Our story

We started off as a small community of healthcare researchers, who were interested in applying artificial intelligence to solve and scale healthcare challenges.

Our community growth and our mission necessitated a more formal organizational structure. In 2019, we became a 501(c)3 tax exempt organization in the state of New York.

In spite of the recent challenges; our team and our community have been resilient and resolute in our mission to build ethical, equitable and explainable healthcare artificial intelligence solutions.

The current advancements in the area of artificial intelligence, especially around generative models; have demonstrated both the capabilities and pit-falls of this powerful technology.

It has reinforced the belief in our mission to provide cutting-edge education, training and research for health applications of artificial intelligence. It has also instilled a new vigor in our pursuit to build human-centric, beneficial and benevolent artificial intelligence tools for healthcare.

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Team and Mission

Rahul Remanan


Nick Giangreco


Our mission

Board of directors

Rahul Remanan

Dr. Rahul Remanan is a physician turned artificial intelligence entrepreneur. He has over a decade of experience in machine learning and scientific computing in healthcare. His multi-disciplinary skill-sets in healthcare, consulting, enterprise software and community development has helped New York Health Artificial Intelligence Society grow from its original roots as a small scientific discussion community in New York; to attain its current stature as a leading proponent of ethical, explainable, equitable AI in healthcare. Rahul is currently the CEO of Moad Computer, an enterprise AI solutions firm.

  • Python, Tensorflow
    Deep learning research and application development using convolutional, attention and recurrent neural networks for image, text and tabular data
  • R, Python, SciPy, SciKit-Learn, NumPy, Pandas
    Scientific computing, short-term and medium-term forecasting, data-science, numerical methods for genomics and proteomics
  • Vega, Bokeh, Leaflet
    Business analytics, interactive visualizations and dashboards
  • Bachelor of Medicine and Bachelor of Surgery (MBBS)
    2003 - 2009: All India Institute of Medical Sciences, New Delhi, India
  • Post doctoral researcher
    2010 - 2016: Neurological applications of transcranial magnetic stimulation and machine learning
  • Bio medical engineering training
    2014 - 2015: Short course in nanotechnology at Meinig School of Bio Medical Engineering at Cornell, Ithaca, New York, United States
  • Clinical research
    Combining neurophysiology and clinical data using machine learning in Amyotrophic Lateral Sclerosis (ALS)
  • Radiology and deep-learning
    DICOM data for deep learning, breast cancer detection using mammography
  • Explainable deep-learning
    Development of Bayesian class activation maps for machine vision based deep neural networks

Nick Giangreco

Dr. Nick Giangreco is a precision medicine scientist and engineer. He holds a Ph.D. from Columbia University in Cellular, Molecular, and Biomedical Studies specializing in Systems Biology. Nick has published in over 10 peer reviewed publications and over a decade of experience in the field of computational biology. He is a frequent participant and leader in bioinformatics hackathons and attends international conferences showcasing the state-of-the-art research and tools used to advance human health. Nick is currently a Quantitative Translational Scientist at Regeneron Pharmaceuticals.

  • R, Tidyverse, SQL, Bioconductor
    Software development and statistical & machine learning for bioinformatics data visualization and analysis
  • Python, SciKit-Learn, Pandas, NumPy
    Monte carlo simulation and prediction using regression- and tree-based machine learning models
  • Shiny, RMarkdown, Jupyter, Quarto
    Business intelligence, scientific dashboards, interactive reports, and website development
  • Bacholar of Science
    2010-2014: University of Rochester, New York, United States
  • Postbaccalaureate trainee
    2014-2016: National Human Genome Research Institute, United States
  • Cellular, Molecular, and Biomedical Studies Ph.D. Candidate
    2016-2021: Columbia University, New York, United States
  • System Biologist
    Biomarker prediction and discovery combining proteomics and clinical data to generate prognostic hypotheses and create models of biological mechanisms
  • Biomedical Informatician
    Biomedical informatics research leveraging clinical ontologies (RxNorm, MedDRA) and observational (Medical Records, Drug safety reports) data to advance pediatric drug safety
  • Cancer Bioinformatician
    Integrating epigenetic (RNA, DNA methylation) next generation sequencing data to investigate ovarian endometrial tumorigenesis

Our mission