Research Projects

View All Projects

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.

View Projects by Status

View Projects by Research Theme

Project Code UQ Supervisor IITD Supervisor Research Themes Title Student Type (i/q) Keywords Discipline Status
UQIDAR 00140 Associate Professor Zuduo Zheng, School of Civil Engineering Professor K. Ramachandra Rao, Department of Civil Engineering TT, TS Developing Effective Traffic Congestion Management Strategies for Road Transport Systems with Traditional, Connected and Automated Vehicles i/q driverless vehicles, connected vehicles, traffic congestion transport engineering, control engineering, mathematics and statistics, computer science Position Filled - Janci Rani P
UQIDAR 00157 Professor Markus Barth, School of Information Technology and Electrical Engineering Professor Anrup Singh, Department of Biomedical Engineering HA, TT Advancing Cardiac Magnetic Resonance Imaging using Machine Learning i/q note: i-students must have own scholarship to apply (CSIR, UCG-NET, etc) mri, medical imaging, cardiac magnetic resonance, image analysis biomedical engineering, computer science, physics and related, electrical engineering Student Required
UQIDAR 00166 Professor David Reutens, Centre for Advanced Imaging Professor Rahul Garg, Department of Computer Science & Engineering HA, TT Information flow in the normal and epileptic brain i/q neuroimaging, epilepsy, data science, machine learning biomedical engineering, applied mathematics, computer science/electronics, neuroscience/neuroimaging, cognitive science/physiology Position Filled - Puneet Dheer
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 Position Filled - Nikhil Jangamreddy
UQIDAR 00214 Associate Professor Kai-Hsiang Chuang, Queensland Brain Institute (QBI) Professor Rahul Garg, Department of Computer Science & Engineering TT Develop ultrafast technique for high-resolution imaging of brain function i/q imaging, brain, machine learning physics, engineering, computer science Student Required