Hello world!
I am the Lead ML Engineer at ParadigmAI and a visiting researcher at KIXLAB, the human–computer interaction lab at KAIST. I graduated from UCSC with an honours degree in Computer Science and am currently reading for an M.Sc in Data Science & AI at the University of Moratuwa.
My research interests primarily lie in the intersection of reinforcement learning and computer games. I am particularly interested in studying about intelligent agents that improve with experience.
In a much broader sense, I like to work on theoretical and application research topics involving artificial intelligence.
(+94) 71 908 4020
oshan [DOT] ivantha [AT] g**** [DOT] com
Research Interests
Reinforcement Learning | Machine Learning | Artificial Intelligence | Game Theory | Computer Games | Computer VisionNews
Jul 2026
My paper Affordable Winner's-Curse Correction: Paired-Offset Reevaluation for Hyperparameter Search on a Single GPU was accepted at the GlobalSouthAI workshop at IJCAI-ECAI 2026, held in Bremen, Germany.
My paper Affordable Winner's-Curse Correction: Paired-Offset Reevaluation for Hyperparameter Search on a Single GPU was accepted at the GlobalSouthAI workshop at IJCAI-ECAI 2026, held in Bremen, Germany.
Sep 2025
Our paper On Privacy-Preserved Machine Learning Using Secure Multi-Party Computing: Techniques and Trends was published in Computers, Materials & Continua (CMC).
Our paper On Privacy-Preserved Machine Learning Using Secure Multi-Party Computing: Techniques and Trends was published in Computers, Materials & Continua (CMC).
Mar 2025
I joined the Colombo HCI Lab at UCSC as a Research Assistant, working with Dr. Dilrukshi Gamage on deepfake detection and media literacy for the Global South.
I joined the Colombo HCI Lab at UCSC as a Research Assistant, working with Dr. Dilrukshi Gamage on deepfake detection and media literacy for the Global South.
Aug 2024
Our paper on the Aya dataset — an open-access collection for multilingual instruction tuning — was published at ACL 2024.
Our paper on the Aya dataset — an open-access collection for multilingual instruction tuning — was published at ACL 2024.