, Hyderabad (June 2024 – April 2026)
  • Assistant Professor, Department of Information Technology, Kakatiya Institute of Technology and Science (KITS), Warangal (June 2008 – May 2020)
  • Software Engineer, Wipro Limited (June 2004 – May 2008)

Subjects Taught:

  • Introduction to Machine Learning
  • SQL and PL/SQL
  • Database Management Systems
  • Python Programming
  • Project Management
  • Software Engineering
  • Computer Architecture and Organization
  • System Software (UNIX)
  • Programming Concepts and Information Technology (C Programming)
  • Data Structures
  • Wireless Communications
  • Service-Oriented Architecture
  • Big Data Analytics

 

Core Research Domains:

  • Artificial Intelligence
  • Machine Learning
  • Deep Learning
  • Data Analytics
  • Healthcare Analytics
  • Human Action Recognition
  • Database Systems

Research Focus:
Research focus on the application of Artificial Intelligence and Machine Learning techniques for solving real-world problems, particularly in healthcare analytics and computer vision. Recent work includes blood cancer prediction and classification using machine learning and deep learning models, as well as human action recognition under multiple viewpoints using intelligent computing approaches.

 

Conference Publication

  • “View-point Discrimination for Human Action Recognition under Multiple Views”,
    presented at the 4th International Conference on Intelligent System & Sustainable Computing (ICISSC 2024),
    Springer–IEEE, 2024.

Journal Publications

  • “A SMOTE Boosting Based Blood Cancer Prediction Using Leukemia Microarray Dataset”,
    International Journal for Multidisciplinary Research,
    Vol. 6, No. 6, 2024.
  • “Automatic Detection of Blood Cancer Using Deep Learning Neural Networks”,
    International Journal of Scientific Research in Engineering and Management (IJSREM),
    Vol. 8, No. 12, 2024.
  • “Blood Cancer Detection and Classification Using ML Algorithms”,
    International Journal of Scientific Research in Engineering and Management (IJSREM),
    Vol. 8, No. 11, 2024.
  • “An Overview on the Utilization of Kali Linux Tools”,
    International Journal of Research and Analytical Reviews,
    Vol. 5, No. 2, 2018.
  • “Incipient Exploration across Database Management Systems in Multidisciplinary Environment”,
    International Journal of New Innovations in Engineering and Technology,
    Vol. 3, No. 4, 2015.
  • “A Firm Retrieval of Software Reusable Component Based on Component Classification”,
    International Journal of Computer Engineering Research,
    Vol. 3, No. 5, 2013.

Patents

  1. Deep Learning Model for Classification of Organic and Non-organic Images (2025)
  2. Enhancing Security and Performance in IoMT using a Blockchain-Enabled Hybrid Metaheuristic Optimization Model (2025)

Certified Courses

  • NPTEL course completion certification on “Introduction to Machine Learning”, April 2026.

FDPs & Workshops Attended

  • One Week FDP on Salesforce Developer Catalyst, ICT Academy, organized by Malla Reddy University, Hyderabad (July 2024).
  • Two-Week Workshop on Entrepreneur Development, KITS Warangal (February 2015).
  • FDP on Latest Trends of VLSI, KITS Warangal (November 2014).
  • One Week FDP on Latest Trends of JAVA, Big Data Challenges using Hadoop, Testing Tools and Agile Technologies, organized by Zensar Technologies, Pune (August 2014).
  • National Workshop on Beneficial Applications of Ionizing Radiation, KITS Warangal in association with IGCAR Kalpakkam (February 2014).
  • FDP on Big Data Challenges, Department of CSE, KITS Warangal (September 2013).
  • FDP on Modern Teaching Methodologies, Kamala Institute of Technology and Science, Huzurabad (August 2008).