Affiliated Research Centers
The following departments across the IIITH community are supporting this initiative and bridging the gap between technology and healthcare.
- Cognitive Sciene Lab(CSL)
- Center for Visual Information Technology(CVIT)
- Centre for Computational Natural Sciences and Bioinformatics(CCNSB)
- Language Technologies Research Center (LTRC)
- Machine Learning Lab, IIIT-Hyderabad
- Center for VLSI and Embedded Systems Technology (CVEST)
- Signal Processing and Communications Research Center (SPCRC)
Focus Areas
Healthcare at IHub-Data aspires to foster a culture of AI research where technology advancements are intertwined with the societal impacts at population scale health and well-being. Here are the highlights on the multidisciplinary focus areas that help people to respond thoughtfully and pursue innovative research, create societally useful problem statements, and develop responsible AI solutions in healthcare.
Healthcare and Artificial Intelligence (HAI) internship Program
During the academic year 2020-21, Prof. C V Jawahar, Research Dean, IIITH, Prof. Deva Priyakumar U, Academic Head, iHub-Data and Prof. Bapi Raju S, Healthcare Head, iHub-Data and Dr. Vinod P.K, Assistant Professor played a key role in brewing up this major innovative interdisciplinary internship program that mainly focuses on leveraging artificial intelligence to solve some real-world challenges in the general area of healthcare.
HAI recruits' full-time interns across the country every year especially in the month of February and March. HAI provides opportunities to research fellows to work on our projects and get mentored by IIITH academia and industry. Every year a set of bright students are formally selected for the Masters by Research program at IIITH, as proof of their excellence and efficiency.
HAI 1.0 B (2021-2022)
HAI 1.0 A (2020-2021)

Deep learning in Nephropathology
Nephro-pathology is a discipline focusing on the diagnostic process of kidney diseases (Lupus nephritis, Diabetic nephropathy, Interstitial nephritis, etc.). This project focus on developing tools that help in the identification and characterization of glomeruli in health and disease. This work will involve segmentation and classification of glomeruli.