PhD Candidate: 4th year, EECS Department, Penn State
Group: Information Processing & Algorithms Laboratory
Advisors: Vishal Monga (Penn State), Steven Schiff (NIH)
Research Interests: Computer Vision, Medical Image Analysis, Multimodal AI, Interpretable Machine Learning, Shape Analysis, Biomedical Signal Analysis
Recent News: Dissertation Award - 2026 Dr. Nirmal K Bose Dissertation Excellence Award by Electrical Engineering Department, Penn State. Dissertation Title: Hydrocephalic Etiology Guided Low-Field MRI Analysis.
My research focuses on developing disease-informed and interpretable machine learning and statistical methods for biomedical image analysis, particularly in clinical settings with scarce, noisy, and imperfect data. I incorporate disease etiology, anatomical structure, geometry, and multi-modal information directly into computational models to achieve a balance of performance, robustness, and interpretability. My current research focuses on neonatal hydrocephalus diagnosis and quantitative analysis from low-field MRI, generalizing the framework to histopathology disease grading and biomedical signal (ICP, ECG) analysis. I mentored two Master’s and two Ph.D. students on biomedical AI projects involving hemi-brain growth analysis, high-field MRI/CT segmentation, histopathological disease grading (DBIBD-Net), and intracranial-pressure (ICP) analysis, guiding them in problem formulation, literature review, methodology, experimentation, and technical communication. I also contributed to NIH and NSF proposals through research framing, methodological design, and technical writing.