Analytics Lab
Analytics Lab provides a unique meeting point for engineers, social scientists, and data scientists to brainstorm and develop algorithms to extract useful insights from large amounts of raw data. We also provide hands-on training to the students, entrepreneurs, and innovators on the application of various analytical tools and techniques for business decision-making. The Lab mainly houses necessary hardware platforms and software tools for the following domains of research in data analytics:
Healthcare Data Analytics
Business and New Venture Analytics
Financial Data Analytics
Computer Vision
Facilities
An experimental setup for big data analytics platform primarily using open source technologies such as MongoDB, Hadoop Distributed File System (HDFS), Hive, Spark
Programming languages and software: Matlab, Python, R, SPSS, AMOS, Stata, etc.
System Dynamics Modeling and Simulation Tool (Vensim)
Agent-Base Modeling and Simulation (Netlogo)
Health Monitoring Devices to measure BP, pulse rate, BMI, level of physical activity
Simulators and software for robotics applications like Gazebo, ROS, Blender, etc.
CMIE Prowess – performance database of active business enterprises in India
HBS Case study Collection database for Cases, Simulations, short cases, and book chapters.
Purpose
To design and develop data-driven solutions for improving healthcare operations
To design behavioral technologies (at individual as well as at community level based on social networks of individuals) for preventive care using m-Health
To develop emergency service delivery and health insurance models
To use visual cues for localization & mapping applications involving multiple robots
To develop path-planning algorithms for rovers exploring the planet’s surface
To develop business models – investment, funding, competition, valuation – for Indian Start-ups and enterprises to facilitate VCs; Angel Investors; Incubators; and Entrepreneurs to predict and spot business opportunities
To understand business performance and to enable inter-company and intra-temporal comparisons for decision-making
To introduce and practice case-based learning and to keep students updated with world-class cases for learning management practices
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