Key Competencies
QuantMD has the following focused practice areas:
- Healthcare - EHR data, Medical Imaging
- Supply Chain Modeling
- Operations - Marketing / Sales
- Industrial Automation / Manufacturing
Chief Data Scientist
Chief Data Scientist, Prahlad G Menon, PhD, is an engineering professor and data scientist, with cross-industry experience leading and successfully executing on data-science projects that positively impact EBIT and form centerpieces of organizational success, including clinical trials research, predictive maintenance of medical equipment, development of data-driven solutions for derailment risk analytics for the railroads and statistical process control for steel-making, in the Greater Pittsburgh Area.
Dr. Menon was formerly a tenure track faculty of electrical & computer engineering at Carnegie Mellon University (until Aug. 2015) and subsequently with the biomedical engineering program at Duquesne University (until Aug. 2018). He is currently affiliated as an adjunct professor with Carnegie Mellon University, University of Pittsburgh and University of Texas at San Antonio. Dr. Menon has a successful history of teaching 10+ courses at the undergraduate and graduate level and over 100+ students at top global institutions.
Dr. Menon is well published in the scientific literature with 60+ peer reviewed publications in the general field of physics based computational modelling, machine learning, image processing and statistical modelling of shapes / appearance.
Dr. Menon was formerly a tenure track faculty of electrical & computer engineering at Carnegie Mellon University (until Aug. 2015) and subsequently with the biomedical engineering program at Duquesne University (until Aug. 2018). He is currently affiliated as an adjunct professor with Carnegie Mellon University, University of Pittsburgh and University of Texas at San Antonio. Dr. Menon has a successful history of teaching 10+ courses at the undergraduate and graduate level and over 100+ students at top global institutions.
Dr. Menon is well published in the scientific literature with 60+ peer reviewed publications in the general field of physics based computational modelling, machine learning, image processing and statistical modelling of shapes / appearance.