Lab Members

Graduate Students

  • Ye Tian

    • Ph.D. Student in Biomedical Engineering

    Ye is a first-year Ph.D. student in Biomedical Engineering. He works on deep learning in glaucoma progression detection using OCT images and visual fields.

    He also has interested in deploying diffusion models in OCT super-resolution for portable applications.

  • Michael Lau

    • CS Ph.D. Student

    Michael is a recent MS Electrical Engineering graduate from Columbia University with an undergraduate degree in Computer Engineering from the University of Illinois at Urbana-Champaign. 

    His interests lies in developing robust algorithms for healthcare applications.

  • Tri (Tom) Le, M.S. in CS

    • CS Master's Student

    Tom is a first year Master's student in Computer Science. He has a keen interest in applying Machine Learning to the healthcare sector, with a particular focus on biomedical imaging. 

    He is currently researching and developing a system designed to assist novice ophthalmologists in analyzing Optical Coherence Tomography images. This system leverages the eye gaze patterns of seasoned clinicians, utilizing Mask Autoencoder and attention-based LSTM. Tom earned his Bachelor's degree in Computer Science from the University of Melbourne.

  • Roshan Kenia

    • CS Master's Student

    Roshan is a first year Master’s student studying Computer Science whose focus is at the intersection of machine learning and biomedical imaging. He is currently working on using Vision Transformer (ViT) models to capture the eye-tracking of clinicians as they view OCT reports. He obtained his undergraduate degree in Computer Science from Stony Brook University. 

    Roshan is interning at MIT Lincoln Laboratory.

  • Sanmati Choudhary

    • CS Undergraduate Student

    Sanmati is a CS undergraduate working on using unsupervised machine learning/deep learning techniques (such as categorical embeddings) to extract meaningful clusters from expert clinician eye movement data.  By understanding the decision-making process of experts through their eye movements, her work has the potential to aid in medical education and in developing automated disease diagnosis systems.

  • Saanvi Aima

    • CS & Stats Undergrad Student

    Saanvi is a CS-Statistics undergraduate student interested in the application of artificial intelligence in healthcare. She is working on the development of a multimodal text-image-gaze model. 

    This would serve as a foundational tool to help radiologists identify regions of interest for glaucoma diagnosis using OCT reports. It would also help create a more interpretable and trustworthy automated diagnostic system.

  • Allison Cui

    • CS Undergrad Student

    Allison is a CS undergraduate student interested in machine learning applications in the field of ophthalmology and medicine. 

    She works on the Machine Learning Approach to Detect Subtle Differences between Normal and Anisometropic Eye Movements. She is also learning image classification techniques in the context of eye-movement data to use deep learning methods to detect glaucoma progression and predict future visual fields. 

  • Angel (Leyi) Cui

    • CS Undergrad Student

    Angel is a CS undergraduate student interested in applying machine learning to the field of healthcare and designing and developing useful and usable software to aid clinicians and improve healthcare software.

    She is working on training experts’ eye fixation data to understand glaucoma results and developing helpful tools for clinicians and medical students to facilitate learning and diagnostic processes.

  • Mingyang Zang

    • BME Ph.D. Student

    Mingyang is a Ph.D. student in Dr. Andrew Laine's Lab, collaborating with AI4VS lab.

    His research interest is computer aided image analysis including classification and segmentation. He is involved in projects on OCT report detection, Vision Field (VF) Mapping prediction, and Posterior Vitreous Opacities (PVOs) segmentation with Dr. Thakoor.