Mohammad Alizadeh

3.9k citations
22 papers · 2.1k indexed · 2 hit papers · h-index 11

Mohammad Alizadeh

21 papers receiving 2.0k citations

Hit Papers

Neural Adaptive Video Streaming with Pensieve9092016202620192022250500750

Peers

Mohammad Alizadeh
Comparison fields: 5 of 68
  • Computer Networks and Communications 1.2k
  • Signal Processing 483
  • Computer Vision and Pattern Recognition 873
  • Information Systems 510
  • Hardware and Architecture 101
Replace Tim Wauters with:
Tim Wauters Belgium
Junchen Jiang United States
Philip Branch Australia
Rocky K. C. Chang Hong Kong
Peter Bodík United States
Lusheng Ji United States
Dan Lin United States
Deep Medhi United States
Kien A. Hua United States
Ravi Netravali United States
Mohammad Alizadeh relative to Tim Wauters Belgium Tim Wauters's profile →
Citations per field
00.5×2.5×
Tim Wauters · 1×
Citations per year

Countries citing papers authored by Mohammad Alizadeh

Since Specialization
Citations

This map shows the geographic impact of Mohammad Alizadeh'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 Mohammad Alizadeh with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mohammad Alizadeh more than expected).

Fields of papers citing papers by Mohammad Alizadeh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mohammad Alizadeh. 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 Mohammad Alizadeh. The network helps show where Mohammad Alizadeh may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Mohammad Alizadeh, 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 Mohammad Alizadeh Line = papers co-authored together Mohammad Alizadeh links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20246
3 20231
4 20232
5 20233
6 20224
7 202129
8 202129
9 202076
10
SageDB: A Learned Database System
201970
11
Elasticity Detection: A Building Block for Delay-Sensitive Congestion Control
20181
12 20187
13
Neural Adaptive Video Streaming with Pensievebreakdown →
2017909
14 201717
15 201615
16
Resource Management with Deep Reinforcement Learningbreakdown →
2016722
17 2016114
18
Threshold Effects of External Debt on Economic Growth of Iran: Smooth Transition Regression (STR) Model
20151
19 201215
20 20125

About Mohammad Alizadeh

Mohammad Alizadeh is a scholar working on Computer Networks and Communications, Statistics and Probability and Hardware and Architecture, having authored 22 papers that have together received 2.1k indexed citations. Recurring topics across this work include IoT and Edge/Fog Computing (3 papers), Statistical Distribution Estimation and Applications (3 papers), Cloud Computing and Resource Management (3 papers), Statistical Methods and Bayesian Inference (2 papers), Advanced Database Systems and Queries (2 papers), Software-Defined Networks and 5G (2 papers), Probabilistic and Robust Engineering Design (2 papers) and Network Traffic and Congestion Control (2 papers). The work is most often cited by research in Computer Networks and Communications (1.2k citations), Signal Processing (483 citations) and Computer Vision and Pattern Recognition (873 citations). Mohammad Alizadeh has collaborated with scholars based in United States, Iran and United Kingdom. Frequent co-authors include Hongzi Mao, Ravi Netravali, Ishai Menache, Srikanth Kandula, Wei Bai, Li Chen, Kai Chen, Ebrahim Akbari, Amir Masoud Rahmani and Mehrdad Khani. Their work appears in journals such as Journal of Statistical Computation and Simulation, Communications of the ACM, ACM SIGMETRICS Performance Evaluation Review, Journal of Computational and Applied Mathematics and Journal of Applied Statistics.

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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