Naresh R Shanbhag

Professor, Electrical and Computer Engineering
Professor, Information Trust Institute
Professor, Coordinated Science Lab
Jack S. Kilby Professor, Electrical and Computer Engineering

Emailshanbhag@illinois.edu

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Energy efficiency Engineering & Materials Science

Decoding Engineering & Materials Science

Throughput Engineering & Materials Science

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Research Output 1988 2019

109 Article
100 Conference contribution
39 Conference article
19 Paper
11 More

Accumulation bit-width scaling for ultra-low precision training of deep networks

Sakr, C., Wang, N., Chen, C. Y., Choi, J., Agrawal, A., Shanbhag, N. R. & Gopalakrishnan, K., Jan 1 2019.

Research output: Contribution to conference › Paper

scaling

Optimal systems

Chemical activation

Hardware

floating

An energy-efficient classifier via boosted spin channel networks

Patil, A. D., Manipatruni, S., Nikonov, D., Young, I. A. & Shanbhag, N. R., Jan 1 2019, 2019 IEEE International Symposium on Circuits and Systems, ISCAS 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 8702648. (Proceedings - IEEE International Symposium on Circuits and Systems; vol. 2019-May).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Classifiers

Adaptive boosting

Learning algorithms

Throughput

Networks (circuits)

An Energy-Efficient Programmable Mixed-Signal Accelerator for Machine Learning Algorithms

Kang, M., Srivastava, P., Adve, V., Kim, N. S. & Shanbhag, N. R., Sep 1 2019, In : IEEE Micro. 39, 5, p. 64-72 9 p., 8768342.

Research output: Contribution to journal › Article

High level languages

Learning algorithms

Particle accelerators

Energy efficiency

Learning systems

An MRAM-based deep in-memory architecture for deep neural networks

Patil, A. D., Hua, H., Gonugondla, S., Kang, M. & Shanbhag, N. R., Jan 1 2019, 2019 IEEE International Symposium on Circuits and Systems, ISCAS 2019 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 8702206. (Proceedings - IEEE International Symposium on Circuits and Systems; vol. 2019-May).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Memory architecture

Networks (circuits)

Deep neural networks

Binodal, wireless epidermal electronic systems with in-sensor analytics for neonatal intensive care

Chung, H. U., Kim, B. H., Lee, J. Y., Lee, J., Xie, Z., Ibler, E. M., Lee, K. H., Banks, A., Jeong, J. Y., Kim, J., Ogle, C., Grande, D., Yu, Y., Jang, H., Assem, P., Ryu, D., Kwak, J. W., Namkoong, M., Park, J. B., Lee, Y. & 25 others, Kim, D. H., Ryu, A., Jeong, J., You, K., Ji, B., Liu, Z., Huo, Q., Feng, X., Deng, Y., Xu, Y., Jang, K. I., Kim, J., Zhang, Y., Ghaffari, R., Rand, C. M., Schau, M., Hamvas, A., Weese-Mayer, D. E., Huang, Y., Lee, S. M., Lee, C. H., Shanbhag, N. R., Paller, A. S., Xu, S. & Rogers, J. A., Jan 1 2019, In : Science. 363, 6430

Research output: Contribution to journal › Article

Open Access

Neonatal Intensive Care

Neonatal Intensive Care Units

Skin

Vital Signs

Diagnostic Imaging