Vineet Prasad

About

Vineet is a doctoral candidate in the Automation & Sustainability in Construction and Intelligent Infrastructure (ASCII) Lab at Monash University. He graduated with a Bachelor of Engineering in Electrical & Electronics from University of the South Pacific (Fiji) in 2019 with a gold medal. He received his Master of Science in Engineering degree in 2021 for his research on developing advanced parametric identification algorithms for nonlinear control systems using fractional calculus. His current multidisciplinary research at Monash concentrates on developing intelligent, smart and sustainable solutions for construction and infrastructure sectors through artificially intelligent algorithms and immersive visualizations. Concurrently, he also serves as an Assistant Lecturer in the Department of Civil Engineering, contributing to effective teaching delivery, curriculum development and assessment within the department.

Employment

• Monash University Assistant Lecturer/Ph.D. Teaching Fellow
  2024 - Present

Education

• Monash University Doctor of Philosophy (Ph.D.)
  2022 - Present
• University of the South Pacific Master of Science in Engineering
  2019 - 2021
• University of the South Pacific Bachelor of Engineering (Electrical & Electronic)
  2015 - 2018

Projects & Funding

Projects & funding information is unavailable.

Publications (6)

• ShARP-WasteSeg: A shape-aware approach to real-time segmentation of recyclables from cluttered construction and demolition waste
  Waste Management 2025 DOI: 10.1016/j.wasman.2025.02.006
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• Real-time instance segmentation of recyclables from highly cluttered construction and demolition waste streams
  Journal of Environmental Management 2024 DOI: 10.1016/j.jenvman.2024.123365
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• Optimally leveraging depth features to enhance segmentation of recyclables from cluttered construction and demolition waste streams
  Journal of Environmental Management 2024 DOI: 10.1016/j.jenvman.2024.120313
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• Modeling and parametric identification of Hammerstein systems with time delay and asymmetric dead-zones using fractional differential equations
  Mechanical Systems and Signal Processing 2022 DOI: 10.1016/j.ymssp.2021.108568
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• Identification scheme for fractional Hammerstein models with the delayed Haar wavelet
  IEEE/CAA Journal of Automatica Sinica 2020 DOI: 10.1109/jas.2020.1003093
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• Parametric Identification of Nonlinear Fractional Hammerstein Models
  Fractal and Fractional 2019 DOI: 10.3390/fractalfract4010002
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