Digital Twin Meets Digital Cousin: From Paradox to Paradoxical Paradigm?
Shoumen Palit Austin Datta
MIT Auto-ID Labs, and MDPnP Lab and Cybersecurity Program, Massachusetts General Hospital, Harvard Medical School
United States
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Brief Bio
Dr Shoumen Palit Austin Datta is a Senior Member of the MIT Auto-ID Labs, Research Affiliate at the Department of Mechanical Engineering, Massachusetts Institute of Technology (MIT) (http://autoid.mit.edu/people-2) and Senior Scientist, Medical Device Interoperability Lab and Cybersecurity Program, Department of Anesthesiology, Massachusetts General Hospital, Harvard Medical School http://mdpnp.mgh.harvard.edu. He is also affiliated with Purdue University (Sensors for Humans) and the University of Florida (Agricultural & Biological Engineering). He is the Co-Founder & former Executive/ Research Director of the MIT Forum for Supply Chain Innovation (2001-2010) at the MIT School of Engineering. Former Member of the MIT Auto ID Center (1999-2003), MIT Data Center (2004-2006) & MIT Energy Initiative (2008-2009). As a Research Scientist in the Engineering Systems Division, MIT School of Engineering, he explored technology innovation, RFID, IoT, digital supply chain, data, analytics and decision systems. He taught & teaches Supply Chain, Strategy and Management at the MIT Sloan School of Management, Chalmers University (Sweden), ESSEC (France), KEDGE (France), Cambridge University (School of Engineering) and Harvard Medical School (Molecular Medicine, Biochemistry and Metabolism for first year MD students). He has offered MBA & executive education courses at MIT and other institutions in US, EU and APAC. He was the founding Senior Vice President for the Industrial Internet Consortium (IIC). He is interested in healthcare, digital economy and technology innovation for science as a service to society. The latter includes IoT as a design metaphor and the value of ubiquitous connectivity to catalyze economic growth and access to global public goods (FEWSH - food, energy, water, sanitation, healthcare). His interests include additive manufacturing, robotics, nano-bio sensor engineering systems. He has authored books, papers, articles related to evolution of IoT and the industrial internet (2003), intelligent software agents (2001), predictive analytics, supply chain management, sensors in public health (SARS-CoV-2), healthcare platforms, energy, digital transformation. He has served/serves as an advisor for start-ups, corporations and governments including US Dept of Defense, US Dept of Commerce, United Nations (UNDP), World Customs Organization (WCO), President’s Science and Technology Advisory Group (PSTAG) for the President of Taiwan (ROC), TEKES (Government of Finland), etc. He earned his BSc (Biochemistry, Physiology, Physics, Chemistry) from the Presidency College, University of Calcutta. He attended University of Pittsburgh & earned his PhD from Rutgers University School of Medicine in collaboration with Dept of Molecular Biology at Princeton University. He was briefly associated (tumor virus research) with Paris VI Université Pierre-et-Marie-Curie and Institut du Cancer et d'Immunogénétique, Villejuif (ICIG, Hôpital Paul Brousse). He was a Research Fellow in Medicine (Thyroid and Neuro-Endocrine Labs, Molecular Oncology) at MGH (Massachusetts General Hospital) and Instructor in Medicine at Harvard Medical School (HMS). He was a Research Associate at the Whitehead Institute at MIT and a founding member of the MIT Human Genome Project. He was a Research Scientist in Molecular Parasitology at University of California UCSF School of Medicine, San Francisco, California. Dr Datta has served the public sector to improve public education and technology as Special Assistant to the Mayor of the City and County of San Francisco, California; Science Education Partnership at UCSF School of Medicine; Berkeley Pledge initiative at the University of California, Berkeley and Chair of the National Task Force on Education, Economy, Workforce and Technology sponsored by Information Technology Association of America (ITAA), Dept of Commerce, US Dept of Labor & White House Council of Economic Advisers (Clinton). Currently he is an advisor to NIH funded research related to CoVID-19.
Abstract
Directly or indirectly, knowingly or unknowingly, in astronomical events or in infinitesimal instances, almost all tools, technologies and techniques (e.g., statistical, operations research [OR], mathematical) converge to catalyze our need to be data-informed, to make sense of data, before the value of the data perishes, and extract actionable information (e.g., process optimization using OR). At the core of almost any system with a popular “buzz” (digital twins, internet of things, cyberphysical systems, cloud, machine learning, smart cities, “big data”, “DL”, “AI”, “Industry X.O”) we commence with data to extract meaningful information of value. The semantics of “meaning” must be rooted in causal context as well as metrics and measurements. Value is inextricably related to “performance” depending on the context and actions (feed-back/feed-forward) which could rapidly become a highly complex decision process (e.g., explosion of state space when synthesizing/analyzing data from percepts, environment, actuators, and sensors, referred to as PEAS and is the superset of the OODA loop which is the cycle observe-orient-decide-act). The underlying glue that permeates the fabric of continuum between meaning and value is causality. Almost every “thing” (made of atoms) or processes or systems we dissect, deconstruct and reconstruct, is made significant when associated with data (bits). The continuum of meaning and value is in dynamic interaction with the continuum between atoms to bits. The key elements of this multi-string, multi-dimensional continuum are connectivity, data, analytics and context (ACDC). In this talk, we will discuss examples of this “electricity” which powers the engines of science, decision science, OR and most data-informed systems across a broad and diverse spectrum of verticals and applications.