My Journey
From AI research labs to MedTech startups, here's how I've been building technology that matters.
6+ Roles
Across startups and research
Multiple Projects
AI, MedTech, and social impact
Team Leadership
Leading diverse technical teams
Professional Timeline
Each role has shaped my understanding of how technology can create meaningful impact
Founding Engineer
CurrentLeading the development of AI-powered medical diagnostic tools that improve patient outcomes in underserved communities.
Key Achievements:
- •Architected scalable ML pipeline processing 10K+ medical images daily
- •Reduced diagnostic time by 40% through automated analysis algorithms
- •Led cross-functional team of 5 engineers and researchers
Technologies Used:
AI Intern & Team Lead
Developed cutting-edge computer vision models for autonomous systems while leading a team of undergraduate researchers.
Key Achievements:
- •Improved object detection accuracy by 25% using novel attention mechanisms
- •Mentored 3 undergraduate researchers on deep learning projects
- •Published research findings at top-tier AI conference
Technologies Used:
Generative AI Project Lead
Spearheaded the development of enterprise-grade generative AI solutions for Dell's internal tools and customer-facing products.
Key Achievements:
- •Built GPT-powered customer service chatbot serving 50K+ users
- •Reduced support ticket resolution time by 60%
- •Implemented RAG system for internal knowledge management
Technologies Used:
Research Participant
Intensive summer program focused on applying machine learning to healthcare challenges and medical data analysis.
Key Achievements:
- •Developed ML model for early detection of cardiac abnormalities
- •Achieved 92% accuracy on ECG classification tasks
- •Collaborated with MIT researchers and industry partners
Technologies Used:
Research Assistant
Conducted independent research on algorithmic bias in AI systems, focusing on gender representation in machine learning models.
Key Achievements:
- •Analyzed bias patterns across 15 popular ML datasets
- •Developed fairness metrics for evaluating AI model equity
- •Presented findings at UC Berkeley undergraduate research symposium
Technologies Used:
Curriculum Developer
Designed and implemented technology-enhanced curriculum for violence prevention education in high schools.
Key Achievements:
- •Created interactive digital modules reaching 2000+ students
- •Reduced reported incidents by 30% in pilot schools
- •Trained 25+ educators on digital curriculum implementation