Research Interests

My research has always revolved around the topics of machine learning (ML) and deep learning (DL), covering the application of ML algorithms in diverse domains. I hold a profound interest in neural networks, particularly in their applications within the commercial realm. Additionally, I derive great joy from exploring the fascinating field of natural language processing, which offers a multitude of possibilities for enhancing human-computer interactions and extracting valuable insights from textual data.

My current research interests focus on building intelligent systems that can learn and reason, drawing on advances in Generative AI, large language models, and foundation models to solve complex real-world problems.

My interests extend to next-generation AI hardware and systems, such as specialized accelerators, high-performance computing platforms, and distributed infrastructures, that make large-scale model training and inference faster, more efficient, and economically viable.

All of this work is conducted under the startup I founded, NirvanaClouds. Previously, I had the opportunity to work as a research assistant in the MPACT research Lab at the Department of Electrical & Computer Engineering, Florida International University, USA. I dedicated approximately 1 year to this role, where my focus was on the application of reinforcement learning and game theory for spectrum sharing, particularly in the context of LTE in Unlicensed Spectrum.

Before my time as a research assistant in the MPACT research Lab, I had the opportunity to conduct research as an undergraduate student in the field of "V2X communications." This research was conducted in association with the Department of Electronic & Telecommunications Engineering at the University of Moratuwa, Sri Lanka. There I designed a virtual traffic light control algorithm that can dynamically optimize the flow of traffic in road intersections using IEEE 802.11p/1609.x as the standards for the V2V data dissemination.

You can find some of my publications below.

"AI will be 10 times bigger than the Industrial Revolution — and maybe 10 times faster."

— Demis Hassabis

Publications

Conference Papers

Thesis & Dissertation