Student Working Group Administration Committee member

Develop and execute a comprehensive strategy & roadmap for clinical data informatics enabling market leading Oncology specific EMR research and development as well healthcare operations. Collaborate with cross-functional stakeholders including product, engineering, design and clinical.Oversee the management, and enhancement of informatics applications used in clinical development, e.g. Terminology management system (TMS), ensuring their optimal performance, reliability, and compliance with industry regulations.Perform structured evaluations and selections of technology solutions and manage relationships with external vendors, including contract negotiations, performance evaluations.Provide leadership to the Health Informatics team, fostering a culture of innovation, collaboration, and continuous improvement. Set clear goals, provide guidance, and support professional development opportunities for team members.Ensure applications used by the team and their usage, comply with regulatory requirements, data privacy regulations e.g. HIPAA, and internal policies. Identify and mitigate potential risks associated with application usage and data management.Stay abreast of industry trends, emerging technologies, and best practices related to data, informatics applications and digital health solutions in EMR development to ensure our team remains at the forefront of innovation.

Sanford Imagenetics was a comprehensive program that aimed to fully integrate patients' genetics results with their clinical data, creating a first-of its-kind model for exceptionally high-quality and innovative primary care for adults. Developed data model for integrated genomic-phenomic data, managed a team of informaticists, developed digital phenotyping algorithms. Established a secure cloud based OHDSI tools environment and converted EHR data to OMOP Common Data Model. This Real-world data resource was utilized to study novel descriptive and predictive model. This RWD informatics platform that supported both clinical (phenomic) and genomic data, allowed us to study polygenic risk scores in domains like cancer and cardiovascular diseases.

NIH funded researcher, working on projects that bring together real world clinical and genomic datasets. Primary focus of research was developing and evaluating polygenic risk scores and phenome-wide association studies. These require extraction of EMR data from research data warehouses, cleaning and feature extracting, developing various statistical (e.g. chi-square, linear regression, survival analysis) and machine learning models (e.g. tree based models like random forest to accommodate multimodal data). Tools used: Jupyter notebooks, Python, Sci-Kit, Pandas, R, Rstudio/Posit. Academic HPC environment and AWS cloud environment.

Each NIH Institute and Center (IC) has appointed a Genomic Program Administrator (GPA) to serve as a single point of contact for GDS Policy implementation within the IC. The GPAs serve as the senior staff leads and point of information for their ICs for investigators, the GDS governance committees, their IC's Data Access Committee, and for the National Center for Biotechnology Information (NCBI). The primary role for GPAs is to coordinate implementation of the NIH GDS policy and manage study registration and submission of human genomic data within their ICs.

Genomic Program Administrator (Intramural) at  NIDCR/NIH, Associate Investigator, Staff Scientist, Bioinformatics analyses of mouse and human next generation sequence data. Mouse SNP chip data analysis, mouse transcriptome sequence data analysis. Natural Language Processing and Ontology research. Supervised development of a metadata-based workflow aware open source research informatics platform. Supervised clinical and research data management efforts including REDCap servers, mobile applications, and a data manager. Managed two contracts for software development and Clinical Data Management. Implemented best practices in data management to uphold data integrity.Represented NIDCR at the Common Data Elements Task Force.Co-supervised clinical research fellows, post-doctoral trainees, and pre-doctoral students.

Bioinformatics and genomics analyses of next generation sequencing data in the Undiagnosed Diseases Program at the National Institutes of Health. I developed a tool (VAR-MD) that is capable of prioritizing exome/genome sequencing data in rare diseases in a family context. As a medical doctor, I evaluate each high ranking variant with the help of scientific literature and the patient's clinical data to create genomic medicine reports that lead to diagnoses.

I was admitted to this program through the National Medical Speciality Admission test (TUS -ranked 500th out of more than 15000 MDs who took the test). I was a resident in the department of obstetrics and gynecology. I had to leave this program to accept a fellowship offered by the National Human Genome Research Institute, National Institutes of Health, Bethesda, MD.

Secretary General

I work at the Department of Medical Education and Informatics. My responsibility is to support the faculty of medicine with necessary IT processes. It is sort of CIO job, but a little different. My research is in clinical informatics and IS management.

Developed and taught "Introduction to Medical Informatics" as an on-line full credit course as part of the Masters in Education degree program.

I analyzed Hospital Information System platform of the company and advised on better use of controlled terminologies like ICD-10, SNOMED-CT , LOINC among orther heath care coding and classification standards.