Farnoush Banaei-Kashani, Ph.D.

Assistant Professor
Computer Science and Engineering

Dr. Farnoush Banaei-Kashani:
• Director of the Big Data Management and Mining Laboratory (BDLab)
• Director of the Big Data Science and Engineering PhD Fellowship Program
• Director of Masters Concentration in "Data Science in Biomedicine"

Expertise:  (Big) Data Management and Mining; Data Science

Phone: (303) 315-0116

Project Examples:

Human Gait Analysis by Mining and Classification of Skeletal Data

Spatiotemporal Sequence Data Management and Mining (STSeq)
Multivariate Spatiotemporal Sequences (MVS) can capture the concurrent motions of the moving objects (e.g., joints in skeletal data, players in a sports field, and vehicles in a transportation network). These sequences are ubiquitous and provide exceptional opportunities to derive interesting insights about the behavior of moving object masses. We are working toward introducing efficient and novel algorithms for mining, indexing and classification of patterns embedded in MVS data.

Point Cloud Data Management and Mining (PCD)
Point Cloud Data (PCD) is a representation of objects in 2D and 3D using a (often) large cloud of points that embody the object. PCDs can be acquired by several technologies such as LIDAR and RGBD cameras (e.g., Microsoft Kinetic), and are used in a variety of modeling and mapping applications, e.g., dike and flood modeling, building mapping, SLAM (Simultaneous Localization And Mapping). Management and mining of PCDs is challenging due to both large size/volume of the data and high rate of data generation. In this project, we develop efficient dynamic index structures for real-time querying of PCDs to enable effective management and mining of this type of Big Data.