Research Projects

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Note for i-students : Applicants with fellowships (CSIR, UCG-NET, etc.) are encouraged to apply for all projects. Please note that projects marked with an asterisk will only consider applications from i-students with fellowships.

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Project Code UQ Supervisor IITD Supervisor Research Themes Title Student Type (i/q) Keywords Discipline Status
UQIDAR 00207 Associate Professor Anders Eriksson, School of Information Technology and Electrical Engineering Associate Professor Chetan Arora, Department of Computer Science & Engineering TT Parametric Deep Neural Networks for Computer Vision Problems i/q computer vision an ideal student for this project will have an undergraduate or masters degree in computer science, or electrical engineering. the student would have done courses in computer vision and machine learning at undergraduate/masters level. he/she would ha Student Required