Computer Science + Biomedical Sciences
Building safer AI systems at the intersection of machine learning and healthcare
I believe that as AI systems become more powerful, ensuring their safety and alignment with human values becomes paramount. My work focuses on developing rigorous testing methodologies for bio-foundational AI while creating healthcare applications that genuinely empower patients and practitioners.
Specialized expertise across AI safety, computer vision, and biomedical applications
Developing adversarial testing frameworks and red-teaming methodologies for generative bio-foundational models. Specializing in vulnerability assessment, jailbreak detection, and safety protocol evaluation.
Implementing pose estimation pipelines, gait analysis algorithms, and real-time inference systems optimized for edge deployment on resource-constrained hardware.
Architecting HIPAA-compliant ML systems with on-device inference, federated learning considerations, and clinical workflow integration for diagnostic and therapeutic applications.
Building scalable microservice architectures with React/React Native frontends, Node.js backends, and cloud infrastructure leveraging containerization and CI/CD pipelines.
Healthcare-focused AI systems designed for real-world impact
Project Manager / AI Engineer / Backend Developer
Mobile application implementing a hybrid CV-NLP pipeline for geriatric fall risk assessment using the PEER clinical framework. The computer vision module performs real-time pose estimation and gait analysis to quantify fall risk scores and validate exercise form compliance. A distilled language model runs inference on-device to deliver context-aware psychological reinforcement. Both models are quantized and optimized for mobile NPUs to ensure patient data never leaves the device. Backend services deployed on Google Cloud with HIPAA BAA compliance. Frontend built in React Native with WCAG 2.1 AA accessibility standards for geriatric usability.
Co-Founder / Full Stack Developer / AI Engineer
AI-powered platform automating administrative workflows for private medical practices. Validated product-market fit through 50+ physician interviews across multiple specialties. Currently in active development.
maiamed.aiFounder / Full Stack Developer / AI Engineer
Neural compression system for whole slide images (WSIs) addressing the storage bottleneck in digital pathology where single slides exceed 1GB. Implemented a VQ-VAE architecture with a learned discrete codebook for latent space quantization, paired with a separate decoder network to preserve diagnostic-quality reconstruction. Achieved 84x compression ratio (272.52MB → 3.24MB) with minimal perceptual loss. Built in 36 hours at Startup Weekend Orlando. React frontend communicates with a Flask API backend running inference on a vast.ai L40S GPU instance.
https://youtu.be/i3qQa6fLZYIFounder / Full Stack Developer / AI Engineer
Multi-platform surgical outcome prediction system. iOS client built in Swift captures facial geometry and transmits to GPU inference server. Core generation model is DreamOmni2 fine-tuned with LoRA adapters on procedure-specific datasets to predict post-operative facial morphology. React webapp integrates Web Speech API for voice-controlled surgeon interaction. Implemented content filtering guardrails using CLIP embeddings to restrict input/output to facial imagery only.
Frontend Mobile Developer
Cross-platform mobile application aggregating student organization events into a unified feed. Translated high-fidelity Figma prototypes into production Flutter code with custom widget composition. Implemented infinite scroll pagination with lazy loading for optimized memory footprint. Achieved WCAG compliance through Lighthouse audits, semantic markup, and VoiceOver/TalkBack screen reader testing. Maintained platform parity across iOS and Android rendering pipelines.
Academic positions driving innovation in AI safety and computer vision
Dr. Bedi's SAFERR AI Lab, UCF
Center for Research in Computer Vision REU, UCF
Open to research collaborations, opportunities in AI safety, and healthcare AI projects