Snipta Mallick is passionate about transforming healthcare through artificial intelligence and data science innovation.
Snipta is a Data Scientist at the National Institutes of Health, where she leads initiatives that bridge the gap between cutting-edge AI research and real-world healthcare applications. Her work focuses on advancing clinical data interoperability and developing innovative solutions that improve how medical institutions share and utilize patient information. She has designed award-winning training programs and organized large-scale workshops that bring together researchers, clinicians, and technologists to accelerate healthcare innovation.
At NIH, Snipta develops AI-powered tools that streamline complex processes and unlock insights from vast healthcare datasets. Her projects span from natural language processing applications that enhance decision-making efficiency to interactive platforms that help leadership understand funding patterns and research trends. She has also led digital transformation initiatives that significantly improve user engagement and accessibility of critical healthcare resources.
Beyond her federal work, Snipta has contributed to both academic research and industry innovation. Her experience spans from developing advanced algorithms for emerging technologies to publishing research that advances our understanding of human perception and global health systems. She brings a unique interdisciplinary perspective that combines technical expertise with deep insights into cognitive science and human-centered design.
Snipta holds dual degrees in Computer Science and Cognitive Science from the University of Texas at Dallas and is currently pursuing advanced studies in Artificial Intelligence at UT Austin. Her academic foundation in both technical and behavioral sciences informs her approach to creating AI solutions that are not only powerful but also intuitive and equitable.
Born and raised in Texas, Snipta is committed to democratizing access to healthcare technology and ensuring that AI innovations benefit all communities. She actively mentors emerging professionals and contributes to the broader conversation about responsible AI development in healthcare through her research, speaking engagements, and collaborative work across government, academia, and industry.
Featured Projects
Key initiatives and technical solutions I've developed
FHIR Training Program Development
Designed and implemented comprehensive FHIR training programs for clinical research institutions, focusing on modular and reusable educational frameworks for healthcare professionals.
NLP Grant Categorization System
Developed an AI-powered text classification tool using Python and machine learning techniques to automatically categorize NIH grant applications with 94%+ accuracy.
Interactive Grant Analytics Dashboard
Created the first interactive data visualization dashboard to analyze and present $9+ billion in data science grants, empowering agency leadership to identify funding trends.
Professional Experience
My journey in AI, healthcare informatics, and data science
Data Scientist
Leading healthcare data exchange and clinical interoperability initiatives across multiple NIH institutes, promoting adoption of FHIR, OMOP, and CDEs while delivering award-winning training programs and data-driven insights to leadership and Congress.
Data Scientist Fellow
Streamlined funding application management processes and developed innovative AI-powered tools for grant categorization and data visualization, significantly improving efficiency and decision-making capabilities.
Software Engineering Intern
Developed production-level C++ profiling tools and scripts for 5G telecommunications infrastructure, building real-time performance monitoring dashboards and resolving critical technical issues.
Publications & Presentations
2025
NIH Program Officer Panel Sets the Stage for Day 2 of 2025 AIM-AHEAD Annual Meeting
Served as panelist on the NIH Program Officers Panel at the 2025 AIM-AHEAD Annual Meeting, discussing updates and strategies for current research initiatives in artificial intelligence, machine learning, and biomedical research alongside NIH leadership.
2024
FHIR-ing Up Clinical Research: Developing Modular and Reusable FHIR® Trainings for IDeA State Institutions
Developed comprehensive FHIR training programs for clinical research institutions, focusing on modular and reusable educational frameworks for healthcare professionals.
2023
Private pharmacies as healthcare providers in Odisha, India: analysis and implications for universal health coverage
Comprehensive analysis of private pharmacy healthcare delivery in Odisha, India, with contributions to data analysis for universal health coverage research.
2022
Conversation with the Coding it Forward Civic Digital Fellow, Snipta Mallick
Featured interview discussing Snipta's journey from Coding it Forward fellow to full-time NIH employee, highlighting her work in data science, FHIR implementation, and civic technology in healthcare.
2022
The Influence of the Other-Race Effect on Susceptibility to Face Morphing Attacks
Research on facial recognition security vulnerabilities, examining how racial bias affects susceptibility to face morphing attacks in biometric systems.
2019
Ultra-Stabilization of Green Fluorescent Protein (GFP) using Metal-Organic Frameworks (MOFs) for Gold Sensing Applications
Presented research on protein stabilization techniques using metal-organic frameworks for enhanced biosensing applications in gold detection.
Get In Touch
Let's Connect
I'm always interested in discussing new opportunities in AI, healthcare informatics, and data science. Whether you have a project in mind or just want to chat about the latest developments in healthcare AI, I'd love to hear from you.