About Me
I'm a Ph.D. candidate at the University of South Carolina, focusing on developing planning strategies for dynamic environments. My research aims to develop more efficient and adaptable planning systems that can handle complex real-world scenarios.
ResumeMy research interests span across:
Published at: (Outlined - first authorship)
Featured Research
Planning Strategies for Dynamic Opinion Networks
Developed intervention strategies using ranking algorithms and neural network classifiers for accurate information dissemination in dynamic networks. Created a reinforcement learning framework analyzing multiple reward structures for network dynamics.
- Deep Learning
- Reinforcement Learning
- Network Analysis
Automated Planning with Large Language Models
Spearheaded the development of datasets for fine-tuning LLMs in automated planning scenarios. Evaluated various LLM architectures for planning tasks and developed the Plansformer model.
- PDDL
- Large Language Models
- Python
Selected Publications
Towards Effective Planning Strategies for Dynamic Opinion Networks
Bharath Muppasani, Protik Nag, Vignesh Narayanan, Biplav Srivastava and Michael N. Huhns
Building a Plan Ontology to Represent and Exploit Planning Knowledge
Bharath Muppasani, Nitin Gupta, Vishal Pallagani, Biplav Srivastava, Raghava Mutharaju, Vignesh Narayanan, and Michael N. Huhns
Experience
Research Assistant
University of South Carolina
Conducting research in automated planning, deep learning, and reinforcement learning. Developing novel approaches for dynamic opinion networks and planning with large language models.
- Automated Planning
- Machine Learning
- Ontology
Research Intern
Indian Institute of Technology, Kharagpur - Samsung Research
Conducted analysis on multi-resident smart home data, focusing on time, sensor, and frequency-based segmentation. Developed unsupervised algorithms for activity classification.
- Data Analysis
- Sensor Data
- Smart Home