Shubham Vaishnav PhD Student
Contact
Name and title: Shubham VaishnavPhD Student
ORCID0000-0001-7612-4227 Länk till annan webbplats.
Workplace: Department of Computer and Systems Sciences Länk till annan webbplats.
Visiting address Nodhuset, Borgarfjordsgatan 12
Office hours Mon-Fri, 8:00-17:00
Postal address Institutionen för data- och systemvetenskap164 25 Kista
Research group
Links
- Dynamic and Distributed Routing in IoT Networks based on Multi-Objective Q-Learn Länk till annan webbplats.
- Communication-Adaptive Gradient Sparsification for FL with Error Compensation Länk till annan webbplats.
- Book chapter: "Multiobjective and Constrained Reinforcement Learning for IoT"" Länk till annan webbplats.
- Energy-Efficient and Adaptive Gradient Sparsification for Federated Learning Länk till annan webbplats.
- Mobile Charger Scheduling using Partial Charging Strategy Länk till annan webbplats.
- Intelligent Processing of Data Streams on the Edge Using Reinforcement Learning Länk till annan webbplats.
- Adaptive Budgeted Multi-Armed Bandits for IoT with Dynamic Resource Constraints Länk till annan webbplats.
About me
I find myself fascinated by the breakthroughs in Artificial Intelligence (AI) in general and their application in wireless communications and networking, in particular. I am carrying out research in the field of AI-driven multiobjective optimization and decision-making, with applications to Internet of Things (IoT) and wireless networks. Having a plethora of enthusiasm for researching and teaching, I work in the research group of Associate Prof. Sindri Magnusson. I have published papers on topics related to federated learning, reinforcement learning, resource-adaptive, and multiobjective decision-making in IoT and wireless networks. My publications are in top venues in the IEEE Communications Society, like the IEEE Internet of Things Journal, IEEE International Conference on Communications (ICC), IEEE Global Communications Conference (Globecom), and in Springer.
I have successfully supervised 27 theses of Master's and Bachelor's students. I have also delivered lectures on Reinforcement Learning and Clustering for Master's level courses at DSV, SU. I have also contributed to conducting lab sessions, tutorial sessions, and grading of students.
- Multiobjective Optimization
- Federated Learning
- Reinforcement Learning
- Wireless, IoT, and Fog networks
- AI-driven Resource-Adaptive decision-making in IoT
