I am currently focusing on Deep Learning AI applications to Australian industries.

2022: 2nd place finish in NASA-sponsored Mars Spectrometry 2: Gas Chromatography Challenge: https://drivendata.co/blog/mars-2-gcms-challenge-winners

  • CP2410: Algorithms and Data Structures (Level 2; TSV)
  • CP3102: Multidisciplinary Project (Level 3; TSV)
  • CP3103: Independent Project (Level 3; CNS & TSV)
  • CP3407: Advanced Software Engineering (Level 3; TSV)
  • CP3501: Deep Learning (Level 3; TSV)
  • 2022: Kaggle Competitions Expert https://www.kaggle.com/dmitrykonovalov
  • Computer vision with Convolutional Neural Networks
  • Application of Deep Learning AI to Northern Australia Beef Industry, Aquaculture, Australian Great Barrier Reef monitoring
  • 2002 to present - Senior Lecturer, James Cook University (Townsville)
Research Disciplines
Socio-Economic Objectives

These are the most recent publications associated with this author. To see a detailed profile of all publications stored at JCU, visit ResearchOnline@JCU. Hover over Altmetrics badges to see social impact.

Journal Articles
Conference Papers

ResearchOnline@JCU stores 45+ research outputs authored by Dr Dmitry Konovalov from 2004 onwards.

Current Funding

Current and recent Research Funding to JCU is shown by funding source and project.

Herbert Cane Productivity Services Ltd - Contract Research

Developing a proof of concept AI for the identification and counting of feral pigs

Indicative Funding
$20,000 over 1 year
The aims of the project is use create a proof of concept Artificial Intelligence capable to count feral pigs entering traps and then when the majority of the pigs has entered the door closes, trapping the pigs.
Marcus Sheaves and Dmitry Konovalov (College of Science & Engineering)
Feral Pig Trapping

Great Barrier Reef Foundation - Reef Trust Partnership

Integrated reef fish monitoring - Nursery Seascapes

Indicative Funding
$102,345 over 2 years (administered by Australian Institute of Marine Science)
A 2 year monitoring program to understand the abundance, diversity, and assemblage composition of Great Barrier Reef Fishes. Within this program, JCU Marine Data Tech will be working with project partners conducting bi-annual surveys of reef fishes in nursery seascapes in the central GBR. Data will be collected using stereo Remote Underwater Video Systems and processed using Artificial Intelligence computing.
Michael Bradley, Dmitry Konovalov and Marcus Sheaves (College of Science & Engineering)
Reef Fish; Seascape; Great Barrier Reef; Fisheries; Monitoring; Nursery grounds

Advisory Accreditation: I can be on your Advisory Panel as a Primary or Secondary Advisor.

These Higher Degree Research projects are either current or by students who have completed their studies within the past 5 years at JCU. Linked titles show theses available within ResearchOnline@JCU.


The map shows research collaborations by institution from the past 7 years.
Note: Map points are indicative of the countries or states that institutions are associated with.

  • 5+ collaborations
  • 4 collaborations
  • 3 collaborations
  • 2 collaborations
  • 1 collaboration
  • Indicates the Tropics (Torrid Zone)

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  • 17.047, Faculty of Science & Engineering (Townsville campus)
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