Principal Investigator

Dr. Bukhari is an Assistant Professor and Director of Healthcare Informatics at St. John's University, New York. He received his Ph.D. in Computer Science from the University of New Brunswick, Canada, and then went on to complete his postdoctoral fellowship at Yale School of Medicine, where he worked with Stanford University, Center of Expanded Data Annotation and Retrieval (CEDAR) to develop data submission pipelines to improve scientific experimental reproducibility. His current research efforts are concentrated on addressing several core problems in healthcare informatics and data science. He mainly focuses on devising techniques to semantically confederate heterogeneous biomedical data and develop Artificial Intelligence-based predictive models for clinical outcomes. These techniques also alleviate many data access-related challenges faced by healthcare providers. Dr. Bukhari is a senior IEEE member and a distinguished ACM speaker who serves as an editorial board member of multiple scientific journals. In September 2019, he was awarded the IEEE Technological Innovation Award. His research work has been published in top-tier journals and picked by various scientific blogs and international media.

Dr. Bukhari, Asst. Professor and Director Healthcare Informatics at St. John's University, New York

Who We Are

We are a team of Medical Informaticians, Artificial Intelligence Experts, Medical Professionals, and Software development professionals who are passionate about developing cutting-edge technologies to improve the healthcare experience.

What We Do

Leveraging thirteen-plus years of Medical/healthcare IT solution development expedience, We work directly with Healthcare professionals, Hospitals, and Private Equity groups, helping to solve complex healthcare industry problems.

Why We Do It

Each of us loves what we do and we feel that spirit helps translate into the quality of our work. Working with clients who love their work combines into a fun, wonderful partnership for everyone involved.

Technology Expertise

Terminology and Standards: SNOMED CT, RxNorm, LOINC, ICD, CPT, CDISC, HL7 (FHIR), NCDPD, IHTSDO, CDISC, and more

100%

Knowledge engineering: Ontologies, Linked Data, Visualization

100%

Artificial Intelligence: Expertise in Machine learning and Deep learning platforms

100%

Data integration: EHR, Lab and Research data, Clinical notes

100%

Programming Languages: Python, PHP, Java, Javascript, HTML5, Linux/Unix/Shell environments

99%

Natural language processing, Natural language generation, Hardware with integrated AI

100%

Databases: NoSQL and SQL e.g., Cassandra, Relational (MySQL, PostgreSQL, SQLite), Graph (Neo4J)

98%

Project Management

Team Commitment

Timely Delivery

Onsite Training