The people building Verena, from research through production. Verena is built by researchers who train the models themselves, from medical imaging to large language models, and stay accountable for the work from first scope through production.
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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
AortaGPT: An Interactive Vision-Language System for Aortic CT Analysis
- Venue: Under review (2026)
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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.