physician turned health informatics specialist focused on transforming clinical, operational and user data into actionable insights.
Healthcare AI and data systems focused on workflow automation, accessibility and decision intelligence.
Built a computer vision and soundscape-based navigation tool designed to help visually impaired users better understand and move through physical environments.
Focused on translating AI capabilities into real-world usability through human-centered design and iterative testing.
Integrated environmental exposure, air quality, socioeconomic data, and clinical outcomes using an OMOP-informed framework to analyze asthma burden.
Explored how machine learning and Natural Language Processing can identify early signals of suicide risk from psychiatric notes and social media language.
Built an AI-powered risk detection system for energy contracts, identifying key signals in complex, unstructured legal text.
Built a predictive model exploring lung cancer classification and risk-oriented machine learning approaches.
Built a geospatial platform enabling research scientists to create dynamic maps integrated with real-time external data sources.
Explored secure, interoperable data sharing for clinical trials using blockchain-based architecture to improve transparency and trust in research data.
Focused on how emerging technologies can support real-world evidence, data integrity, and multi-party collaboration in healthcare systems.
Making complex concepts in AI, data, and emerging technologies accessible and practical.
Developed an interactive lecture introducing sentiment analysis and NLP concepts through real-world examples and practical applications.
Created educational content explaining AI, data science, and technology concepts for broader audiences.
My work connects clinical experience, data systems, and product thinking.
I started my career as a clinician, where I saw firsthand how critical insights are often buried within conversations, documentation, and everyday workflows.
That experience fundamentally shaped how I view technology and that the most powerful systems don’t just process data, rather, they enable people to make better, more informed decisions.
I currently work across healthcare data analytics, applied AI, and informatics, with graduate training in Health Informatics at Weill Cornell Medicine.
I am especially interested in real-world data, EHR systems, interoperability, clinical NLP, and AI tools that turn unstructured information into practical insight.
Clinical depth, data work, product building, and stakeholder-facing communication.
Analyze engagement data to improve digital literacy programs, support high-impact community events, and identify trends that inform service delivery.
Built agentic AI systems for cybersecurity and decentralized applications, contributed to platforms reaching 3,000+ users, and developed classification models using Python, scikit-learn, MLflow, and Docker.
Led data-driven clinical partnerships, supported regulatory and access initiatives, facilitated stakeholder discussions, and trained 100+ sales associates with metrics-based feedback.
Delivered primary and preventive care to 40–80 patients daily, building deep expertise in clinical workflows, patient care, and healthcare operations.
Selected awards, mentorship, and innovation work across AI, healthcare, accessibility, and emerging technologies.
+ additional awards across AI, Web3, data, security, and healthcare innovation.