Hey there! I’m a Data and AI enthusiast who turned my fascination with machines and numbers into a full-time gig. I’m stationed as a Senior Developer Relations Manager (Developer 🥑) at NVIDIA. Basically, I help developers and GPUs get along better.
Before joining Team Green, I spent my time at Microsoft as a Cloud Solution Architect, designing and implementing scalable, secure, and intelligent AI applications on Azure. My dedication to AI has been recognised by Microsoft, which has honored me as a Most Valuable Professional in Artificial Intelligence for eight consecutive years.
I’ve got a Ph.D. in Deep Learning from La Trobe University, done in collaboration with the Australian Institute of Sport (yes, AI can help athletes too).
When I’m not busy geeking out over neural networks, you’ll find me speaking at tech events, running AI sessions, or capturing the beauty of the wilderness with my camera.
Research Interests : Deep Learning, Computer Vision, Generative AI, Responsible AI
Apart from being an AI researcher, I enjoy most of my time being outdoors. I enjoy hiking, camping, and nature photography. Can explain myself as a travel addict, ready to hit the road at any time with the backpack.
When forced indoors, I do enjoy writing free style poems and short stories, I am an aspiring chef, and I spend a large amount of my free time exploring the wonderful spices in my kitchen.
Group Activity Recognition using Unreliable Tracked Pose
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H Thilakarathne, A Nibali, Z He, S Morgan, Neural Computing & Applications (2024)
Pose is all you need: The pose only group activity recognition system (POGARS)
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H Thilakarathne, A Nibali, Z He, S Morgan, Machine Vision and Applications 33, 95(2022)
Predicting Floods in North Central Province of Sri Lanka using Machine Learning and Data Mining Methods.
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H Thialakarathne, K Premachandra, Proceedings of the 12th Annual Sessions, Sri Lanka Association for Artificial Intelligence 2017.
Improving Assessment on MOOCs through Peer Identification and Aligned Incentives.
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Gamage D,Whiting ME,Rajapakshe T,Thilakarathne H,Perera I et al., L@S 2017 - Proceedings of the 4th (2017) ACM Conference on Learning at Scale.
Daemo: A Self-Governed Crowdsourcing Marketplace.
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Stanford HCI Research Group, UIST 2015 - Adjunct Publication of the 28th Annual ACM Symposium on User Interface Software and Technology.