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Faculty

JKLU boasts a distinguished faculty body comprising experienced academics and industry professionals.
About

Mayank Kumar Kundalwal

Assistant Professor

Institute of Engineering & Technology

Biography

Mayank Kumar Kundalwal is an Assistant Professor in the Department of Computer Science and Engineering at JK Lakshmipat University (JKLU), Jaipur. He is currently pursuing his Ph.D. at the Indian Institute of Technology (IIT) Jodhpur, where his research focuses on Machine Learning and Federated Learning, with particular emphasis on statistical heterogeneity, robustness, and privacy-preserving techniques in distributed learning systems. He holds an M.Tech. from NIT Patna and a B.Tech. from Poornima University, Jaipur. His broader research interests span deep learning, federated learning, and privacy-preserving AI, with applications in healthcare and other domains.

Education

  • Indian Institute of Technology, Jodhpur, 2026

    PhD

    Focus: Machine Learning and Federated Learning

  • National Institute of Technology, Patna, 2018

    MTech

    Major: Computer Science and Engineering

  • Poornima University, Jaipur, 2016

    BTech

    Major: Computer Science and Engineering

  • Federated Learning
  • Deep Learning
  • Machine Learning for Healthcare

  • Kundalwal, M. K., & Mishra, D. (2026). AR2FL: Anomaly-Resistant Robust Framework for Federated Learning. IEEE Transactions on Artificial Intelligence, 7(2), 1131–1142.
  • Kundalwal, M. K., & Mishra, D. (2025). FLAME: Federated Learning With Masked Autoencoders and Mean-Prototypes Embedding for Sparsely Labeled Medical Images. IEEE Transactions on Emerging Topics in Computational Intelligence.
  • Kundalwal, M. K., Chatterjee, K., & Singh, A. (2019). An improved privacy preservation technique in health-cloud. ICT Express, 5(3), 167–172.

  • Kundalwal, M. K., Mamta, Mishra, D., & Ekbal, A. (2026). Federated Model Synchronization for Diagnostic Redefinition through a Novel Selective Parameter Unlearning. Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), 1395–1404.
  • Kundalwal, M. K., Saraswat, A., Mishra, I., & Mishra, D. (2024). Client Contribution Normalization for Enhanced Federated Learning. 2024 IEEE 21st India Council International Conference (INDICON), 1–6.
  • Kundalwal, M. K., Saraswat, A., Mishra, I., & Mishra, D. (2022). BAFL: Federated Learning with Base Ablation for Cost Effective Communication. 26th International Conference on Pattern Recognition (ICPR), 1922–1928.
  • Kundalwal, M. K., Singh, A., & Chatterjee, K. (2018). A Privacy Framework in Cloud Computing for Healthcare Data. 2018 IEEE International Conference on Advances in Computing, Communication Control and Networking (ICACCCN).

  • Deep Learning

  • Federated Learning
  • Privacy-Preserving AI
  • Artificial Intelligence
  • Programming in Python, C
  • Database Management Systems

  • Assistant Professor, Manipal University Jaipur. (January 2026 - June 2026).

  • Assistant Professor, Department of Computer Science and Engineering, JK Lakshmipat University (JKLU), Jaipur. (2024 - Present).
  • Research Scholar (PhD), Indian Institute of Technology (IIT) Jodhpur. (Jul 2019 - 2024).
  • Assistant Professor, Manipal University Jaipur. (January 2026 - June 2026).

  • Coordinator, Robotic Process Automation Course, Manipal University Jaipur.

  • IEEE Transactions on Emerging Topics in Computational Intelligence
  • IEEE Transactions on Artificial Intelligence
  • IEEE INDICON
  • International Conference on Pattern Recognition (ICPR)
  • ICT Express
  • IEEE Transactions on Artificial Intelligence
  • IJCAI, AAAI
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