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Daniel Sauceda (Assoc)

Postdoctoral Scientist

About Me:

Howdy,
My research history was focused on computational materials science in the High-entropy Alloy and MAX phase alloy space at Texas A&M University. To conduct this work effectively, I understood the importance of establishing efficiently workflows and data-management tools.  This has led to my current research interest of designing and establishing infrastructure for automated scientific workflows. Then using these workflows better leverage Bayesian statistics and ai-driven models for decision-making applications.

 

Current Project(s): 


Rapid Drug Analysis and Research (RaDAR)

My current work is focused on enhancing the automated and batch processing capabilities of data produced from the RaDAR Lab. The RaDAR Lab is a pioneer pilot program for addressing the opioid epidemic through rapid mass spectra forensics analysis. Recognizing that the there is a growing rise in street-drug related mortality [1], the classification and processing of each particular item is far out pacing traditional forensics labs. By using DART-MS rather that GC-MS, measurements of samples are shortened drastically to minutes rather than hours. By partnering with third-party organizations, such as hospitals and law enforcement, samples are sent in, analyzed, and reported faster than in-house forensics. By developing shareable softwares, frameworks, and infrastructures, our goal is to make deployable labs that interconnect with their respective datasets for the purposes of datamining discovery.

Rapid Drug Analysis and Research (RaDAR): Providing Near Real-Time Insight into the Illicit Drug Landscape | NIST



 

Graduate Publications:

 

Created September 5, 2024, Updated January 27, 2025