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shiva1387/README.md

Shivshankar Umashankar

LinkedIn Google Scholar

πŸ‘‹ Welcome to my GitHub!

I am an AI and healthcare data science leader with over 15 years of experience, specializing in developing advanced AI/ML solutions, knowledge graphs, and digital health strategies. I have worked extensively in the domains of personalized medicine, population health, and AI ethics, particularly within the healthcare sectors in Singapore and India.

🌐 About Me

  • Expertise: AI/ML in Healthcare, Knowledge Graphs, Personalized Medicine, Population Health, AI Ethics.
  • Current Focus: Digital twins, healthcare analytics, and AI ethics frameworks in healthcare.
  • Publications: 20+ scientific papers, 1000+ citations, h-index: 9. View Publications
  • Patents: 5 international patents for AI/ML applications in healthcare. View Patents

πŸš€ My Projects

Here are a few highlighted projects that represent my journey in AI and healthcare:

  1. Healthcare Digital Twins: Developed and deployed digital twin models at Holmusk to simulate patient journeys and healthcare interventions, enabling real-time decision-making for clinical outcomes and remote health monitoring.

  2. AI-Driven Knowledge Graphs: At PatSnap, I led the development of AI-powered knowledge graphs that integrate multi-modal data (e.g., genomics, IoT, and clinical records) to generate healthcare insights and inform strategic R&D decisions in life sciences.

  3. Population Health Models: At PwC and Holmusk, I worked on building AI-driven population health models that leverage real-world data (EHR, SDoH, claims) to predict disease risks, optimize treatment protocols, and improve healthcare delivery for national health systems in Singapore and India.

  4. Data Governance and Quality Frameworks: As Lead Data Scientist at Holmusk, I designed and implemented data governance frameworks in Databricks, enabling enhanced data quality management and efficient deployment of AI/ML solutions for healthcare clients.

πŸ›  Skills & Tools

  • Programming Languages: Python, R, SQL
  • Data Platforms & Tools: Databricks, Neo4j, TensorFlow
  • Specializations: Knowledge Graphs, NLP, AI in Healthcare, Data Analytics
  • Healthcare IT: Healthcare IT & Analytics Program Management, Population Health Models, Predictive Analytics
  • AI/ML Expertise: AI/ML Model Development, Data Product Development, Digital Twins, Personalized Medicine
  • Management & Leadership: Stakeholder Engagement, Cross-Functional Team Leadership, Strategic Planning, Leadership

πŸ“« Contact

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  1. datacarpentry/R-ecology-lesson datacarpentry/R-ecology-lesson Public

    Data Analysis and Visualization in R for Ecologists

    R 315 506

  2. CapsNet-Tensorflow CapsNet-Tensorflow Public

    Forked from naturomics/CapsNet-Tensorflow

    A Tensorflow implementation of CapsNet(Capsules Net) in Hinton's paper Dynamic Routing Between Capsules

    Python 1

  3. BatchEffects BatchEffects Public

    Algae metabolomics data analysis

    R 1 1

  4. cdiscount-kernel cdiscount-kernel Public

    Forked from drauh/cdiscount-kernel

    Open cxflow kernel for cdiscount image classification Kaggle competition.

    Python

  5. dragonn dragonn Public

    Forked from kundajelab/dragonn

    A toolkit to learn how to model and interpret regulatory sequence data using deep learning.

    Python

  6. microbiome_helper microbiome_helper Public

    Forked from LangilleLab/microbiome_helper

    An assortment of scripts to help process and automate various microbiome and metagenomic bioinformatic tools.

    Perl