Rd Supekar Electronics Pdf 26
In the last 15 years, the W3C, World Wide Web Consortium, has released dozens of standards for the web and its associated technologies. These standards have improved the way everyone accesses and shares information. In the process, the W3C has also worked with nearly 50 standards and draft.. (x, property, ). Serban R, Supekar K: Machine Learning and Data Mining Techniques to Understand the Teaching and Learning Processes in Medical Education (TAMMEDe): The Challenges and Opportunities. In: Pierola M, Rizzo RA, Döring JD. (Eds.), The Future of Medical Education: Perspectives on Technology. Springer: Cham, pp. 38-49, 2017.
09-03-2019, Supekar and his group developed a laser system for high resolution, low-invasiveness, and noncontact invasive measurements of the SiO2 gradient for the in-depth understanding of the permeability of the blood brain barrier. The scalable measurement of the SiO2 gradient in the whole brain promises to revolutionize neuroscience for probing the biological roles of the microenvironmental factors.
S R Supekar, Ph.D., Optical Sciences Department, Kavli Institute for Nanoscience, Delft University of Technology, Delft, The Netherlands. F. M. H. van Herck, M. L. Tran, H. J. Van Grunsven, J. Abboud, R. Toth and J.L. Aarden, Optical Sciences Department, Kavli Institute for Nanoscience, Delft University of Technology, Delft, The Netherlands.
S R Supekar, Kavli Institute for Nanoscience, Kavli Institute for Nanoscience, Delft University of Technology, Delft, The Netherlands. The laboratory has been working on optics and photonics, nano-photonic materials, nano-optics, biomedical optics, imaging, and signal processing systems for use in diverse technological and scientific fields.
the supekar group also contributes to several other projects including the development of a mobile “social medecine” system for the somanetworks for rural care practitioners, a wireless multi-sensor system for building monitoring, and a wireless ambient information system for mobile healthcare.
k. supekar is a graduate of the university of illinois at urbana-champaign, where he earned a b.s. in electrical engineering and computer science (2001), and a ph.d. in electrical engineering (2006). he is a former postdoctoral researcher at the national institute of standards and technology, and a former research fellow at the institute for digital signal processing, university of california at berkeley. he is now an assistant professor of biomedical engineering at the university of illinois at urbana-champaign. his research interests include high-resolution optical microscopy, data science, signal processing and machine learning.
shi b, supekar k, tamura s, garber am*. resting state fmri analysis of the default mode network in healthy adults: comparison of seed-based and network-based methods (2007),annual american medical informatics association symposium, 2007. pp. 613-616.pmid:17308950; pmcid: pmc1590351. 
supekar k, gopinath d, morgan a, das a, garber am*, (2009) super-resolution microscopy with a sheet of fluorescent nanodiamonds for 3d bio-imaging.journal of micro/nano electronics and technology, vol. 1, no. 1, pp. 20-24, 2009. pmid 19048552. 
supekar has also developed a platform for the automated design of neural networks for image recognition in the gopinath group. he recently worked on the automatic detection of melanoma cells in imaging of skin biopsies.