Sumedh R. Risbud

763 citations
13 papers · 445 indexed · 1 hit paper · h-index 7

Impact in

Papers in

Sumedh R. Risbud

12 papers receiving 441 citations

Hit Papers

Advancing Neuromorphic Computing With Loihi: A Survey of Results and Outlook 2021 · 332 citations
3322021202620222024100200300

Peers

Sumedh R. Risbud
Comparison fields: 5 of 64
  • Cognitive Neuroscience 132
  • Electrical and Electronic Engineering 336
  • Artificial Intelligence 159
  • Cellular and Molecular Neuroscience 77
  • Condensed Matter Physics 14
Replace Abhishek Khanna with:
Abhishek Khanna United States
Md Sakib Hasan United States
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Min-Woo Kwon South Korea
Guanrui Wang China
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Sumedh R. Risbud relative to Abhishek Khanna United States Abhishek Khanna's profile →
Citations per field
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Citations per year

Countries citing papers authored by Sumedh R. Risbud

Since Specialization
Citations

This map shows the geographic impact of Sumedh R. Risbud's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Sumedh R. Risbud with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sumedh R. Risbud more than expected).

Fields of papers citing papers by Sumedh R. Risbud

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sumedh R. Risbud. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Sumedh R. Risbud. The network helps show where Sumedh R. Risbud may publish in the future.

Co-authorship network

The 24 scholars most cited alongside Sumedh R. Risbud, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Sumedh R. Risbud Line = papers co-authored together Sumedh R. Risbud links everyone, so they are left out of the graph.

All Works

13 of 13 papers shown
#Work
1 20240
2 20244
3 20241
4 20238
5 20236
6 202233
7 20223
8
Advancing Neuromorphic Computing With Loihi: A Survey of Results and Outlook
Hit paper breakdown →
2021332
9 201514
10 201419
11 20148
12 20135
13 201112

About Sumedh R. Risbud

Sumedh R. Risbud is a scholar working on Physical and Theoretical Chemistry, Physiology, Artificial Intelligence, Electrical and Electronic Engineering and Cellular and Molecular Neuroscience, having authored 13 papers that have together received 445 indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (8 papers), Ferroelectric and Negative Capacitance Devices (5 papers), Neural Networks and Reservoir Computing (4 papers), Microfluidic and Bio-sensing Technologies (4 papers), Microfluidic and Capillary Electrophoresis Applications (3 papers), Electrostatics and Colloid Interactions (2 papers), Nanopore and Nanochannel Transport Studies (2 papers) and Modular Robots and Swarm Intelligence (1 paper). The work is most often cited by research in Cognitive Neuroscience (132 citations), Electrical and Electronic Engineering (336 citations), Artificial Intelligence (159 citations), Cellular and Molecular Neuroscience (77 citations) and Condensed Matter Physics (14 citations). Sumedh R. Risbud has collaborated with scholars based in United States, India and Germany. Frequent co-authors include G. A. Fonseca Guerra, Prasad Joshi, Mike Davies, Garrick Orchard, Yulia Sandamirskaya, Andreas Wild, Germán Drazer, James W. Swan, Maryam Parsa and Joëlle Fréchette. Their work appears in journals such as Applied Physics Letters, Soft Matter, Proceedings of the IEEE, IEEE Robotics & Automation Magazine and Microfluidics and Nanofluidics.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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