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Muhammad Kashif

New York University Abu Dhabi

30 papers hereh-index 11281 citations33 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author12
  • middle author18

Across the 30 of 30 papers where every author was matched, so the position is known.

fields
  • quant-ph22
  • cs.LG4
  • cs.AI1
  • cs.CL1
  • cs.RO1
  • cs.SE1
affiliations
  • New York University Abu Dhabi
HomepageORCID 0000-0003-2023-6371
same name
  • Muhammad Kashif — 1 paper, h 7
  • Muhammad Kashif — 1 paper
  • Muhammad Kashif — 1 paper, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20242026
collaborators
Showing cs.LGShow all

4 papers · 1 filter

cs.LG2026

Design Space Exploration of Hybrid Quantum Neural Networks for Chronic Kidney Disease

Muhammad Kashif, Hanzalah Mohamed Siraj, Nouhaila Innan +2

Hybrid Quantum Neural Networks (HQNNs) have recently emerged as a promising paradigm for near-term quantum machine learning. However, their practical performance strongly depends o…

cs.LG2026

FAQNAS: FLOPs-aware Hybrid Quantum Neural Architecture Search using Genetic Algorithm

Muhammad Kashif, Shaf Khalid, Alberto Marchisio +2

Hybrid Quantum Neural Networks (HQNNs), which combine parameterized quantum circuits with classical neural layers, are emerging as promising models in the noisy intermediate-scale…

cs.LG2026

Quantum vs. Classical Machine Learning: A Benchmark Study for Financial Prediction

Rehan Ahmad, Muhammad Kashif, Nouhaila Innan +1

In this paper, we present a reproducible benchmarking framework that systematically compares QML models with architecture-matched classical counterparts across three financial task…

cs.LG2025

ResQuNNs: Towards Enabling Deep Learning in Quantum Convolution Neural Networks

Muhammad Kashif, Muhammad Shafique

In this paper, we present a novel framework for enhancing the performance of Quanvolutional Neural Networks (QuNNs) by introducing trainable quanvolutional layers and addressing th…

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