Prahlad G. Menon, Ph.D.

Engineering professor and AI consultant / 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 predictive maintenance of industrial assets, data-driven solutions for derailment risk analytics for the railroads, statistical process control for steel-making, computer vision for retail, etc.Highlights:

• Delivered over $2.5M in digital transformation and data science projects on the Google Cloud, leveraging AI and IoT for clients in healthcare, retail, finance and manufacturing (including Wawa, Nurse.com, The Brooklyn Hospital and several others, in North America, Africa and South-east Asia), with 100+ indirect reports across three time-zones, as a chief of practice / consultant

• Winner of the Global Digital Innovation Award from Bayer for innovations relating to Deep Learning applied to medical image diagnostics

• Developed the first breath based Covid-19 test applying machine learning to mass spectrometry data acquired from breath samples (published on The Lancet)

• History of successful execution on data science projects, ranging from financial forecasting, portfolio analytics, algorithmic trading, procurement spend analytics to predictive maintenance and machine vision based statistical process control

• Experienced in data science applied to drug discovery, biostatistical analysis for clinical trials data, patient-specific medical image analytics for diagnostics, cardiovascular surgical planning as well as developing and validating technology for image guided surgery

• Experience with Big Data Analytics frameworks (including Google Cloud, AWS, Microsoft Azure, Oracle big data cloud, IBM Bluemix), text-analytics using natural language processing, generating APIs for data models and consuming public APIs

• Expertise in algorithmic forecasting of time-series data, including automatic signal classification for real-time analytics from IoT sensors• Former tenure track faculty of electrical & computer engineering at Carnegie Mellon University

• 100+ peer reviewed publications in the general field of physics based computational modeling, AI / machine learning, image processing and statistical modeling of shapes / appearance

• PhD + Post-doctoral training in physics-based computational modeling and bioinformatics + MS in mechanical engineering from Carnegie Mellon University• Expert programmer in R, Python, Matlab, SAS with clinical trials research experience