Tanveer Choudhury | Federation University

Dr. Tanveer Choudhury

Deputy Head of Engineering

Contact

t.choudhury@federation.edu.au +61 (3) 51228481

Campus

Churchill Campus

Biography

Dr Tanveer Choudhury is a Lecturer in mechatronics engineering at Federation University Australia. Dr Choudhury’s expertise is in applying artificial intelligence and machine learning techniques for predictive modelling and the design and development of control systems.

Tanveer’s research covers a diverse range of disciplines including materials and surface engineering, mechanical engineering, water engineering, geotechnical engineering, mining engineering, and biomedical engineering. His research also focuses on robotics and automation, and he is actively working on developing an intelligent novel mobile robot navigation algorithm and applying the Internet of Things to develop smart power inverter and water quality monitoring systems.

Tanveer holds a PhD in engineering from Swinburne University of Technology, and worked for two years as a radio-frequency engineer at Ericsson, where he was involved with various large-scale telecommunication projects in Bangladesh, Kenya, Benin and the Ivory Coast.

Publications

Non-Conservative Efficient Collision Checking and Depth Noise-Awareness for Trajectory Planning

Journals
DOI reference: 10.1109/LRA.2025.3580318

Artificial-Intelligence-Based Prediction of Crack and Shrinkage Intensity Factor in Clay Soils During Desiccation

Journals
DOI reference: 10.3390/designs9030054

Characterization of Energy Profile and Load Flexibility in Regional Water Utilities for Cost Reduction and Sustainable Development

Journals
DOI reference: 10.3390/su17083364

An Extreme Learning Machine Algorithm to Predict the In-flight Particle Characteristics of an Atmospheric Plasma Spray Process

Journals
DOI reference: 10.1007/s11090-013-9466-4

Improving the Generalization Ability of an Artificial Neural Network in Predicting In-Flight Particle Characteristics of an Atmospheric Plasma Spray Process

Journals
DOI reference: 10.1007/s11666-012-9775-9

Artificial Neural Network application for predicting in-flight particle characteristics of an atmospheric plasma spray process

Journals
DOI reference: 10.1016/j.surfcoat.2011.04.099

Applicability of artificial neural network in hydraulic experiments using a new sewer overflow screening device

Journals
DOI reference: 10.7158/W12-019.2013.17.1

Using Artificial Neural Network to Predict the Particle Characteristics of an Atmospheric Plasma Spray Process

Conference Proceedings
DOI reference: 10.1109/ICELCE.2010.5700795

Artificial Neural Networks for the prediction of the trapping efficiency of a new sewer overflow screening device

Conference Proceedings
DOI reference:

Optimal sensing requirement for slippage prevention in robotic grasping

Conference Proceedings
DOI reference: 10.1109/ICIT.2015.7125127

New artificial intelligence based tire size identification for fast and safe inflating cycle

Conference Proceedings
DOI reference: 10.1109/ICIT.2015.7125347

Modular implementation of artificial neural network in predicting in-flight particle characteristics of an atmospheric plasma spray process

Journals
DOI reference: 10.1016/j.engappai.2015.06.015

A Study and Review on Vehicle Suspension System and Introduction of a High -Bandwidth Configured Quarter Car Suspension System

Journals
DOI reference:

Study and Review on Vehicle Suspension Control Theories and Introduction of Novel Adaptive Skyhook Control System

Journals
DOI reference:

Study and Comparison on Linear Electromagnetic Shock Absorbers among other Available Intelligent Vibration Dampers

Journals
DOI reference:

Friction-based slip detection in robotic grasping

Conference Proceedings
DOI reference: 10.1109/IECON.2015.7392863

Friction-based slippage and tangential force detection in robotic grasping

Conference Proceedings
DOI reference: 10.1109/IECON.2015.7392864

Dr. Tanveer Choudhury

Deputy Head of Engineering

Biography

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