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Muhammad Ashar Javid

NUST · 2026

asharjavidaj@gmail.com

Phone

923228901685

https://www.linkedin.com/in/ashar-javid/

GitHub

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Academic

Program

Electrical Engineering

CGPA

3.6

Year

2026

Education

School of Electrical Engineering and Computer Science

Address

HOUSE NO.53 OVERSEAS B, STREET 17 BAHRIA TOWN, LAHORE , Lahore , Pakistan

DOB

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Career

Current role

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Target role

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Skills

Reconfigurable Intelligent Surfaces (RIS), 6G networks, Large Language Models (LLMs), Agentic AI, Geometric Deep Learning, Seismic Data Analysis, Geophysical Datasets, Multi-Agentic AI, Signal Processing, Semantic Communication, ACP, NOMA, Backscatter, DRL

Verbatim text

The exact text the LLM saw on the page (or the booklet text from the old import). This is what powers semantic search.

Muhammad Ashar Javid
Cell: 923228901685 | Email: asharjavidaj@gmail.com
LinkedIn: https://www.linkedin.com/in/ashar-javid/
Address: HOUSE NO.53 OVERSEAS B, STREET 17 BAHRIA TOWN, LAHORE , Lahore , Pakistan
PROFESSIONAL PROFILE
Electrical Engineering student and researcher specializing in next-generation wireless communications, with a focus on
Reconﬁgurable Intelligent Surfaces (RIS) and 6G networks. Proven track record of high-impact research, including an accepted
paper at IEEE WCNC 2026 and an international research internship through MITACS Globalink. Expertise in integrating Large
Language Models (LLMs) and Agentic AI into wireless frameworks to optimize network performance. Conducting research on the
intersection of quantum-native communication and intelligent signal processing.
EDUCATION
Electrical Engineering
School of Electrical Engineering and Computer Science , Islamabad , 3.6 (2026)
INTERNSHIP EXPERIENCE
University of Alberta, Canada
09-Jun-2025 - 31-Aug-2025
1. Leveraged geometric deep learning to analyze non-Euclidean seismic data across distributed sensor arrays. 2. Processed large-
scale geophysical datasets to identify precursor patterns often missed by traditional linear models. 3. Worked in a high-stakes
research environment at UAlberta, honing technical communication and cross-functional problem-solving skills.
FINAL YEAR PROJECT
Realtime RIS Optimization for 6G networks using Multi Agent Framework
The era of 6G requires technologies like RIS, NOMA and Backscatter for ultra-reliable latency aware systems with data rates
approaching terabytes per second. Such technologies require eﬃcient management of resources in dynamic and ever evolving
environments. Traditional statictical techniques and DRL based schemes are specialised for singular kind of optimization however
require heavy computational resources to cater for a dynamic environment. We propose a LLM-reasoning based multi-agentic
technique MAFRO working through semantic communication using ACPN for eﬃcient resource management in next generation
wireless networks achieving high level of fairness and energy efficiency.
TECHNICAL EXPERTISE
Intelligent Systems & Advanced Signal Processing
Expertise lies at the intersection of traditional engineering and frontier artiﬁcial intelligence, specializing in the fusion of signal
processing with Multi-Agentic AI frameworks. By leveraging Large Language Models (LLMs) to enhance decision-making and
autonomous coordination, I develop robust solutions fo ...

AI enrichment

Muhammad Ashar Javid is an Electrical Engineering student graduating in 2026 with a 3.6 CGPA, specializing in 6G networks and Reconfigurable Intelligent Surfaces. He has research experience at the University of Alberta and has published at IEEE WCNC 2026, focusing on integrating LLMs and multi-agent systems into wireless frameworks.

Skills (AI)

["Reconfigurable Intelligent Surfaces", "6G Networks", "Large Language Models", "Multi-Agent AI", "Geometric Deep Learning", "Signal Processing", "Semantic Communication", "Python", "Research"]

Status: ai_done

Provenance

Source file: SEECS - Electrical Engineering-2026.pdf
From job #259 page 96
Created: 1778168427