Malika Nisal Ratnayake

Hi, I’m Malika Ratnayake! I am a Research Fellow at the Department of Data Science and AI at Monash University, Australia, and a 2024 National Geographic Explorer. My research focuses on the intersection of computer science, engineering, ecology, and agriculture, where I develop novel technologies and methods to advance insect pollination monitoring for agriculture and conservation.

I completed my PhD in Computer Science at Monash University in 2022, under the guidance of Professor Alan Dorin and Associate Professor Adrian Dyer. My doctoral research focused on creating computer vision and deep learning frameworks for automated pollination monitoring. Currently, I am part of an industry and government-funded collaborative project at Monash University. My role involves designing and developing robotic and edge-computing solutions for real-time insect and crop monitoring in horticulture. This work involved extensive collaborations with industry partners to design and implement systems tailored to the specific needs of agricultural stakeholders.

My research has been recognised through several prestigious awards and grants, including the National Geographic Society (United States) grant (2024), the Helmholtz Information and Data Science Academy Visiting Researcher grant (Germany, 2024), and the Green Talents Award for Outstanding Young Scientists in Sustainable Development (2022) from the German Federal Ministry of Education and Research.

I am passionate about leveraging technology to address real-world challenges, deepening our understanding of the natural world to drive conservation efforts and improve quality of life. I am always eager to collaborate on innovative projects that blend science and technology. When I’m not working, I enjoy photography, music, and movies. Feel free to reach out to me via email or social media to discuss research collaborations, share ideas, or ask any questions.

Publications

• A Motion-based Compression Algorithm for Resource-constrained Video Camera Traps

  Malika Nisal Ratnayake, Lex Gallon, Adel N Toosi, Alan Dorin
  Preprint published in arxiv.org

  DOI:doi.org/10.48550/arXiv.2405.14419 

• Spatial Monitoring and Insect Behavioural Analysis Using Computer Vision for Precision Pollination

  Malika Nisal Ratnayake, Don Chathurika Amarathunga, Asaduz Zaman, Adrian G Dyer, Alan Dorin
  Published in International Journal of Computer Vision 131, no. 3 (2023): 591-606.

  DOI:doi.org/10.1007/s11263-022-01715-4 | Full-text Access 

• A World Without Bees: New Insights from Australia for Managing Sustainability in a Changing Climate

  Adrian G Dyer, Mani Shrestha, Jair E Garcia, Scarlett R Howard, Malika Nisal Ratnayake, Alan Dorin
  Published in the Proceedings of the Royal Society of Victoria, 135(1), 2023.

  DOI:doi.org/10.1071/RS23003" 

• Fine-Grained Image Classification of Microscopic Insect Pest Species: Western Flower Thrips and Plague Thrips

  Don Chathurika Amarathunga, Malika Nisal Ratnayake, John Grundy, Alan Dorin
  Published in Computers and Electronics in Agriculture 203 (2022) 107462

  DOI:doi.org/10.1016/j.compag.2022.107462 

• Towards Computer Vision and Deep Learning Facilitated Pollination Monitoring for Agriculture

  Malika Nisal Ratnayake, Adrian G. Dyer, Alan Dorin
  Published in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2021.

  DOI:doi.org/10.1109/CVPRW53098.2021.00327 

• Towards precision apiculture: Traditional and technological insect monitoring methods in strawberry and raspberry crop polytunnels tell different pollination stories

  Scarlett R Howard, Malika Nisal Ratnayake, Adrian G Dyer, Jair E Garcia, Alan Dorin
  Published in Plos one 16.5 (2021): e0251572

  DOI:doi.org/10.1371/journal.pone.0251572 

• Tracking individual honeybees among wildflower clusters with computer vision-facilitated pollinator monitoring

  Malika Nisal Ratnayake, Adrian G Dyer, Alan Dorin
  Published in Plos one 16.2 (2021): e0239504

  DOI:doi.org/10.1371/journal.pone.0239504 

• A meta-heuristic for a bi-objective multi-commodity green distribution network

  Malika Nisal Ratnayake, Voratas Kachitvichyanukul, Huynh Trung Luong
  Published in International Journal of Logistics Systems and Management 36.2 (2020): 282-304.

  DOI:doi.org/10.1504/IJLSM.2020.107384 

• A multi-objective model for location-allocation problem with environmental considerations

  Malika Nisal Ratnayake, Voratas Kachitvichyanukul, Huynh Trung Luong
  Published in Environmental Sustainability in Asian Logistics and Supply Chains, pp. 205-217. Springer, Singapore, 2019.

  DOI:doi.org/10.1007/978-981-13-0451-4_11 

Talks and Presentations

Spatial Monitoring and Insect Behavioural Analysis Using Computer Vision for Precision Pollination

Invited poster presentation at "CV4Animals: Computer Vision for Animal Behavior Tracking and Modeling" workshop held in conjunction with Computer Vision and Pattern Recognition 2022

Workshop page | Poster | Paper

Tracking Honey Bees with Machine Vision and Artificial Intelligence

Invited Talk at the Central Association of Bee Keepers (CABK), United Kingdom (February 2022)

Event page | Youtube Video

Spatial Modelling of Cross-pollination in Crop Systems Through Multi-point Honeybee Tracking

Oral presentation at the 24th International Congress on Modelling and Simulation (MODSIM2021)

Conference page | Youtube Video | Paper

Towards Computer Vision and Deep Learning Facilitated Pollination Monitoring for Agriculture

Oral and Poster presentation at the "2nd Agriculture-Vision: Challenges & Oppotunities for Computer Vision in Agriculture" workshop held in conjunction with Computer Vision and Pattern Recognition 2021

Workshop page | Youtube Video | Poster | Paper

Tracking Individual Honeybees among Wildflower Clusters with Computer Vision-facilitated Pollinator Monitoring

Poster presentation at "CV4Animals: Computer Vision for Animal Behavior Tracking and Modeling" workshop held in conjunction with Computer Vision and Pattern Recognition 2021

Workshop page | Poster | Paper

Decoding Bees with Video Recordings

Submission for the Visualise Your Thesis Competition (2020)

Video Link

Software

• Polytrack

  Tracking multiple species of insects simultaniously with flower interaction monitoring.
  Previous versions: Polytrack 2.0 | Polytrack_v1
  

  Download | Paper

• HyDaT Tracker

  Tracking insect pollinators in complex dynamic environments.

  Download | Paper

Datasets

• Spatial monitoring and insect behavioural analysis dataset

  Malika Nisal Ratnayake, Don Chathurika Amarathunga, Asaduz Zaman, Adrian G Dyer, Alan Dorin
  

  DOI:doi.org/10.26180/21533760 | Download | Paper

• Image dataset of two morphologically close thrip species: Western Flower Thrips and Plague Thrips

  Don Chathurika Amarathunga, Malika Nisal Ratnayake, John Grundy, Alan Dorin
  

  DOI:doi.org/10.26180/21547650 | Download | Paper

• Monitoring insect pollination in strawberry and raspberry crop polytunnels

  Scarlett R Howard, Malika Nisal Ratnayake, Adrian G Dyer, Jair E Garcia, Alan Dorin
  

  DOI:doi.org/10.26180/14531892 | Download | Paper

• Honeybee video tracking data

  Malika Nisal Ratnayake, Adrian G Dyer, Alan Dorin
  

  DOI:doi.org/10.26180/5f4c8d5815940 | Download | Paper

Media and Communications

• AI can track bees on camera. Here’s how that will help farmers

  The Conversation

• How AI can be used to track pollinators in strawberry crops

  Cosmos Magazine | Greenlight Project

• Research utilising artificial intelligence track insect movements

  Stock & Land

• Pi-powered pollination monitors support farming in Australia

  Raspberry Pi News

• AI can help track insect pollinators: Here’s how it helps farmers

  The Hindu Businessline Podcast

• Farming with AI: Optimising pollination for better food production

  Monash University | Media Release

• AI and bees: A game-changing solution to better fruit farming

  2SER Radio