Scholar
Muhammad Umer
Google Scholar ID: PIzXX3sAAAAJ
Stanford University
Citations & Impact
Citations
99
H-index
6
i10-index
4
Publications
13
Co-authors
17
list available
Publications
Resume (English only)
Academic Achievements
- - Journal: Intelligent Spectrum Sharing in Integrated TN-NTNs: A Hierarchical Deep Reinforcement Learning Approach, submitted to IEEE Wireless Communications [under review].
- - Journal: RIS-Assisted Aerial Non-Terrestrial Networks: An Intelligent Synergy with Deep Reinforcement Learning, accepted by IEEE Vehicular Technology Magazine [Preprint].
Research Experience
- - R&D Engineer at Adept (ATS) Inc. (July 2024 - Present): Contributing to the development of Ascend, a cutting-edge tool for generating synthetic data, focusing on data anonymization and implementing correlative masking techniques.
- - Research Assistant at Information Processing and Transmission Lab (IPT) (May 2023 - Present): Conducting research focused on addressing the evolving challenges of beyond 5G and 6G wireless networks, actively engaged in pioneering novel network architectures.
- - Research Assistant at TUKL Research and Development Lab (June 2022 - Mar. 2023): Contributed to the advancement of table recognition in image-based documents to automate information extraction.
- - Research Assistant at Signal Processing & Machine Learning Lab (SIGMA) (Oct. 2021 - Jan. 2022): Contributed to the development of a sickle cell anemia detection system.
Education
- Bachelor's degree: Electrical Engineering, National University of Sciences & Technology (NUST), Supervisor: Dr. Syed Ali Hassan.
Background
- Currently an R&D engineer at Adept (ATS) Inc. Prior to this, I was an undergraduate student at the National University of Sciences & Technology (NUST), where I graduated with a Bachelor's degree in Electrical Engineering. I am also serving as a research assistant at the Information Processing and Transmission Lab (IPT) under the supervision of Dr. Syed Ali Hassan. My final year project involved developing a novel reinforcement learning-based optimization framework for resource allocation in next-generation wireless networks. I have a keen interest in the intersection of artificial intelligence and communication theory, and I am particularly passionate about applying cutting-edge AI techniques to tackle the evolving challenges of 6G networking. Through my research and expertise, I am committed to fostering innovation and enhancing global connectivity.
