Personal profile
Research Interests
Dr. Himanshu Sharma is a Postdoctoral Researcher at Technological University Dublin working within the ARISE programme on AI-assisted communications engineering and energy-efficient Open Radio Access Networks (O-RAN). His work focuses on applying Artificial Intelligence and Machine Learning to optimize energy usage, resource allocation, and operational efficiency in next-generation communication systems and other resource-constrained environments.
He holds a PhD in Computer Science and Engineering from Thapar Institute of Engineering and Technology, where his research centered on AI-enabled, energy-efficient, and secure data transmission in 5G heterogeneous networks. Over the years, Dr. Sharma has developed strong expertise in designing data-driven optimization models that translate complex system data into actionable decision-support tools. His research spans AI for networking, energy optimization, edge intelligence, and applied machine learning for real-world systems.
At TU Dublin, his role combines advanced research with industry engagement. He collaborates with enterprises to identify practical challenges and design AI-based solutions that can be rapidly prototyped and evaluated, supporting the university’s mission of research translation and industry impact.
Dr. Sharma has published in leading international journals inclding IEEE Transactions and IEEE Flagship conferences in AI, communications, and applied optimization. He has also supervised multiple student research projects and is passionate about bridging the gap between theoretical research and deployable solutions. His broader interests include AI for sustainable systems, intelligent resource management, and applied optimization in agriculture, energy, and communication networks.
Research Interests
- AI/ML for energy-efficient communication networks (O-RAN, 5G/6G)
- Resource optimization in data-driven systems
- Edge intelligence and distributed learning
- Applied AI for sustainable energy and agriculture
- Decision-support systems under limited data conditions
Current Focus at TU Dublin
- AI-driven energy reduction strategies in Open RAN architectures
- Industry-linked problem solving through applied AI research
- Experimental evaluation on real networking platforms and testbeds
Dr. Sharma is keen to collaborate with industry partners and researchers interested in applied AI solutions for sustainable and efficient technological systems.
Education/Academic qualification
PhD, Energy-Efficient Secure Transmission Techniques for 5G Enabled Heterogeneous Networks, Thapar Institute of Engineering and Technology
Award Date: 26 Oct 2023
Collaborations and top research areas from the last five years
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Scheduling irrigation with artificial intelligence: a systematic review on evapotranspiration based techniques
Sharma, G., Sharma, H., Jain, S., Singh, A. & Biswas, S., 2026, In: PeerJ Computer Science. 12, e3677.Research output: Contribution to journal › Article › peer-review
Open Access -
Comparative Analysis of Deep Learning Models for Sentiment Classification of Indian Automobile YouTube Comments
Yadav, N., Chaudhary, S., Sangwan, A. & Sharma, H., 2025, 2025 IEEE 7th International Conference on Computing, Communication and Automation, ICCCA 2025. Institute of Electrical and Electronics Engineers Inc., (2025 IEEE 7th International Conference on Computing, Communication and Automation, ICCCA 2025).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
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Multi-Task Learning Model for Fine-Grained Categorization of Emergency Tweets
Nandan, A., Pradhan, L., Sharma, H., Bhola, A. & Srivastava, A., 2025, 2025 17th IEEE International Conference on Computational Intelligence and Communication Networks, CICN 2025. Institute of Electrical and Electronics Engineers Inc., p. 2045-2050 6 p. (2025 17th IEEE International Conference on Computational Intelligence and Communication Networks, CICN 2025).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review