Igor Ganichev
Impact in
-
- Software-Defined Networks and 5G
- Caching and Content Delivery
- Network Traffic and Congestion Control
- Network Security and Intrusion Detection
- Peer-to-Peer Network Technologies
- Opportunistic and Delay-Tolerant Networks
- Hardware and Architecture top 10%
Papers in
-
- Software-Defined Networks and 5G 3
- Network Traffic and Congestion Control 3
- Software System Performance and Reliability 2
- Opportunistic and Delay-Tolerant Networks 1
-
- Network Packet Processing and Optimization 3
- Co-authors
- Scott Shenker (6 shared papers)P. Brighten Godfrey (4 shared papers)Ion Stoica (2 shared papers)Bin Dai (1 shared paper)Nick McKeown (3 shared papers)Hari Balakrishnan (1 shared paper)Somaya Arianfar (1 shared paper)Jennifer Rexford (1 shared paper)
- Partner nations
- United StatesFinlandChina
In The Last Decade
Igor Ganichev
7 papers receiving 332 citations
Peers
Comparison fields: 5 of 23
- Computer Networks and Communications 340
- Hardware and Architecture 32
- Artificial Intelligence 86
- Electrical and Electronic Engineering 85
- Information Systems 28
Countries citing papers authored by Igor Ganichev
This map shows the geographic impact of Igor Ganichev'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 Igor Ganichev with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Igor Ganichev more than expected).
Fields of papers citing papers by Igor Ganichev
This network shows the impact of papers produced by Igor Ganichev. 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 Igor Ganichev. The network helps show where Igor Ganichev may publish in the future.
Co-authors
The 25 scholars most cited alongside Igor Ganichev, 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 | 2009 | 175 | |
| 2 | 2011 | 59 | |
| 3 | 2009 | 55 | |
| 4 | 2010 | 34 | |
| 5 | 2010 | 18 | |
| 6 | 2010 | 6 | |
| 7 | 2019 | 4 | |
| 8 | TensorFlow Eager: A Multi-Stage, Python-Embedded DSL for Machine Learning | 2019 | 1 |
About Igor Ganichev
Igor Ganichev is a scholar working on Computer Networks and Communications, Hardware and Architecture, Artificial Intelligence, Information Systems and Organic Chemistry, having authored 8 papers that have together received 352 indexed citations. Recurring topics across this work include Software-Defined Networks and 5G (3 papers), Network Traffic and Congestion Control (3 papers), Network Packet Processing and Optimization (3 papers), Internet Traffic Analysis and Secure E-voting (3 papers), Software System Performance and Reliability (2 papers), Cloud Computing and Resource Management (2 papers), Synthetic Organic Chemistry Methods (1 paper) and Opportunistic and Delay-Tolerant Networks (1 paper). The work is most often cited by research in Computer Networks and Communications (340 citations), Hardware and Architecture (32 citations), Artificial Intelligence (86 citations), Electrical and Electronic Engineering (85 citations) and Information Systems (28 citations). Igor Ganichev has collaborated with scholars based in United States, Finland and China. Frequent co-authors include Scott Shenker, P. Brighten Godfrey, Ion Stoica, Bin Dai, Nick McKeown, Hari Balakrishnan, Somaya Arianfar, Jennifer Rexford, Guru Parulkar and Nick Feamster. Their work appears in journals such as ACM SIGCOMM Computer Communication Review.
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.