Sadasivan Shankar
Biography: Sadasivan Shankar is Research Technology Manager of Microelectronics in SLAC National Laboratory, Adjunct Professor in Materials Science and Engineering in Stanford University . He was the first Margaret and Will Hearst Visiting Lecturer in Harvard University. He has co-instructed several graduate-level classes on Computational Materials Design, Extreme Computing for Real Applications, and Mitigating Toxicity by Materials Design. He is involved in research in the areas of materials, chemistry, multi-scale and non-equilibrium methods, and large-scale computational methods. Dr. Shankar earned his Ph.D. in Chemical Engineering and Materials Science from University of Minnesota, Minneapolis. He is a co-inventor in over twenty patent filings covering areas in new chemical reactor designs, semiconductor processes, bulk and nano materials, device structures, and algorithms. He is also a co-author in over hundred publications and presentations in measurements, multi-scale and multi-physics methods spanning from quantum scale to macroscopic scales, in the areas of chemical synthesis, plasma chemistry and processing, non-equilibrium electronic, ionic, and atomic transport, energy efficiency of information processing, and machine learning methods for bridging across scales, and estimating complex materials properties and in process control. Dr. Shankar is a co-founder of Material Alchemy, a “last mile” translational and independent venture in materials design for accelerating materials discovery to adoption, with environmental sustainability as a key goal.
Field(s) of Research: Chemical Reaction Networks, Computer Science Engineering to Address Energy Costs, General Non-equilibrium Statistical Physics, Logically Reversible Computing, Naturally Occurring Biological Computation
Related links
- Stanford Web Page
- Harvard Bio Page
- Carnot’s Engine, Bernoulli’s Pump, and Turing’s Machine - Some clues to realization of ideal computing
- Computation from Devices to System Level Thermodynamics
- Die Stacking (3D) Microarchitecture
- Non-equilibrium dynamics of electrons in weakly ionized plasmas from Boltzmann Equation
- CAN WE LEARN (AGAIN) FROM NEUROSCIENCE ABOUT HOW TO DO COMPUTING?
- Maxwell’s Demon, Schrodinger’s Cat, and Broca’s Brain: Gate keepers to the Future of Computing
- APS March Meeting 2021: Use of Carnot’s Engine and Bernoulli’s Pump to identify efficiency of information processing for computing beyond Moore's Law
- Physical Bioenergetics
- Lessons from Nature for Computing
- Energy as a design variable in computing
- Untangling Feynman's puzzle: Examining the future of computing
- Q&A: How to make computing more sustainable
- Design for Sustainability: Energy Efficiency and Computing
- Energy Estimates Across Layers of Computing
- Neuromorphic intermediate representation: A unified instruction set for interoperable brain-inspired computing