About the Authors

Highlights

• B.S. Computer Science & Mathematics @ University of Florida (2024-2027)
• Volunteer Researcher @ MIRTH AI Lab (2024-Present)
• OPS Employee @ Computational Microscopy Imaging Laboratory (2025-Present)

Research Interests

• Self-supervised learning.
• Diffusion models and flow matching.
• Reinforcement learning.
• Geometric constraints and feature representations (manifolds, spectral structure).
• Current focus: flow matching for medical image synthesis and geometric representation learning.

Timeline

Volunteer Researcher, MIRTH AI Lab

• Period: 2024 - Present
• Location: Gainesville, FL
• Trained diffusion and flow-matching generative models for high-fidelity medical image synthesis.
• Developed implicit neural representations (INRs) for resolution-independent volumetric analysis.

OPS Employee, Computational Microscopy Imaging Laboratory

• Period: 2025 - Present
• Location: Gainesville, FL
• Contributing to a large NIH-funded grant focused on multimodal AI predictions for nephrology.
• Built self supervised abstract feature extraction pipelines across medical imaging modalities including ultrasound.
• Trained semantic embeddings from clinical reports using encoder-decoder architectures.

B.S. Computer Science, B.S. Mathematics, University of Florida

• Period: Aug 2024 - May 2027
• GPA: 3.95 / 4.00
• Relevant coursework:
  • Deep Learning in Medical Image Analysis
  • Linear Algebra for Data Science
  • Real Analysis with Advanced Calculus I and II

Publications

Geometry-Aware Implicit Neural Reconstruction of Oblique Micro-Ultrasound Scans

• Venue: In review at CMIG (2026)
• Code: https://github.com/mirthAI/GeometryAware-MicroUS-INR

AortaGPT: An Interactive Vision-Language System for Aortic CT Analysis

• Venue: Under review (2026)

Highlights

• Incoming M.S. Computer Science @ Rice University (Fall 2026)
• B.S. in Computer Science @ University of Florida (Aug 2022 - May 2026)
• Undergraduate Researcher @ MIRTH AI Lab (Jan 2025-Present)

Research Interests

• Large Language Models (LLMs) and Vision-Language Models (VLMs).
• Theoretical foundations of AI, information theory, and Reinforcement Learning (RLVF).
• High-Performance Computing (HPC) and distributed training (Data/Expert Parallelism).
• Current focus: Reinforcement learning for medical VLMs, and optimizing distributed model training.

Timeline

Undergraduate Researcher, MIRTH AI Lab

• Period: Jan 2025 - Present
• Location: Gainesville, FL
• Developing deep learning model for 3D MRI segmentation to quantify brain volumes in preterm infants, directly impacting clinical evaluations of antibiotic exposure.
• Implementing Reinforcement Learning pipelines using Group Relative Policy Optimization (GRPO) for Medical 3D Vision-Language Models (VLM).

Lead ML Engineer, GatorLM

• Period: Jan 2026 - Present
• Location: Gainesville, FL
• Building a full-stack AI chatbot and managing the project architecture for a custom-trained DeepSeek-style LLM.
• Developed and trained a 9B parameter Mixture of Experts (MoE) model from scratch.
• Leveraged NVIDIA Blackwell B200 GPUs on the HiPerGator cluster, utilizing Transformer Engine for FP8 training to maximize throughput.
• Implemented a distributed training strategy combining Data Parallelism, Expert Parallelism, and Optimizer Sharding to handle the model’s scale efficiently.

Teaching Assistant, University of Florida

• Period: Jan 2024 - Jun 2024 & Spring 2026
• Location: Gainesville, FL
• Mentored students in C++ and Python, reinforcing core concepts of memory management and data structures.
• Developed exams and technical assessments to test students programming skills and conceptual understanding.

B.S. in Computer Science, University of Florida

• Period: Aug 2022 - May 2026
• GPA: 3.59 / 4.00
• Relevant Coursework:
  • Information Theory
  • Deep Learning in Medical Image Analysis
  • Linear Algebra
• Additional Coursework: Signals and Systems

Key Projects & Research

Medical AI Agent (Full Stack AI)

• Built an agentic framework integrating LLM orchestration with MONAI 3D segmentation tools.
• Engineered a sandboxed Python execution environment to allow the agent to run analysis code autonomously, bridging software design with deep learning applications.