2 citations · 4 across the 10 of their papers we have counts for
11 papers
Quantum-Enhanced Learning Framework for Intelligent and AI-Native 6G Wireless Networks
Muhammad Bilal Akram Dastagir, Rakesh Saini, Omer Tariq +4
The recent convergence of 6G wireless systems and Tiny Machine Learning (TinyML) has driven the need for on-device intelligence in edge networks, where ultra-low latency, stringent…
Anti-Shortcut Distillation via Temporal Negative Knowledge Transfer
Syed Muhammad Raza, Omer Tariq, Jeongbae Son
Knowledge distillation (KD) trains a compact student by attracting it towards a converged teacher. It is silent about which directions the teacher itself learned to suppress: repul…
SAD-LoRA: Spectral Alignment for Low-Rank Knowledge Distillation
Omer Tariq, Syed Muhammad Raza, Jeongbae Son
Distilling a fine-tuned teacher into a LoRA-adapted student is a standard recipe for parameter-efficient compression, but output-level KD does not explicitly control which rank-…
Uncertainty-Aware and Decoder-Aligned Learning for Video Summarization
Omer Tariq, Syed Muhammad Raza, Jeongbae Son
Video summarization aims to produce a compact representation of a long video by selecting a subset of temporally important segments that best reflect human preferences. This task i…
BARFI-Q: Quantum-Enhanced Block Attention Residual Fusion Framework for Multivariate Time-Series Forecasting in Atom Interferometry
Muhammad Bilal Akram Dastagir, Omer Tariq, Safaa Alqrinawi +3
Atom interferometry generates heterogeneous multivariate temporal streams governed by phase evolution, fringe dynamics, control variables, and auxiliary sensing measurements. Accur…
GST-VLA: Structured Gaussian Spatial Tokens for 3D Depth-Aware Vision-Language-Action Models
Md Selim Sarowar, Omer Tariq, Sungho Kim
VLA models encode visual observations as 2D patch tokens with no intrinsic geometric structure. We introduce GST-VLA with two contributions. First, the Gaussian Spatial Tokenizer (…
Quantum-Inspired Reinforcement Learning for Secure and Sustainable AIoT-Driven Supply Chain Systems
Muhammad Bilal Akram Dastagir, Omer Tariq, Shahid Mumtaz +2
Modern supply chains must balance high-speed logistics with environmental impact and security constraints, prompting a surge of interest in AI-enabled Internet of Things (AIoT) sol…
NOS-Gate: Queue-Aware Streaming IDS for Consumer Gateways under Timing-Controlled Evasion
Muhammad Bilal, Omer Tariq, Hasan Ahmed
Timing and burst patterns can leak through encryption, and an adaptive adversary can exploit them. This undermines metadata-only detection in a stand-alone consumer gateway. Theref…
ConvXformer: Differentially Private Hybrid ConvNeXt-Transformer for Inertial Navigation
Omer Tariq, Muhammad Bilal, Muneeb Ul Hassan +2
Data-driven inertial sequence learning has revolutionized navigation in GPS-denied environments, offering superior odometric resolution compared to traditional Bayesian methods. Ho…
Learning to Undo: Rollback-Augmented Reinforcement Learning with Reversibility Signals
Andrejs Sorstkins, Omer Tariq, Muhammad Bilal
This paper proposes a reversible learning framework to improve the robustness and efficiency of value based Reinforcement Learning agents, addressing vulnerability to value overest…
QSCL-EWIL: Quantum Stochastic Contrast Learning for Enhanced WiFi-Based Indoor Localization
Muhammad Bilal Akram Dastagir, Omer Tariq, Dongsoo Han +3
WiFi-based indoor localization is essential for asset tracking, healthcare monitoring, and smart buildings. However, existing systems face challenges such as data variability, envi…