collaborators

9 papers

cs.AR2026

PCB-QA: Evaluating LLMs over the First Printed Circuit Board Design Question-Answer Dataset

Sahana Srinivasan, Benjamin Tan, Benjamin Turnbull +1

Large Language Models (LLMs) have demonstrated capabilities in electronic design automation (EDA) for integrated circuits. However, their applications in printed circuit board (PCB…

cs.AR2026

Surveying GenAI-based Automation in Printed Circuit Board Design and Test

Sahana Srinivasan, Benjamin Turnbull, Hammond Pearce

Generative artificial intelligence (GenAI) is increasingly used for applications in the hardware and software domains. It purports to reduce the manual effort involved in the devel…

cs.CL2025

LEME: Open Large Language Models for Ophthalmology with Advanced Reasoning and Clinical Validation

Hyunjae Kim, Xuguang Ai, Sahana Srinivasan +27

The rising prevalence of eye diseases poses a growing public health burden. Large language models (LLMs) offer a promising path to reduce documentation workload and support clinica…

eess.IV2025

Is an Ultra Large Natural Image-Based Foundation Model Superior to a Retina-Specific Model for Detecting Ocular and Systemic Diseases?

Qingshan Hou, Yukun Zhou, Jocelyn Hui Lin Goh +19

The advent of foundation models (FMs) is transforming medical domain. In ophthalmology, RETFound, a retina-specific FM pre-trained sequentially on 1.4 million natural images and 1.…

eess.IV2025

Generalist versus Specialist Vision Foundation Models for Ocular Disease and Oculomics

Yukun Zhou, Paul Nderitu, Jocelyn Hui Lin Goh +20

Medical foundation models, pre-trained with large-scale clinical data, demonstrate strong performance in diverse clinically relevant applications. RETFound, trained on nearly one m…

cs.CV2025

FusionFM: Fusing Eye-specific Foundational Models for Optimized Ophthalmic Diagnosis

Ke Zou, Jocelyn Hui Lin Goh, Yukun Zhou +11

Foundation models (FMs) have shown great promise in medical image analysis by improving generalization across diverse downstream tasks. In ophthalmology, several FMs have recently…