VR Developer & AI enthusiast from Arlington, Texas. Specializing in immersive technologies, machine learning, and full-stack development. Currently pursuing Computer Science at UT Arlington while working on cutting-edge VR simulations and AI-powered solutions.
Lead VR Developer & Back-end for UTA IMSE Department. Multiplayer powder bed fusion machine simulation using Unity Netcode, training 3+ operators simultaneously across distributed locations. Achieved $15,000 annual cost reduction and 41% decrease in machine downtime.
                        Lead ML & Front-end developer. Document intelligence pipeline utilizing Microsoft DiT & LayoutLMv3 to automate 90% of mortgage document processing, enhancing data accuracy by 25% & halving processing time.
                        Team Lead for Team Croissant. Developed AI-powered predictive beauty analytics tool using machine learning algorithms to assess personalized hair and skin condition risks based on product usage patterns, enabling proactive beauty care recommendations.
MERN Stack
API Development
Cloud Storage
Firebase & MongoDB
Database Management
Application Development
Framework
Design & Prototyping
Expected Graduation: December 2026
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                                        University of Texas at Arlington Engineering Department | Arlington, Texas
                                        β’ Spearheaded collaboration with Fort Worth Police Department to optimize VR de-escalation simulations using dynamic branching scenarios
                                        β’ Integrated Google Cloud Text-to-Speech for automated, context-aware audio prompts in real-time VR training
                                        β’ Enhanced high-fidelity VR simulations using Unity3D & Unreal Engine, achieving 25% boost in workflow efficiency
                                        β’ Reduced training iteration cycles by 20% through Python-based analytics pipeline and data mining techniques
                                    
                                        Codepath | Remote
                                        β’ Facilitated student success in TIP102 course by conducting weekly technical workshops and code reviews
                                        β’ Delivered 1-on-1 Python & JavaScript debugging support
                                        β’ Graded complex assignments, resulting in improved completion rates & elevated project quality
                                    
                                        Extern | Remote
                                        β’ Streamlined AI-driven workflows for document classification & data extraction using NLTK, spaCy, & Gensim, improving accuracy by 30% & reducing processing time by 50%
                                        β’ Achieved 25% boost in information search accuracy by orchestrating retrieval system utilizing LlamaIndex & RAG
                                        β’ Delivered comprehensive analysis report on AI models (BERT, GPT-3, RoBERTa, XLNet, ALBERT), identifying 15% cost savings
                                    
                                        Computer Science
                                        University of Texas at Arlington
                                        Arlington, Texas
                                    
ReactJs β’ JavaScript frameworks β’ TCP/IP networking β’ AWS Lambda β’ Python scripting β’ SQL Azure β’ UNIX/Linux β’ Machine Learning β’ Pandas β’ NumPy β’ Google Cloud Platform β’ Kubernetes