Lab Introduction


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


BIIC lab conducts fundamental and applied research in human-centered behavioral signal processing (BSP) - an interdisciplinary research field (pioneered by Prof. Shrikanth Narayanan) across behavior science and engineering. We take firm belief in the following core objectives:

  1. Data-driven → Let data tell the story
  2. Human-centric → Computing for, of, by humans
  3. Algorithmic-derived → Handling human variabilities with principled mathematical framework
  4. Domain-aware → Make sure it has grounded societal impact
  5. Integrity → Science only matters if it is real and rigorous

The BIIC objective is to develop novel human-centric technologies to “computationally innovate human-centric analytics enabling next-generation decision intelligence”. These human-centric analytics modeling heterogeneous human behaviors in a domain-aware & scientifically-relevant manner with mathematically-principled framework.


BIIC lab members focus on conducting tightly-integrated interdisciplinary research with the following core computational techniques:

  1. Multimodal Signal Processing
  2. Machine Learning
  3. Large-scale Human-centric Data Collection

We are at the intersection between signal processing, machine learning with grounded real-world applications of affective computing, health, education, psychology, neuro-science, etc.

⇒ We provide quantitative next-generation decision-making analytics that aim at transforming the status-quo!

Come talk to us if you are interested in our Research