Lab Introduction


biic lab strives to provide an open, fun, and exciting research environment for students to engage in forefront research topics pushing the boundaries of both scientific discoveries and domain applications geared toward human applications. The aim of the lab is to foster well-rounded, creative, and independent research leaders in taking on multitudes of challenging real-world human behavioral data-modeling tasks bearing high societal significance.


biic lab conducts fundamental and applied research in human-centered behavioral signal processing (BSP) - an interdisciplinary research direction (pioneered by Professor Shrikanth Narayanan) across behavioral science and engineering. We take firm belief in the the following three core values:

  1. Data-driven → Let data tell the story
  2. Domain-aware → Make sure it has impact
  3. Integrity → Science only matters if it is real and rigorous

The biic objective is to develop novel computational algorithms, i.e., behavioral informatics, to model human behaviors during interactions in a domain-aware & scientifically-relevant manner.


biic lab members focus research using the following core mathematical frameworks:

  1. Digital Signal Processing
  2. Machine Learning

We are at an intersection of signal processing and machine learning with grounded applications across human-machine interface, health, education, etc.

⇒ We provide quantitative decision-making computational frameworks that aim to transform the status-quo!

Come talk to us if you are interested in our research !