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Dr. Ankita Jaiswal

Biography

Dr. Ankita Jaiswal is currently serving as an Assistant Professor (Senior Grade) in the Department of Computer Science and Engineering & Information Technology at Jaypee Institute of Information Technology, Noida-62, Uttar Pradesh, India. She earned her Ph.D. and M.Tech. degrees in Computer Science and Technology from Jawaharlal Nehru University, New Delhi, in 2022 and 2016, respectively. Her primary research interests span across Wireless Sensor Networks, Internet of Things (IoT)-enabled smart services, energy harvesting and trading, Quantum Learning, Machine Learning, Next-generation wireless systems and Network security. She has published several research articles in reputed international journals and conferences, including those by IEEE, Elsevier, and Springer.

With over three years of teaching experience, Dr. Jaiswal has taught a variety of core subjects such as Operating Systems, C Programming, C++ Programming, Discrete Mathematics, Theory of Computation & Formal Languages, Computer Networks. She has successfully supervised numerous undergraduate and postgraduate projects and theses. Currently, two Ph.D. scholars are pursuing their research under her guidance.

Educational Qualifications

Ph.D. (Computer Science & Technology), Jawaharlal Nehru University (JNU), New Delhi, 2022, M.Tech (Computer Science & Technology ), Jawaharlal Nehru University (JNU), New Delhi, 2016, B.Tech (Computer Science & Engineering), U.P.T.U, Lucknow, 2013.

Research Highlights

Dr. Ankita Jaiswal’s research is centered on the design and development of intelligent, secure, and energy-efficient frameworks for next-generation wireless and IoT-enabled systems. Her work leverages advanced machine learning, deep learning, reinforcement learning, and quantum learning techniques to address critical challenges in wireless sensor networks, edge computing, and resource-constrained IoT environments. She focuses on optimizing key performance metrics such as energy efficiency, computational latency, spectrum utilization, and physical layer security under dynamic and stochastic conditions. Her research integrates predictive analytics, Markov decision process modeling, and algorithmic optimization to support adaptive system behavior and robust decision-making. Emphasizing sustainable and scalable architectures, her contributions aim to enable reliable data acquisition, secure communication, and efficient computation in applications ranging from precision agriculture and smart infrastructure to 6G-centric edge networks. By bridging theory with simulation-driven validation, her work advances the development of context-aware, high-performance wireless systems suited for complex, real-time environments.

Areas of Interest
  • Wireless Sensor Networks
  • Internet of Things (IoT)-enabled smart services
  • Energy harvesting & Energy Optimization
  • Machine Learning & Quantum Learning
  • Network security.
Publications
  1. P. K. Kashyap, S. Kumar, Jaiswal, A.., "DECENT: Deep Learning Enabled Green Computation for Edge centric 6G Networks," in IEEE Transactions on Network and Service Management, doi: 10.1109/TNSM.2022.3145056, January 2022.
  2. Ankita Jaiswal, Sushil Kumar "Quantum Learning Enabled Green Communication for Next Generation Wireless Systems," in IEEE Transactions on Green Communications and Networking, doi: 10.1109/TGCN.2021.3067918, March 2021.
  3. P. Kashyap, S. Kumar, A. Jaiswal "Towards Precision Agriculture: IoT-enabled Intelligent Irrigation Systems Using Deep Learning Neural Network," in IEEE Sensors Journal, doi: 10.1109/JSEN.2021.3069266, March 2021.
  4. Ankita Jaiswal, Sushil Kumar “Green computing in IoT: Time slotted simultaneous wireless information and power transfer,” Computer Communications, Elsevier , 168, pp. 155- 169, January 2021. https://doi.org/10.1016/j.comcom.2020.12.024 .
  5. Ankita Jaiswal, Sushil Kumar "Secrecy Rate Maximization in Virtual-MIMO Enabled SWIPT for 5G Centric IoT Applications," in IEEE Systems Journal, vol. 15, no. 2, pp. 2810- 2821, November 2020. doi:10.1109/JSYST.2020.3036417