Faculty Muhammad Salman 2

Muhammad Salman

Assistant Professor

My name is Muhammad Salman. I hold a Ph.D. degree in Electrical and Computer Engineering from Inha University, South Korea, with a joint M.S. degree in Electronic Engineering from Politecnico di Torino (Italy) and Chalmers University of Technology (Sweden), and a B.S. degree in Elecronic Engineering from BUITEMS (Pakistan). My international experience includes a year-long Postdoctoral position at KENTECH, South Korea; and five years as a Lab Engineer and Lecturer at Effat University in Saudi Arabia. I also served as a Teaching Assistant at Inha University, where I taught various courses. My research focus spans Computer and Wireless Networks, Signal Analysis, and its Applications.

Academic Background
PhD (Computer Science and Engineering) Inha University March 01, 2020 - February 17, 2023
Honours and Awards
WiSOM: WiFi-enabled self-adaptive system for monitoring the occupancy in smart buildings May 01, 2024 Muhammad Salman, Lismer Andres Caceres-Najarro, Young-Duk Seo, Youngtae Noh, Energy - Volume: 294, Article Number: 130420, Pages: 12
Evolutionary Tracking Algorithm Based on Combined Received Signal Strength and Angle of Arrival Measurements in Wireless Sensor Networks October 02, 2023 Lismer Andres Caceres Najarro, Iickho Song, Slavisa Tomic, Muhammad Salman, Youngtae Noh, Kiseon Kim, IEEE Sensors Journal - Volume 23, Issue 19, Pages 23734-23743
DARCAS: Dynamic Association Regulator Considering Airtime Over SDN-Enabled Framework October 15, 2022 Muhammad Salman, Jin-Ho Son, Dong-Wan Choi, Uichin Lee, Youngtae Noh, IEEE Internet of Things Journal - Volume 9, Issue 20, Pages 20719-20732
CSI:DeSpy-Enabling effortless spy camera detection via passive sensing of user activities and bitrate variations. July 07, 2022 Muhammad Salman, Nguyen Dao, Uichin Lee, Youngtae Noh, Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies - Volume 6, Issue 2, Article No. 72
DeepDeSpy: A Deep Learning-Based Wireless Spy Camera Detection System November 01, 2021 Dinhnguyen Dao, Muhammad Salman, Youngtae Noh, IEEE Access - Volume 9, Pages 145486-145497
Study on performance of AQM schemes over TCP variants in different network environments January 03, 2021 Muhammad Salman, Touseef Javed Chaudhery, Youngtae Noh, IET Communications - Volume 15, Issue 1, Pages 93-111
Postdoctoral Researcher KENTECH February 25, 2023 - March 01, 2024
Lecturer EFFAT University August 01, 2014 - May 30, 2019