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Dr. Anand Koirala

Doctor of Philosophy
Post Doctoral Research Fellow
School of Health, Medical and Applied Sciences
Institute for Future Farming Systems
Rockhampton North
Building 361 - Open Space
1st Floor
About Me

Dr Anand Koirala:
I am working as Research Officer in School of Health, Medical and Applied Sciences, CQUniversity, Australia. I obtained my PhD from CQUniversity, in 2020. I have completed Master of Engineering Science (Electrical and Electronics) from University of Southern Queensland, Australia, and Bachelor of Engineering (Electronics and Communications) from Tribhuvan University, Nepal. I have provided machine vision solutions and consulting services for Australian industries (horticulture, aquaculture, medical and automotive). My research interest is in developing computer vision decision support systems based on deep learning and AI.

General
Background

I have my academic background in Electronics and communications engineering with a PhD in computer vision and deep learning applied to horticultural applications. My expertise and experience is in design, development, and deployment of machine vision systems on broad areas including horticulture, fisheries, automotive and medical imaging. I have delivered several short-term projects for engineering consulting firm and industries (e.g., AusIndustry, Enterprise Connect and DFAT/AIC).
Over the past six years I am involved with IFFS at CQUniversity in delivering the project funded by DAWR R&D4Profit program and managed through Hort Innovation where I
was involved (during and post PhD) with data collection on farms in Qld and NT, and interaction with growers, Department of Agriculture staff and others using the prototype imaging system which is awaiting licensing on the IP.

Universities Studied At

  1. Central Queensland University, Rockhampton, Australia
        Degree: Doctor of Philosophy (PhD)
        Doctoral Thesis: "Precision Agriculture: Exploration of machine learning approaches for assessing mangocrop quantity"
  2. University of Southern Queensland, Toowoomba, Australia
        Degree: Master of Engineering Science major in Electrical and Electronic Engineering
        Masters Thesis: "Feasibility study of incorporating barometric pressure transducers in miniature UAV forobstacle avoidance in an indoor environment"
  3. Tribhuwan University, Kathmandu, Nepal
        Degree: Bachelor’s Degree in Electronics & Communications Engineering
        Dissertation: "Home Security System"

 

Universities Worked At

School of Health, Medical and Applied Sciences, Institute for Future Farming Systems (IFFS), Central Queensland University

Awards

Regional Universities Network (RUN) scholarship for PhD, Central Queensland University

Previous teaching

  • Completed 'Adult Learning in Practice (OLTC20005)’
  • Completed Research Accelerate program- ‘Supervising Doctoral Studies (SDS_10)’

Professional Experience

  • Demonstrated ability to conduct research and development activities either individually or in a team environment.
  • Proven ability to drive research projects and provide postgraduate supervision.
  • Proven record of timely publication and reviews on state-of-the-art in the field of related research.
  • Highly developed problem-solving skills and proven ability to build integrated solutions and evolve those as needed.
  • Demonstrated capability to engage with stakeholders and industry partners to meet the project expectations.
  • Demonstrated cross-departmental and cross-institutional collaboration and proven ability to work in diverse projects across different industries.

Professional Memberships

  1. Professional Engineer, ANZSCO Skill level 1, Electronics Engineer (ANZSCO Code 233411), Engineers Australia (EA id: 5028926).
  2. Registered member of Nepal Engineering Council (Regd. No. 2858 “Electronics and Communication Engineer”).

Responsibilities

  • Design and develop machine vision solution and decision support systems for horticultural applications
  • Orchard imaging system hardware design and software programming
  • Assist on the development of vision system for auto harvester
  • Provide supervision to postgraduate students and interns
  • Assist in the preparation of grant applications
  • Preparation and publication of journal articles, conference papers and scientific reports

Key Achievements

  • Developed Orchard imaging system- consisting of cameras, GPS receiver and LED lights.
  • Developed processing pipeline for automated spatial registration and processing of image data from orchard blocks for visualization in web maps.
  • Designed and developed machine learning models for flower/fruit detection, tracking and yield estimation.
  • Developed software apps for image acquisition in fruit sizing applications.
  • Developed user interface for auto-harvester’s vision system and actuator controls.

 

 

Computer Software

  • Computer vision and image processing R&D experience with solid knowledge of deep learning object detection and ML algorithms, techniques, and packages.
  • Experience with deploying deep learning object detection models in Amazon AWS (EC2instance and S3 bucket) cloud platform.
  • Experience with deep learning CNN object detection frameworks- R2CNN, Faster R-CNN,YOLO, and SSD.
  • Experience with researching and developing AI models using OpenCV and deep learning libraries- Keras and TensorFlow.
  • Python programming experience with a little touch on Java and C++.
  • Experience with Microsoft Windows and Linux (Ubuntu) operating systems.
  • Experience with edge computing devices and optimization libraries like OpenVino.

Consultancy Work

  1. Senior Computer Vision Engineer
    School of Information Technology and Systems,University of Canberra(www.canberra.edu.au)
    Developed deep learning AI model for detection of malaria parasite in microscope images of bloodsmears
  2. Senior Computer Vision Engineer
    Corematic Engineering (www.corematic.com.au)
    Developed deep learning AI model for vehicle hail damage assessment on camera images.
  3. Senior Computer Vision Engineer
    Easy Skill Australia Pty Ltd (www.easy-skill.com)
    Developed deep learning AI model for defect assessment of macadamia nuts in a sorter.
  4. IT support administrator
    Ignite (www.igniteco.com/) talent business.
    Conducted IT support and desktop rollout activities representing Lenovo.

Recent Research Projects
Mango-tech (ICG002347)
From: 20/02/2023 to 20/07/2023
Grant: Competitive Grant (Category 2: Other Public Sector)
Funding Scheme: Department of Industry, Innovation & Science - Innovation Connections Researcher Placement
Total Funding: $50,000.00
Study to review automation opportunities within the avocado production system (AV22002 CON-002516)
From: 08/02/2023 to 01/08/2024
Grant: Non-Gov Tender (Category 1: Aust Competitive Grant)
Funding Scheme: Hort Innovation RFP AV22002 Study to review automation opportunities within the avocado production system
Total Funding: $163,500.00
Research Supervision
Accreditation

I am currently accredited for supervision in the following:

  • 0801 Artificial Intelligence and Image Processing

At the level of Principal Supervisor


Current Capacity
I am currently available to supervise more research candidates
Current Supervision
Master of Research
Benchmarking new methods for estimation of tree fruit harvest timing and crop load
Associate Supervisor
Master of Research
Deep learning in estimation of fruit attributes using near infrared spectroscopy
Associate Supervisor
Doctor of Philosophy
New deep learning architectures for mango yield estimation
Associate Supervisor
Research Interests
Information And Computing Sciences

Artificial Intelligence and Image Processing - Computer Vision
Interest in building innovative but cheap and affordable solution based on AI.

Publications
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Teaching
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