- Leading research in Neuro-symbolic AI and NLP, focusing on planning, knowledge graphs, and multimodal AI systems under Dr. Biplav Srivastava.
- Organized Safe AI for Seniors, a full-day hybrid event with 80+ attendees, securing AAAI sponsorship and coordinating 8+ expert speakers.
- Mentored students in research methodologies, resulting in successful conference submissions and improved experimental design.
- Published 4+ peer-reviewed papers at premier AI conferences on explainable AI, generative AI evaluation, and AI planning.
- Peer-reviewed 10+ research papers for top-tier AI conferences, ensuring quality and relevance in the field.
AI
Neuro-symbolic AI
NLP
Event Organization
Mentorship
- Promoted organ, eye, and tissue donation at the University of South Carolina through community outreach.
- Successfully persuaded over 300 individuals to register as donors on the national organ donor registry.
Community Outreach
Public Speaking
Leadership
- Developed a novel framework integrating Planning Ontology with LLMs to generate transparent, context-aware explanations for AI-generated plans
- Demonstrated significant improvements in reasoning capabilities of smaller LLMs through ontology-enhanced prompts, contributing to the field of Explainable AI by enhancing user understanding and trust
- Presented research findings at the 2024 Summer Research Symposium, receiving positive feedback from industry professionals
- Also, worked on conducted traffic data analysis for the SCDHEC, SCDPS, NSCSC by identifying collision patterns and evaluating safety programs
- Worked under Dr. Biplay Srivastava and PhD student Bharath Muppasani for both projects
Explainable AI
LLMs
Data Analysis
Research
- Worked with teams at the University of Virginia, University of North Carolina Chapel Hill, and the University of South Carolina to develop ML methods for the OnTheBooks project
- Conducted data mining on South Carolina Laws using Python and Natural Language Processing
- Trained machine-learning (ML) algorithms to study the prepared session laws and identify Jim Crow Language
Machine Learning
NLP
Python
Data Mining
- Enhanced high energy physics research by developing C++ analysis code to process simulated data for various magnet materials, leading to potential cost savings of over $1,000,000
- Contributed to the design of a muon detection system for a new particle accelerator using data analysis
- Strengthened the magnet material effect study in high energy physics using data analysis through SSH
C++
Data Analysis
Physics
SSH
- Designed interactive, web-based documents and tools for data visualizations under the Digital Research Services department
- Strengthened the University Library's data analysis tools for public and future use
Data Visualization
Web Development
Research
- Created Python machine learning algorithms to beat games
- Presented these implementations at the GSSM Annual Research Colloquium and SCJAS 2021
- Worked under Dr. Yuyuan "Lance" Ouyang
Python
Machine Learning
AI
Game Development
