Research

My research focuses on Optimization, Smart Grid Technologies, electric vehicles, and Reinforcement Learning

Research Areas

Optimization Algorithms

I develop and apply advanced optimization techniques to solve complex problems in real-world scenarios. This includes both traditional approaches and AI-based methods to achieve optimal solutions under various constraints.

  • Reinforcement learning for Optimization
  • Heuristic optimization
  • Real-time optimization
  • Multi-objective optimization techniques
  • Machine learning for prediction and optimization

Electric Vehicles

My EV research explores optimal routing, scheduling, and charging strategies for electric vehicles, with a particular focus on Vehicle-to-Grid (V2G) and Vehicle-to-Vehicle (V2V) technologies that enable bidirectional energy flow between vehicles and the grid.

  • V2G and V2V integration with microgrids
  • Optimal EV routing and scheduling
  • Battery-aware EV management
  • Vehicle-on-demand systems

Smart Grid Technologies

My research in smart grid technologies focuses on developing innovative algorithms for efficient energy management and distribution. This includes real-time monitoring, control systems, and optimization of energy resources to maximize efficiency and minimize costs.

  • Microgrid management and optimization
  • Renewable energy integration
  • Efficient resource allocation in smart grids
  • Cost optimization algorithms for energy distribution

Scheduling and Resource Management

My research in scheduling focuses on efficient allocation of resources in complex systems, particularly in microgrids and energy distribution networks, to optimize performance, reduce costs, and enhance reliability.

  • Appliance scheduling in smart grids
  • Energy resource scheduling
  • Real-time scheduling algorithms
  • Multi-objective scheduling optimization

Current Projects

Adaptive Re-purposing of Second-life Electric Vehicle Batteries for Diverse Applications

Active

It promotes sustainable energy practices by extending the lifecycle of EV batteries but also enhances energy resilience in microgrids and accelerates the adoption of EVs by addressing critical infrastructure gaps. It sets the stage for scalable solutions in energy optimization and smart mobility.

Duration: 2024-2026
Funding: IIT(ISM) Dhanbad Funded

Research Opportunities

For PhD Students

I'm looking for motivated PhD students with strong backgrounds in computer science, electrical engineering, or related fields, to work on projects related to smart grid optimization, electric vehicle management, and machine learning applications in energy systems.

Current openings are available in the following areas:

  • AI-based optimization
  • Electric vehicle routing and charging optimization
Contact for Details

For Collaborations

I welcome research collaborations with academic and industry partners interested in smart grid technologies, electric vehicle management, optimization algorithms, and related fields.

Potential collaboration areas include:

  • Joint research projects
  • Industry partnerships for real-world implementation
  • Academic collaborations on optimization algorithms
Discuss Collaboration