Associate Professor Simit Raval
- PhD Mining Engineering (2008 – 2011) from theUniversity of New South Wales, Sydney, Australia
- Bachelor of Mining Engineering (1991-1994) from theGuru Ghasidas University, Bilaspur, India
Associate Professor Simit Raval is Director of Undergraduate Studies in Mining Engineer and Co-Director of the Laboratory for Imaging of the Mine Environment (LIME), at the University of New South Wales (ʹڲƱ) in Sydney, Australia. He is specialised in the integration of sensing technologies to drive applied innovation in mining, environmental and civil engineering sectors. He leads a group of researchers focused on utilising data from sensors mounted on various platforms, from satellite through to UAVs, to visualise, identify and monitor operational environments. He has received several competitive research grants, including SIX nationally competitive grants as the project leader. He has supervised PhD research projects involving drone-based smart sensing (multispectral, hyperspectral and LiDAR), underground mobile laser scanning, image-based automated material characterisation, mine rehabilitation/closure, climate change and asteroid mining. He has received SIX teaching awards including ʹڲƱ Vice Chancellor’s Awards for Outstanding Contributions to Student Learning (2020) and the International Tim Show Award for Innovation in Teaching and Learning (2018).
- Publications
- Media
- Grants
- Awards
- Research Activities
- Engagement
- Teaching and Supervision
I have received a total of more than $3 million competitive research funding that includes:
Category 1 (Federal government competitive grants)
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Raval S(2024).Methane Matters: Updates on Relevant Advances for Coal Mine Emissions.Australian Coal Industry’s Research Program (ACARP).
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Raval S(Project Leader), Banerjee B and Roddis D (2024).Assessment of sensors and airflow modelling for their suitability to quantify methane emissions in open cut mines.Australian Coal Industry’s Research Program (ACARP).
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Raval S (Project Leader)and Banerjee B(2024). “SCANDY” - A handheld Imaging System for Real Time Spoil Categorisation.Australian Coal Industry’s Research Program (ACARP).
- Raval S (2022).Image-based automated characterisation of waste materials - Extension. Australian Coal Industry’s Research Program (ACARP).
- Khalili-Naghadeh N., …Raval S. (total 16 CIs) (2022). ARC Industry Transformation Research Hub for Resilient and Intelligent Infrastructure Systems (RIIS) in Urban, Resources and Energy Sectors.
- Raval S (2020). Automated structural mapping in underground mines using mobile laser scanning technology (Extension). Australian Coal Industry’s Research Program (ACARP).
- Raval S (2019).Image-based automated characterisation of waste materials. Australian Coal Industry’s Research Program (ACARP).
- Fityus S, Simmons J, Thoeni K, Burton G and Raval S (2019). Baseline data for the development of automated characterisation of waste materials. Australian Coal Industry’s Research Program (ACARP).
- Raval S (Project Leader) and Canbulat I (2017). Automated structural mapping in underground mines using mobile laser scanning technology. Australian Coal Industry’s Research Program (ACARP).
- Raval S (Project Leader), Shen X, Masoumi H and Tannant D (2016). Improved structural mapping of pit walls using UAV-based mobile laser scanning. Australian Coal Industry’s Research Program (ACARP).
Category 2, 3 (State, Industry, University and School level competitive grants and other grants)
- Raval S. (2023). Advanced underground laser scanning for safety and automation. Azure Mining Technology funded industry research project.
- Raval S (Project Leader), Tabelin C and Saydam S (2022). On-Belt Lithium Ore Characterisation: Choosing the right technology. Australian Remote Operations for Space and Earth (AROSE) facilitated industry research.
- Raval S (Project Leader), Le-Hussain F, Zhang C, Li B (2022). Thermal infrared (TIR) and multi-spectral remote sensing.
- Kara S... Raval S. (total 21 CIs) (2021). BHP Tailings Challenge Proof of Concept Stage.
- Raval S. (2019). Automated volumetric calculation of grain storage. Industry (ANZ bank) funding through Innovation Central Sydney.
- Raval S (Project Leader) and Rasekh (2019). Development of virtual reality based interactive sustainable mining practice module. MERE School Teaching Initiative Grant.
- Hussain F, Clark S and Raval S (2019). Impact of CO2 sequestration on groundwater resources and vegetation. ʹڲƱ MERE Collaborative Research Grant.
- Raval S (2017). Precision data integration tool for a friction free agronomic workflow. Tech Voucher Grant funded by Agronomeye Pty Ltd and NSW Department of Industries.
- Raval S (Project Leader) and Canbulat I (2016). Underground mobile laser scanner. ʹڲƱ School of Mining Research Grant.
- Raval S (Project Leader), Sharifzadeh M and Kizil M (2017). Evaluation of mobile laser scanning for rapid rock mass characterisation in underground mining environment. MEA Collaborative Research grant.
- Cullen PJ, Raval S, Prescott S, Spicer P, Boyer C, Saydam S and Triantafilis J (2017). High Resolution Laser-induced Breakdown Spectroscopy (LIBS) Imaging. ʹڲƱ Research Infrastructure Scheme.
- Raval S (Project Leader), Chanda E, Unger C and Winchester S (2016). Review of the Socio Environmental Aspect of Mining Course. Mining Education Australia (MEA).
- Cullen PJ, Raval S and other 9 co-investigators (2015). Provision of non-thermal plasma technology and hyperspectral imaging. ʹڲƱ Research Infrastructure Scheme.
- Raval S, Timms W and Taplin R (2014). A novel approach to monitor peat swamp conditions in the vicinity of underground mines using a combination of LiDAR, radar, and time-series optical satellite data. ʹڲƱ School of Mining Research Grant.
- Taplin R and Raval S (2014). Operationalising best practice in biodiversity offsets for coal mining in the Upper Hunter/Bowen Basin: A toolkit for industry. ʹڲƱ School of Mining Research Grant.
- Raval S and Taplin R (2013). Investigating the capabilities of hyperspectral remote sensing in detecting fugitive metals around the Yerranderie Silver Mine in the Blue Mountains National Park. ʹڲƱ Faculty of Engineering Early Career Researcher Grant.
- Raval S (2013). Development of satellite imagery based most suitable vegetation index to monitor mine site rehabilitation. ʹڲƱ School of Mining Research Grant.
- Taplin R and Raval S (2013). Assessing the effectiveness of biodiversity offsetting efforts to balance conservation and mining industry impacts. ʹڲƱ School of Mining Research Grant.
- Raval S (2012). Investigating capabilities of an advanced Interferometry in detecting horizontal displacement at the Metropolitan Mine. ʹڲƱ School of Mining Research Grant.
- Raval S (2011). Provision for spectroradiometer and image processing software. ʹڲƱ School of Mining Laboratory Equipment Grant.
- "Environment Champion" – the title bestowed by the student society (MERESOC) (2022).
- ʹڲƱ Vice Chancellor’s Awards for Outstanding Contributions to Student Learning (2020).
- Postgraduate Coursework Teaching Excellence Award(2020) by ʹڲƱ Engineering,
- The International Tim Show Award for Innovation in Teaching and Learning (2018) presented by the Society of Mining Professors (SOMP).
- Best Lecturer Award 2017 judged by the Mining Society (MINSOC) - A student-run society for Mining Engineering Undergraduates and Postgraduates at ʹڲƱ.
- School of Mining Engineering Teaching Award(2015) judged by the peers.
- The Best Teacher Award (2013) judged by the IEEE conference committee for MOOC, Innovation and Technology in Education (MITE).
- The Endeavour Postgraduate Award funded by the Australian Government (2008).
- The inaugural Australian Centre for Sustainable Mining Practices (ACSMP) scholarship award (2010).
- Finalist for the Dean’s Award for Excellence in Postgraduate Research, a poster competition at ʹڲƱ (2010).
I have developed an interdisciplinary research approach that is capable of addressing wider issues of sustainable mining practices and innovation in mining.
I am currently engaged in the following TWO core research domains:
- Industrial Automation
- Optimising LiDAR for specific application, both at hardware and software levels.