Rajesh K. Gupta Department of Computer Science and Engineering University of California, San Diego mHeath Summit, NIH 2014 A Perspective on Challenges of mHealth Academics

A Story An archetype of a discipline, not the only one. Embedded. CPS. Quantum Computing, Molecular Computing, Cybernetics… An archetype of a discipline, not the only one. Embedded. CPS. Quantum Computing, Molecular Computing, Cybernetics…

That brings us to today 1.Effect of emerging knowledge on academic institutions –Slow moving institutions…and not just a corporation of ideas 2.Growing intersection with life sciences –A challenge of millennials era: new fangled knowledge domains, emergent MD/PhDs. –A whole host of new areas: cBIO, qBIO, mHealth, Systems 3.Whence mHealth? 3

Physical & Life Sciences Computing and Data are truly at the intersection of physical and life sciences –From knowns of physics to unknowns of life Semi without Maxwell’s equations, Fluid dynamics w/o Navier-Stokes or Chemistry w/o periodic table… –Known methods of CS fail us –Emergent domain of “Data Sciences” Our physical realities find expression and reproduction in virtual through data –Data quality seen very differently. 4

Near Home: Computational to Quantitative Biology 5 Programs are run by people in specific departments where they are evaluated for their success or not by their departmental colleagues. In the meantime: Neurosciences at UCSD have thrived. In the meantime: Neurosciences at UCSD have thrived.

Computational versus Quantitative cBIO –Computation applied to genomics, omics… –Really Systems Biology and Bioinformatics –“Can you teach my students all Biology in a course or two?” qBIO –Predictive modeling of cellular regulatory systems –Really Dynamical Systems –“Can you teach my students all Computer Science in a course of two?” 6

mHealth: From excitement of discovery to academic discipline Formation of a core community of researchers and practitioners Core concepts, skills that are agreed by this community to be essential –De facto will not work Enable strong peer evaluation system –To help academic evaluation process to succeed. 7

DATA QUALITY IS CRITICAL Data can bridge the gap between physical and health sciences, but 8

Data and Culture 9 Power output (kcal/min) = VO2 / ( fraction of VO2 by fat*100 kcal/O2 mole + fraction of VO2 by carb*120 kcal/O2 mole) VO2max = mL O2/kg/min => 3.3 L O2/min O2: L/mole mole/min Power output (kcal/min) = VO2 / ( fraction of VO2 by fat*100 kcal/O2 mole + fraction of VO2 by carb*120 kcal/O2 mole) VO2max = mL O2/kg/min => 3.3 L O2/min O2: L/mole mole/min

10

11 5 cyclists, 2 hours