Mohammad Adibuzzaman

Mohammad Adibuzzaman

Co-Director, Informatics, @OCTRI, OHSU

Posts by Collection

portfolio

publications

talks

Closing the Data Loop: An Integrated Open Access Analysis Platform for the MIMIC Database

Published:

We describe a new model for collaborative access, exploration, and analyses of the Medical Information Mart for Intensive Care - III (MIMIC III) database for translational clinical research. The proposed model addresses the significant disconnect between data collection at the point of care and translational clinical research. It addresses problems of data integration, preprocessing, normalization, analyses (along with associated compute back-end), and visualization. The proposed platform is general, and can be easily adapted to other databases. The pre-packaged analyses toolkit is easily extensible, and allows for multi-language support. The platform can be easily federated, mirrored at other locations, and supports a RESTful API for service composition and scaling.

An Open-access High Performance Computing System for Developing Research Applications (Apps)

Published:

Despite the promise of big data, little evidence has been generated for clinical practice with data driven systems. A new model for collaborative access, exploration, and analyses of integrated clinical data will be presented with a standard database, Medical Information Mart for Intensive Care - III (MIMIC III), for translational clinical research. The proposed model addresses the significant disconnect between data collection at the point of care and translational clinical research. It addresses problems of data integration, pre-processing, normalization, analyses (along with associated compute back-end), and visualization. The pre-packaged analyses toolkit is easily extensible, and allows for multi-language support. The platform can be easily federated, mirrored at other locations, and supports a RESTful API for service composition and scaling.

LATICE: Framework for Longitudinal Analysis of Time-Course Data from Patient Generated Health Data

Published:


We aim to develop critical and enabling cyberinfrastructure for integrated analyses of longitudinal and time-series data from the multitude of sensors in common commercial wearables, in conjunction with the corresponding patient pharmacological and electronic health records EHRs). Effective analyses of this rich source of data has the potential to significantly enhance long-term individual well-being, reduce cost of healthcare, improve our understanding of pathology, associated sensor markers and prognoses, characterize the efficacy of drugs and identify adverse effects and interactions, and to enable a broad class of new data-driven studies. Architecting the proposed system poses significant challenges stemming from the heterogeneity of sensor devices and associated quality of data, diversity of populations and underlying pathologies, disparate drug regimes and responses, and complexity of the underlying analytics problems.

teaching

Lecturer

Undergraduate course, University of Asia Pacific, Department of Electrical Engineering, 2009

I taught Microprocessors and for junior students and also was the instructor for the lab testings for the course.

Teaching Assistant

Undergraduate course, Marquette University, Department of Mathemtatics, Statistics, and Computer Science, 2010

I was a teaching assistant for Calculus I, II and III for eight semesters between 2010 and 2015 at Marquette University.

Primary Instructor

Undergraduate course, Marquette University, Department of Mathemtatics, Statistics, and Computer Science, 2011

I taught Data Structures to Sophomores. Topics included, data structures such as trees, heaps, hash functions, and search algorithms.

Mentoring

Mentoring, Purdue University, 2020

  • Gradute Student
    • Yonghan Jung (Ph.D. Candidate (Computer Science), Advisor Elias Barienboim)
    • Fatemeh Rouzbeh (Ph.D. Candidate (Computer Science), Advisor Ananth Grama)
    • Mobasshir Arshed Naved (Ph.D. Candidate (Industrial Engineering), Advisor Paul Griffin)
    • Chih-Hao Fang (Ph.D. Candidate (Computer Science), Advisor Ananth Grama)
    • Riddhiman Adib (Ph.D. Candidate (Computer Science, Marquette University), Advisor Sheikh Iqbal Ahamed)
    • Brett Meyers (Ph.D. Candidate (Mechanical Engineering), Advisor Pavlos Vlachos)
    • Amber Johnson (Ph.D. (Computer Science), Advisor Bharat Bhargava)
    • Yao Chen (Ph.D. Candidate (Statistics), Advisor Xiao Wang)
  • Undergraduate Student
    • Adam Patrick Goodman (ECE, Discovery Park Undergraduate Research Internship Program (DURI))
    • Brett Collar (BME, Discovery Park Undergraduate Research Internship Program (DURI))
    • Navya Annam (CS, Independent Study)
    • Yiyan Zhou (CS, Independent Study)