AI for Healthcare
My research pursuits focus on advancing AI for healthcare by developing predictive models for the analysis and interpretation of complex biomedical data. I am particularly interested in developing innovative AI solutions for precision medicine, especially by leveraging multimodal data. My work spans deep learning, graph representation learning, large language models, and natural language processing.
Hi, I am Shaika Chowdhury (সাইকা চৌধুরী). Welcome to my personal website! I am currently a Postdoctoral Research Associate in Bioinformatics at the Bozdag Lab in the Department of Computer Science and Engineering, University of North Texas. I work on AI applications for precision medicine through multimodal analysis and integration of real-world healthcare data.
At UNT, I am actively involved in mentoring and training undergraduate and graduate students, contributing to grant writing, and publishing and presenting research in conferences and journals. Previously, I was a Postdoctoral Researcher/Fellow in the Department of AI and Informatics Research at Mayo Clinic. I received my Ph.D. in Computer Science from the University of Illinois Chicago in December 2021. During my doctoral studies, I also completed internships at IQVIA, Siemens Healthineers, and Target.
Latest
A day packed with engaging discussions and fun at the Lab Retreat 2025 at UNT Frisco!
I am excited to join the Bozdag Lab as a Postdoctoral Research Associate in Bioinformatics in September 2025!
Paper titled "Probing Fine-grained and Coarse-grained Embeddings with Large Language Models for Patient-Trial Matching using Siamese Neural Network" is accepted to the AMIA 2025 Annual Symposium as a poster!
My joint work titled "Advancing Efficacy Prediction for EHR-based Emulated Trials in Repurposing Heart Failure Therapies" has been accepted to the npj Digital Medicine 2025!
Paper I co-authored titled "Synoptic Reporting by Summarizing Cancer Pathology Reports using Large Language Models" is accepted to npj Health Systems 2025!
My paper titled "Stratifying heart failure patients with graph neural network and transformer using Electronic Health Records to optimize drug response prediction" is accepted to the Journal of the American Medical Informatics Association 2024!
I presented my work titled "Evaluation of GPT-3 for Anti-Cancer Drug Sensitivity Prediction" at the AMIA Informatics Summit 2024.
I presented my work titled "Drug Response Prediction and Phenomapping for Personalized Healthcare Management using EHR: A Graph-based Deep Learning Approach" at the AMIA Clinical Informatics Conference 2024.
My paper titled "Evaluating Drug Effectiveness for Antihypertensives in Heart Failure Prognosis: Leveraging Composite Clinical Endpoints and Biomarkers from Electronic Health Records" is accepted to the 14th ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics 2023, which I also presented at the conference!
Paper I co-authored titled "BETA: a comprehensive benchmark for computational drug-target prediction" is accepted to Briefings in Bioinformatics 2022!
Links
Miscellaneous
lovely succulents 🌼
Small creature, big focus.