Notice: Function _load_textdomain_just_in_time was called incorrectly. Translation loading for the sina-ext domain was triggered too early. This is usually an indicator for some code in the plugin or theme running too early. Translations should be loaded at the init action or later. Please see Debugging in WordPress for more information. (This message was added in version 6.7.0.) in /home/uym3hfalurg6/public_html/wp-includes/functions.php on line 6121

Notice: Function _load_textdomain_just_in_time was called incorrectly. Translation loading for the astra domain was triggered too early. This is usually an indicator for some code in the plugin or theme running too early. Translations should be loaded at the init action or later. Please see Debugging in WordPress for more information. (This message was added in version 6.7.0.) in /home/uym3hfalurg6/public_html/wp-includes/functions.php on line 6121
Biophotonics Lab - IIT Madras

IIT Madras – Biophotonics Lab

Biophotonics Lab

Indian Institute of Technology Madras

Announcements

  • [CONGRATULATIONS]

    Ms. Subitcha J. won First prize for the 3-minute thesis presentation titled "New dimensions in breast cancer diagnosis using bi-modal optical spectroscopy" held at the Women in Optics and Photonics in India conference 2023 at IIT Madras, Chennai.

  • [CALL FOR PAPERS]

    Showcase of Photonics Research in India (VSI: WOPI 2023) - Deadline: 31.01.2024 [Click here]

  • [CALL FOR PAPERS]

    Ms. Subitcha J. got featured in the SPIE Women in Optics 2024 planner [Click here]

VIEW ALL EVENTS

About the Lab

Welcome to the Biophotonics lab!

Our focus is on developing non-invasive tools based on optical principles for disease diagnosis. This area is highly application-oriented, while at the same time deeply involved in the basic sciences. Using the physics of light-tissue interaction, we try to extract the chemical composition and architecture of the target tissue to understand the biology of tissue transformation during the progression of diseases. We do simulations for optimal device design, instrumentation, and experimentation at research and clinical application levels. Most projects involve large-scale data analysis and interpretation using machine learning/deep learning techniques. The focus is developing clinically viable non-invasive portable units for conveniently sensing physiological conditions. For more details on our research, please view our publications.

Interested in joining us?

Find out more about joining requirements
and our active research projects here:

Research Interests

Scroll to Top