Artificial Intelligence and Data Analytics Research (AIDAR) Laboratory
is a part of Department of Electrical Engineering at
Indian Institute of Technology Kanpur, India and is led by Prof. Nishchal K. Verma.
The research at AIDAR Lab mainly focuses on Artificial Intelligence,
Deep Learning, Machine Learning,
Computer Vision, Cyber Physical Systems, and
The primary goal of the lab is to develop technologies and tools which address the various complex and challenging problems affecting the real-world especially where traditional approaches are not effective.
In parallel to theoretical research, new applications like Future Image Frame Generator using smart computing devices i.e. Smartphone, palmtop, Vision based Inventory Management System, Vision based Automated Guided Vehicle, Deep Learning Strategies in BioInformatics, Image Classification and Condition Based Monitoring are being developed. Apart from this, Transducers and Instrumentation Virtual Laboratory has been setup for UG students for conducting experiments online and offline to better understand the working of various transducers and related instruments.
Artificial Intelligence and Data Analytics Research (AIDAR) Laboratory,
Dept. of Electrical Engineering, IIT Kanpur invites applications from
outstanding, promising, bright and passionate Students (3rd/4th, B.Tech.)
having secured CPI>=9.0 and interested in working for at least six months
or more for some long-term research project opportunities in the following areas:
1) Artificial Intelligence and Machine Learning
2) Computer Vision
3) Autonomous Navigation and Localization
4) 3D Object reconstruction
Please note that:
a) Stipend (as per the guidelines of DoRD, IITK) and a Project completion certificate will be offered to the Students upon their successfully completing the assigned projects within the prescribe time frame.
b) Only students (3rd/4th, B.Tech.) having secured CPI>=9.0 and interested in working for at least six months or more should only apply through the following link:
The positions are limited and final selection will be done through the interview of shortlisted students.