Deepti R. Bathula

Dr. Bathula is an Assistant Professor in the Department of Computer Science and Engineering at IIT Ropar. She graduated from the University of Auckland, New Zealand in 2002 with a Bachelor of Engineering degree in Computer Systems. After a brief stint as a Software Engineer in the healthcare industry, she joined the graduate program at Yale University and earned her PhD in Biomedical Engineering in May 2009. Her doctoral dissertation involved statistical modeling of brain activation patterns for robust analysis of Functional Magnetic Resonance Imaging (fMRI) data. Prior to joining IIT Ropar, she worked as a Research Associate at Oregon Health & Science University.

Her research interests focus on applying computational and statistical methods to address challenges in medical imaging. Particularly, development of image/signal processing, pattern recognition and machine learning techniques to assist in biomedical image analysis and diagnostic decision making.

Doctoral Students

Anoop J. Thomas

Anoop is currently working on reducing the inter-scanner variability in activation in multicenter fMRI data. Before joining as a PhD student here at IIT Ropar, he worked as a Research Assistant in the Python group of FOSSEE at IIT Bombay where he was involved in the development of course content material, conducting workshops/conferences on Python. He completed my B.Tech from the University of Kerala, and worked as a lecturer for an year before joining FOSSEE.


Apoorva Sikka

Apoorva graduated from GWECA Ajmer with a B.Tech. in Computer Engineerintg. She pursued her Masters from Malviya National Institute of Technology Jaipur in Computer Engineering. Her interests are in Computational Neuroimaging, applications of machine leaning to neuroimaging. Her current work focuses on the identifying Imaging Biomarkers that will help in detecting people who are at a risk of developing Alzheimer’s Disease using various machine learning techniques.



Tara Chand

Tara Chand earned his B.Tech and M.Tech degrees in Cognitive Neuroscience from the Centre for Converging Technologies, University of Rajasthan, Jaipur.  His research areas focus on the functional connectivity of the brain. currently, he is working towards exploring the application of different time series similarity metrics on fMRI data to capture both linear and nonlinear trends. He is currently pursuing his PhD at University of Tuebingen, Germany.




Vishav Jyoti

Vishav Jyoti earned her M.Tech in Computer Science & Engineering with distinction from the Department of CSE at Punjabi University Patiala. She is currently working on DST project entitled “Neuroimaging: Towards Integrated Analysis of Multi-site Functional MRI Data”. Her overall research interests include: Medical Imaging, Digital Image Processing, MRI and f-MRI data analysis. She is currently pursuing her PhD at IIT Gandhinagar.