Areas of Research -Swarm Robotics, Multi-Agent Systems, Mobile Robots, Machine Learning

• Developing an advanced vision-language multi-modal model for real-time guidance in robotic surgery, integrating vision and language encoders to interpret direction prompts and surgical images, generating a relevant answer based on the trained data from the JIGSAWS dataset.• Leveraging data curation methods, such as those mentioned in LLaVa, to generate more surgical data(with the goal of implementing semantic reasoning) using three distinct prompts: Conversation, Detailed Description, and Complex Reasoning. This totaled to more than 330,000 data samples that were used to train the model.

• Collaborated with a cross-functional team to provide technical support and contribute to the development of operational tools and software solutions aimed at preventing unscheduled downtime. • Made multiple automation’s for different departments effectively speeding processes by at least 90%, with procedural scripts that can be repeated by any background.

 Participated in a competitive NSF REU program at Texas A&M University-Corpus Christi, focusing on applied computing research in unmanned aerial systems (UAS) and their coastal environmental applications.  Collaborated with a diverse team of undergraduate researchers, developing secure and autonomous UAS technology for data collection, storage, and analysis.