Mikhail Smelyanskiy
- Hardware and Architecture top 0.5%
- Computer Networks and Communications top 1%
- Artificial Intelligence top 5%
- Electrical and Electronic Engineering top 10%
- Computer Vision and Pattern Recognition top 5%
- Co-authors
- Pradeep DubeyJatin ChhuganiDaehyun KimAnthony D. NguyenChangkyu KimNadathur SatishVictor W. LeeMichael Deisher
- Topics
- Parallel Computing and Optimization Techniques (37 papers)Advanced Data Storage Technologies (24 papers)Distributed and Parallel Computing Systems (14 papers)
- 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
- Computer Networks and Communications 1.1k
- Artificial Intelligence 381
- Electrical and Electronic Engineering 340
- 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 of co-authors of Mikhail Smelyanskiy
This figure shows the co-authorship network connecting the top 25 collaborators of Mikhail Smelyanskiy. A scholar is included among the top collaborators of Mikhail Smelyanskiy based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Mikhail Smelyanskiy. Mikhail Smelyanskiy is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 145 | |
| 3 | Distributed Hessian-Free Optimization for Deep Neural Network. | 2 |
| 4 | 51 | |
| 5 | 13 | |
| 6 | 28 | |
| 7 | Opportunities for Parallelism in Matrix Multiplication | 1 |
| 8 | 42 | |
| 9 | 18 | |
| 10 | Closing the Ninja Performance Gap through Traditional Programming and Compiler Technology | 13 |
| 11 | 9 | |
| 12 | 17 | |
| 13 | 1 | |
| 14 | 9 | |
| 15 | 62 | |
| 16 | 20 | |
| 17 | 7 | |
| 18 | 32 | |
| 19 | 13 | |
| 20 | 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) and Distributed and Parallel Computing Systems (14 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.