Mikhail Smelyanskiy
- Hardware and Architecture top 0.5%
- Parallel Computing and Optimization Techniques 37
- Embedded Systems Design Techniques 4
- Computational Mathematics top 5%
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- Advanced Data Storage Technologies 24
- Distributed and Parallel Computing Systems 14
- Interconnection Networks and Systems 10
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- Stochastic Gradient Optimization Techniques 7
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- Sparse and Compressive Sensing Techniques 5
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- Cloud Computing and Resource Management 5
- Co-authors
- Pradeep DubeyJatin ChhuganiDaehyun KimAnthony D. NguyenChangkyu KimNadathur SatishVictor W. LeeMichael Deisher
- Journals
- The Journal of Chemical Physics (1 paper)Proceedings of the IEEE (1 paper)Communications of the ACM (1 paper)
- Partner nations
- United StatesUnited KingdomIndia
In The Last Decade
Mikhail Smelyanskiy
56 papers receiving 2.2k citations
Hit Papers
Peers
Comparison fields: 5 of 100
- Hardware and Architecture 1.3k
- Computational Mathematics 37
- Computer Networks and Communications 1.1k
- Computer Graphics and Computer-Aided Design 74
- Computer Vision and Pattern Recognition 337
Countries citing papers authored by Mikhail Smelyanskiy
This map shows the geographic impact of Mikhail Smelyanskiy'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 Mikhail Smelyanskiy with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mikhail Smelyanskiy more than expected).
Fields of papers citing papers by Mikhail Smelyanskiy
This network shows the impact of papers produced by Mikhail Smelyanskiy. 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 Mikhail Smelyanskiy. The network helps show where Mikhail Smelyanskiy may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Mikhail Smelyanskiy, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2021 | 5 | |
| 2 | 2020 | 145 | |
| 3 | Distributed Hessian-Free Optimization for Deep Neural Network. | 2017 | 2 |
| 4 | 2016 | 51 | |
| 5 | 2015 | 13 | |
| 6 | 2015 | 28 | |
| 7 | Opportunities for Parallelism in Matrix Multiplication | 2014 | 1 |
| 8 | 2012 | 42 | |
| 9 | 2012 | 18 | |
| 10 | Closing the Ninja Performance Gap through Traditional Programming and Compiler Technology | 2012 | 13 |
| 11 | 2012 | 9 | |
| 12 | 2012 | 17 | |
| 13 | 2011 | 1 | |
| 14 | 2010 | 9 | |
| 15 | 2009 | 62 | |
| 16 | 2008 | 20 | |
| 17 | 2007 | 7 | |
| 18 | 2002 | 32 | |
| 19 | 2001 | 13 | |
| 20 | 2000 | 9 |
About Mikhail Smelyanskiy
Mikhail Smelyanskiy is a scholar working on Hardware and Architecture, Computer Networks and Communications and Computational Mechanics, having authored 56 papers that have together received 2.3k indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (37 papers), Advanced Data Storage Technologies (24 papers), Distributed and Parallel Computing Systems (14 papers), Interconnection Networks and Systems (10 papers), Stochastic Gradient Optimization Techniques (7 papers), Sparse and Compressive Sensing Techniques (5 papers), Cloud Computing and Resource Management (5 papers) and Embedded Systems Design Techniques (4 papers). The work is most often cited by research in Hardware and Architecture (1.3k citations), Computational Mathematics (37 citations) and Computer Networks and Communications (1.1k citations). Mikhail Smelyanskiy has collaborated with scholars based in United States, United Kingdom and India. Frequent co-authors include Pradeep Dubey, Jatin Chhugani, Daehyun Kim, Anthony D. Nguyen, Changkyu Kim, Nadathur Satish, Victor W. Lee, Michael Deisher, Edmond Chow and Ronak Singhal. Their work appears in journals such as The Journal of Chemical Physics, Proceedings of the IEEE and Communications of the ACM.
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.