Muhammad Khan

Muhammad Khan

New York University

H-index: 11

North America-United States

About Muhammad Khan

Muhammad Khan, With an exceptional h-index of 11 and a recent h-index of 9 (since 2020), a distinguished researcher at New York University, specializes in the field of TCP Congestion Control, Self-Organising Networks (SON), Cloud Radio Access Networks (C-RAN), Artificial Intelligence (AI), Machi.

His recent articles reflect a diverse array of research interests and contributions to the field:

Empagliflozin in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial

ZEUS: An Experimental Toolkit for Evaluating Congestion Control Algorithms in 5G Environments

[Solution] ALCC: Migrating Congestion Control To The Application Layer In Cellular Networks

An approach based on context and situation awareness to improve functional safety in complex scenarios

An AI-enabled lightweight data fusion and load optimization approach for Internet of Things

The case for model-driven interpretability of delay-based congestion control protocols

A multigraph approach for supporting computer network monitoring systems

Can we exploit machine learning to predict congestion over mmWave 5G channels?

Muhammad Khan Information

University

Position

___

Citations(all)

487

Citations(since 2020)

294

Cited By

295

hIndex(all)

11

hIndex(since 2020)

9

i10Index(all)

13

i10Index(since 2020)

9

Email

University Profile Page

New York University

Google Scholar

View Google Scholar Profile

Muhammad Khan Skills & Research Interests

TCP Congestion Control

Self-Organising Networks (SON)

Cloud Radio Access Networks (C-RAN)

Artificial Intelligence (AI)

Machi

Top articles of Muhammad Khan

Title

Journal

Author(s)

Publication Date

Empagliflozin in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial

The Lancet Diabetes & Endocrinology

O Abani

A Abbas

F Abbas

J Abbas

K Abbas

...

2023/12/1

ZEUS: An Experimental Toolkit for Evaluating Congestion Control Algorithms in 5G Environments

arXiv preprint arXiv:2208.13985

Rohail Asim

Muhammad Khan

Luis Diez

Shiva Iyer

Ramon Aguero

...

2022/8/30

[Solution] ALCC: Migrating Congestion Control To The Application Layer In Cellular Networks

Journal of Systems Research

Yasir Zaki

Rohail Asim

Muhammad Khan

Shiva Iyer

Talal Ahmad

...

2022

An approach based on context and situation awareness to improve functional safety in complex scenarios

Fabio Clarizia

Francesco Colace

Massimo De Santo

Muhammad Khan

Marco Lombardi

...

2022

An AI-enabled lightweight data fusion and load optimization approach for Internet of Things

Future Generation Computer Systems

Mian Ahmad Jan

Muhammad Zakarya

Muhammad Khan

Spyridon Mastorakis

Varun G Menon

...

2021/9/1

The case for model-driven interpretability of delay-based congestion control protocols

ACM SIGCOMM Computer Communication Review

Muhammad Khan

Yasir Zaki

Shiva Iyer

Talal Ahamd

Thomas Poetsch

...

2021/3/12

A multigraph approach for supporting computer network monitoring systems

Francesco Colace

Muhammad Khan

Marco Lombardi

Domenico Santaniello

2020/10/1

Can we exploit machine learning to predict congestion over mmWave 5G channels?

Applied Sciences

Luis Diez

Alfonso Fernández

Muhammad Khan

Yasir Zaki

Ramón Agüero

2020/9/4

Use of carbohydrate antigen 19-9 in the management of bladder cancer

Muhammad F Khan

Georgios Tsampoukas

2020/4/1

Learning congestion over millimeter-wave channels

Luis Diez

Ramón Agüero

Alfonso Fernández

Yasir Zaki

Muhammad Khan

2020/10/12

See List of Professors in Muhammad Khan University(New York University)

Co-Authors

H-index: 36
Hamed  Al-raweshidy

Hamed Al-raweshidy

Brunel University London

H-index: 27
Alfonso Fernández del Rincón

Alfonso Fernández del Rincón

Universidad de Cantabria

H-index: 22
Marco Lombardi

Marco Lombardi

Università degli Studi di Salerno

H-index: 19
Domenico Santaniello

Domenico Santaniello

Università degli Studi di Salerno

H-index: 18
Yasir Zaki

Yasir Zaki

New York University

H-index: 12
Luis Diez

Luis Diez

Universidad de Cantabria

academic-engine