Joining two research labs, excited to share what we work on!

• Developed an end-to-end document intelligence system to extract structured data from unstructured blob documents (e.g., mortgage and financial records), reducing manual review time by 99%+ and cutting processing latency from hours to seconds.
• Built and evaluated OCR and document preprocessing pipelines using OpenCV, regex, and Python-based data cleaning to improve text extraction quality, alignment, and downstream model accuracy across noisy real-world documents.
• Designed and implemented LLM-powered RAG (Retrieval-Augmented Generation) pipelines to ground model outputs in extracted document content, improving factual accuracy and reliability for document-based question answering.
• Developed an interactive Gradio-based chatbot interface that allows users to query processed documents in natural language, enabling rapid validation, exploration, and human-in-the-loop review of extracted data.
• Applied machine learning workflows for data formatting, extraction, and visualization using pandas and matplotlib, analyzing failure cases and iteratively refining preprocessing and model behavior to improve system robustness.
• Integrated OpenAI and PyTorch-based LLM components into the processing pipeline, combining traditional OCR techniques with modern language models to handle complex layouts, variable formatting, and semantic extraction tasks.

• Planned, organized, and led weekly peer-assisted study sessions for Calculus and Statistics courses, independently designing session structure, problem sets, and instructional strategies to reinforce core mathematical concepts and exam readiness.
• Proactively marketed and promoted sessions through campus outreach and peer networks, driving consistent attendance and engagement without direct faculty oversight.
• Facilitated large-group problem-solving discussions, breaking down complex concepts into clear, intuitive explanations that enabled students of varying backgrounds to reach understanding and apply techniques independently.
• Mentored students in independent learning strategies, emphasizing analytical thinking, self-debugging, and effective study methods rather than dependency on instructors or tutors.
• Built strong cross-year peer relationships, collaborating with upperclassmen and repeat attendees to foster a supportive learning environment and sustained academic progression.
• Earned 100% satisfaction ratings in anonymous student feedback surveys, with students citing leadership, clarity of instruction, and measurable improvement tied directly to session participation.

• Managed and organized student performance and attendance data to track tutoring progress, identify trends, and support data-driven instructional decisions across multiple students.
• Designed and maintained streamlined data-tracking processes for recording outcomes, improving consistency, accuracy, and ease of analysis for tutors and administrators.
• Supported mentorship and tutoring initiatives by working directly with younger students, building strong relationships that encouraged engagement, confidence, and long-term academic growth.
• Collaborated with tutors and staff to translate performance data into actionable insights, helping tailor support strategies to individual student needs.
• Planning and developing a web-based platform to centralize student records, streamline reporting workflows, and improve accessibility and transparency for stakeholders

Founded and operated a successful detailing business in Stone Mountain, Georgia. Managed all aspects of business operations including client relations, service delivery, and business development.