Nilakshan Kunananthaseelan

I am a PhD student at the ECSE, part of the Faculty of Engineering at Monash University, where I work on customizing foundational models for out-of-distributions. My PhD advisor is A/Prof.Mehrtash Harandi.

Prior to joining Monash University, I was working at Analog Inference. I primarily designed computer vision algorithms for efficient hardware ASICs. Additionally, I worked on text anlytics software API at ExentAI, and I was involved in creating an OCR pipeline dedicated to digitizing Tamil documents at Noolaham project.

I completed my undergraduate study at the University of Moratuwa, with a major in Electronic and Telecommunication Engineering. My undergraduate thesis was advised by Dr. Ajit Pasqual.

Email / CV / GitHub / Google Scholar / LinkedIn / Twitter /

"Don't doubt yourself, son. Doubt kills." — Robert McCall

"If you are failing to plan, you are planning to fail"

"If everything seems under control, you're not going fast enough." — Mario Andretti

Research

I have a keen interest in several areas of artificial intelligence, particularly in computer vision, multimodal representation learning, and the development of few-shot learning methods. My focus involves exploring innovative techniques within these domains to tackle complex challenges and contribute to advancing the field of AI.
Research Statement

LaViP: Language-Grounded Visual Prompts

Nilakshan Kunananthaseelan, Jing Zhang, Mehrtash Harandi
AAAI Conference on Artificial Intelligence-2024, 2023
arxiv / code /

We introduce a language-grounded visual prompting method to adapt the visual encoder of vision-language models for downstream tasks.

Undergraduate Projects

My journey into machine learning and computer vision began with a project, igniting my deep interest in these fields.

Machine-based detection and classification for bone marrow aspirate differential counts: initial development focusing on nonneoplastic cells

undergraduate
2019-09-30
website / paper /

We introduce a deeplearning pipeline for detection and classification of whiteblood cells from bonemarrow slide images.

Teaching Experience

I have served as a Teaching Assistant at Monash University for the following courses:

ECE 4076/ECE 5176: Computer Vision (Semester 1, 2023 and 2024)
ECE 4179/ECE 5179/ECE 6179: Neural Networks and Deep Learning (Semester 2, 2023 and 2024)

My responsibilities included delivering lectures, grading assignments, and mentoring students in deep learning projects.

Reviewing Activities

I have actively contributed as a reviewer for prestigious conferences and journals in the field of AI and computer vision:

WACV 2024
NeurIPS 2024
ACMM 2024
ECCV 2024 — Outstanding Reviewer Award
AAAI 2024

These activities have enabled me to stay updated with cutting-edge research and contribute to the academic community.

Design and source code from Jon Barron's website