ORCID ID: https://orcid.org/0000-0001-9498-807X
Nikita Jalodia is currently pursuing her PhD in the Department of Computing and Mathematics at the Emerging Networks Lab Research Unit in Telecommunications Software and Systems Group, Waterford Institute of Technology, Ireland. She is working as a part of the Science Foundation Ireland funded CONNECT Research Centre for Future Networks and Communications, and is supervised by Dr. Alan Davy.
Her research is focused around dynamic and automated management of virtualised resources in Network Function Virtualization (NFV) application environments towards next generation networks.
- Deep Learning
- Neural Networks
- Network Function Virtualization (NFV)
- Reinforcement Learning
- Internet of Things (IoT)
- Fog and Cloud Computing
Nikita received her Bachelor’s Degree in Computer Science and Engineering from The LNM Institute of Information Technology, Jaipur, India in 2017, with a diploma specialization in Big Data and Analytics with IBM.
She has also previously worked as a Developer at Publicis Sapient (Sapient Global Markets division), India.
- Award recipient of a travel grant sponsored by the IEEE Communications Society to travel and present her accepted research paper in the 2019 IEEE Conference on Network Function Virtualization and Software Defined Networks held in Dallas, Texas, USA.
- Contributor to a project that was a Finalist in AI Awards 2019 under the category of Best Application of AI in an Academic Research Body (SmartHerd)
- Contributor to a project that was listed as one of the top 5 projects in the IEEE ComSoc Student Competition 2019 (SmartHerd: An IoT Machine Learning Based System and Method for Predicting Lameness in Dairy Cattle)
- Contributor to a project that was listed as one of the top 10 projects in the IEEE ComSoc Student Competition 2018 (Connected Cows- Fog Assistance Towards Data Driven Smart Dairy Farming)
- M. Taneja, J. Byabazaire, N. Jalodia, A. Davy, C. Olariu, and P. Malone, “Machine learning based fog computing assisted data-driven approach for early lameness detection in dairy cattle,” Computers and Electronics in Agriculture, vol. 171, p.105286, 2020. [Online]. Available: http://www.sciencedirect.com/science/article/pii/S016816991931840X
- M. Taneja, N. Jalodia, P. Malone, J. Byabazaire, A. Davy and C. Olariu, “Connected Cows: Utilizing Fog and Cloud Analytics toward Data-Driven Decisions for Smart Dairy Farming,” in IEEE Internet of Things Magazine, vol. 2, no. 4, pp. 32-37, December 2019.
- N. Jalodia, S. Henna and A. Davy, “Deep Reinforcement Learning for Topology Aware Resource Prediction in NFV Environments”, 2019 IEEE Conference on Network Function Virtualization and Software Defined Networks (NFV-SDN), Dallas, Texas, USA Italy, 2018
- M. Taneja, N. Jalodia and A. Davy, “Distributed Decomposed Data Analytics in Fog Enabled IoT Deployments,” in IEEE Access, vol. 7, pp. 40969-40981, 2019. doi: 10.1109/ACCESS.2019.2907808, URL: https://ieeexplore.ieee.org/document/8675283
- M. Taneja, N. Jalodia, J. Byabazaire, A. Davy, and C. Olariu, “Smartherd management: A microservices-based fog computing assisted iot platform towards data-driven smart dairy farming,” in Software: Practice and Experience, vol. 49, no. 7, pp. 1055-1078, 2019. doi: 10.1002/spe.2704, URL: https://onlinelibrary.wiley.com/doi/full/10.1002/spe.2704
- M. Taneja, N. Jalodia, and A. Davy, “Towards Decomposed Data Analytics in Fog Enabled IoT Deployments – IEEE Internet of Things Newsletter,” September 2018, [Online]. Available: https://iot.ieee.org/newsletter/september-2018/towardsdecomposed-data-analytics-in-fog-enabled-iot-deployments.html
- IEEE Communications Society
- IEEE Computer Society
- IEEE Computational Intelligence Society
- Artificial Intelligence/ Machine Learning Special Interest Group, TSSG