Tharindu Kaluarachchi joined the Augmented Human Lab in October 2015 as an intern. In 2017 he received his B.Sc. honours degree in Electronic and Telecommunication Engineering from University of Moratuwa Sri Lanka. After that, he worked for two years as a research and development engineer at Cyrup (Pvt). Ltd. which is a start-up in Sri Lanka. There he has worked on developing solutions for local and international businesses using portable electronics, image processing, and machine learning.
Now he is conducting research as a Ph.D. student in the area of Human-Centered Machine Learning. He is interested in unsupervised learning, human-computer interaction, Artificial Intelligence in general and its real-world applications. He is hoping to use AI to help people learn things efficiently.
He likes to play badminton, TT, any card game, any board game, any role-playing game and he enjoys travelling, hiking, swimming, walking, singing, dancing, playing guitar and cajong
Kaluarachchi, T., Sapkota, S., Taradel, J., Thevenon, A., Matthies, D.J.C., and Nanayakkara, S.C., 2021. EyeKnowYou: A DIY Toolkit to Support Monitoring Cognitive Load and Actual Screen Time using a Head-Mounted Webcam. In MobileHCI ’21 Extended Abstracts: The ACM International Conference on Mobile Human Computer Interaction, Sept. 27- Oct. 1, 2021, Touluse, France.
Kaluarachchi, T., Reis, A., and Nanayakkara, S.C., 2021. A Review of Recent Deep Learning Approaches in Human-Centered Machine Learning. Sensors. 21(7):2514.
Withana, A., Kaluarachchi, T., Singhabahu, C., Ransiri, S., Shi, Y. and Nanayakkara, S.C., 2020. waveSense: Low Power Voxel-tracking Technique for Resource Limited Devices. In AHs ’20: Augmented Humans International Conference (AHs ’20), March 16–17, 2020, Kaiserslautern, Germany.
Dissanayake, V., Zhang, H., Billinghurst, M. and Nanayakkara, S.C., 2020. Speech Emotion Recognition ‘in the wild' using an Autoencoder. Proc. Interspeech 2020, pp.526-530.
Siriwardhana, S., Kaluarachchi, T., Billinghurst, M. and Nanayakkara, S.C., 2020. Multimodal Emotion Recognition With Transformer-Based Self Supervised Feature Fusion. IEEE Access, 8, pp.176274-176285.
Withana, A., Ransiri, S., Kaluarachchi, T., Singhabahu, C., Shi, Y., Elvitigala, S., Nanayakkara, S.C., 2016. waveSense: Ultra Low Power Gesture Sensing Based on Selective Volumetric Illumination, In proceedings of the 29th Annual Symposium on User Interface Software and Technology (UIST '16)