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Beenish Bakhtawar

The Hong Kong Polytechnic University

Hong Kong

Research Interests

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Articles (9)

Year:

2026

Year:

2025

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2025

Year:

2025

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2025

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2025

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2025

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2024

Year:

2023

Collaborators (2)

Ali Fares

Postgraduate Researcher

The Hong Kong Polytechnic University

HONG KONG

View details

Ridwan Taiwo

Research Staff

The Hong Kong Polytechnic University

HONG KONG

View details

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Beenish Bakhtawar

Research Interests

Make your next move.

Articles (9)

Toward smart water infrastructure monitoring: Bayesian-optimized interpretable deep learning for pipeline failure prediction

Explainable deep learning models for predicting water pipe failures

Ageing underground water pipelines: Time-to-failure models, gaps and future directions

Multi-step time-to-failure predictions in water pipelines using feature engineering and cascading ensembles

Time-to-failure based deterioration factors of water networks: Systematic review and prioritization

Damage assessment of modular integrated construction during transport and assembly using a hybrid CNN–Gated recurrent unit model

AIoT-Driven Leak Detection in Real Water Networks Using Hydrophones

Data-Driven Approaches for Vibroacoustic Localization of Leaks in Water Distribution Networks

State-of-the-art review of leak diagnostic experiments: Toward a smart water network

Collaborators (2)

Ali Fares

Ridwan Taiwo

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