Vineeth N Balasubramanian

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Vineeth N Balasubramanian


Assistant Research Professor


Computer Science Engineering

Joined CUbiC




Former ASU student.

Research Profile

Vineeth joined CUbiC in August 2005 as a PhD student in the Department of Computer Science and Engineering (now, the School of Computing and Informatics). Before coming to CUbiC, he had worked on video segmentation and mosaicing in the MPEG domain as part of his Masters thesis in India. At CUbiC, his initial work included projects on surgical skill analysis with the Banner Good Samaritan hospital, and on scientific visualization of medical imaging data. Currently, he works on pattern recognition problems related to face analysis, with a focus on head pose estimation. His research work is centered on coming up with confidence measures associated with pattern recognition algorithms. His broad research interests include computer vision, pattern recognition, machine learning, human computer interaction with an emphasis towards high-dimensional data analysis, learning theory, and statistical approaches in pattern recognition.


Learning Attention Based Saliency in Videos from Human Eye Movements
S. Nataraju, V.N. Balasubramanian, S. Panchanathan,
Online Active Learning using Conformal Predictions
V. Balasubramanian, S. Chakraborty, S. Panchanathan,
Predicting risk of complications following a Drug Eluting Stent Procedure: a SVM approach for imbalanced data
R. Gouripeddi, V. Balasubramanian, J. Harris, A. Bhaskaran, R. Siegel, S. Panchanathan,
Multiple Cue Integration in Transductive Confidence Machines for Head Pose Classification
V. Balasubramanian, S. Chakraborty, S. Panchanathan,
Human-Centered Machine Learning in a Social Interaction Assistant for Individuals with Visual Impairments
V. Balasubramanian, S. Chakraborty, Krishna S, S. Panchanathan,


Individuals with cognitive, developmental and learning disabilities – in particular, Autism Spectrum Disorders (ASD) - have a significant social communication impairment, a situation that can often lead to social isolation. Reducing the need for formal care services for…

FacePix is a face image database created at the Center for Cognitive Ubiquitous Computing (CUbiC) at Arizona State University, and made available free of charge to the worldwide research community. In the first version of the FacePix database, called FacePix(30), there…

The Tabletop Interaction Assistant, part of the larger Social Interaction Assistant research project, consists of a webcam on a pan-tilt mechanism used to track human faces, regardless of whether the person is directly facing the camera. Additionally, the video collected…

Motivated by the vision of the future, automated analysis of nonverbal behavior, and especially of facial behavior, has attracted increasing attention in Computer Vision, Pattern Recognition, and Human-Computer interaction. With facial expression being one of the most…

The goal of the project is to help people who are blind or visually impaired to shop independently. Present day shopping environments are centered around the needs of the consumer, and they aim to facilitate convenient access to different product lines varying from…