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Sabbir M. Rashid

Sabbir Rashid
Postdoctoral Research Associate
Ph.D. 2023
Employing Ensemble Reasoning to Support Clinical Decision-Making
Advisor: Deborah L. McGuinness

Email: rashis3@rpi.edu

Sabbir M. Rashid is a Postdoctoral Research Associate at the RPI Tetherless World Constellation. Dr. Rashid received his Ph.D. from Rensselaer Polytechnic Institute in 2023, working with Professor Deborah McGuinness on research related to data annotation and harmonization, ontology engineering, knowledge representation, and various forms of reasoning. His dissertation research involved the application of deductive and abductive inference techniques over linked health data, such as in the context of chronic diseases like diabetes. Before attending RPI, Sabbir completed a double major at Worcester Polytechnic Institute, where he received B.S. degrees in both Physics and Electrical & Computer Engineering. Much of his graduate studies at RPI involved research related to the semantic annotation and transformation of data using Semantic Data Dictionaries.

Thesis defense: 
https://tw.rpi.edu/media/thesis-defense-employing-ensemble-reasoning-support-clinical-decision-making-sabbir-rashid

Thesis document: 
https://www.proquest.com/openview/da085fc6138578a8929d275089fade2b/

Google Scholar: 
https://scholar.google.com/citations?user=F3pzzo4AAAAJ&hl=en 

Talks: 
https://tw.rpi.edu/media/twed-talk-sabbir-rashid-employing-ensemble-reasoning-support-clinical-decision-making-21-mar 

https://tw.rpi.edu/media/twed-talk-sabbir-rashid-creating-trading-card-game-using-knowledge-graphs-24-apr-2024 

https://www.youtube.com/watch?v=dUum3R56xnY 

https://www.youtube.com/watch?v=KYvMXu60FjY 

https://www.youtube.com/watch?v=x54GC9XRHt0 


Projects as Research Assistant

Semantic Extract, Transform, and Load-er (SETLr) is a flexible, scalable tool for providing semantic interpretations to tabular, XML, and JSON-based data from local or web files.

HADatAc (Human-Aware Data Acquisition framework) is an open-source infrastructure that enables combined acquisitions of data and metadata in a way that metadata is properly and logically connected to data.

The MaterialsMine Team brings together expertise across five research institutions in the fields of mechanics, materials, design, manufacturing, data science, and computer science to build and develop an open-source, user-friendly materials data resource guided by FAIR principles, with current mo