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Prof. Jabez Christopher    

Assistant Professor,
Dept. of Computer Science and Information Systems

Artificial Intelligence and Expert Systems, Decision Theory, Fuzzy Logic and evolutionary algorithms, Swarm intelligence
Birla Institute of Technology & Science, Pilani
Hyderabad Campus
Jawahar Nagar, Kapra Mandal
Dist.-Medchal-500 078
Telangana, India

Funded Projects

Education for Visually Impaired School Children in Tamil Nadu through AI-Assisted Skills

Duration of the project : 5 Years (Oct-2023 to Oct-2028)

Funding Details : Indian Council of Social Science Research (ICSSR - Ministry of Education); Collaborative Research Proposals on Longitudinal Studies in Social and Human Sciences. 

SUMMARY
This project uses AI, Fuzzy Logic  and digital learning technology to develop learning systems tailored for visually impaired students. Using AI, specifically a Fuzzy Inference System (FIS), it adjusts learning content based on individual student abilities, creating personalized and effective educational experiences. It intends enhancing access to quality education for visually impaired learners. The project promotes social inclusion by empowering visually impaired students with personalized learning, fostering educational equity, and enhancing their integration into society for long-term social and economic upliftment.
It is a collaborative work with Prof. Anjum Khan (Principal Ivestigator), Prof. Rachel & Prof. Sreeja, Department of English, Avinashilingam Institute for Home Science and Higher Education for Women, Coimbatore, Tamil Nadu (Coordinating Institute).

Interpretation of Tuberculin Reaction Using Medical Photography and Computer Aided Diagnosis

Duration of the project : 2 Years (Dec-2019 to Mar-2022)

Funding Details : DST-SERB, Govt. of India - Startup research grant (SRG) 

SUMMARY
In this project, Medical photography (not medical imaging) is primarily used to record Tuberculin skin test images. The images captured from the forearm are processed for extracting relevant features. The image of the forearm and the relevant features are recorded twice: first, at the time of injecting the tuberculin fluid into the skin; finally, after 48 hours from the time of injection. The difference in the features of the wheal may enhance clinical decision making. The proposed system eliminates the traditional error-prone interpretation process of the Tuberculin Skin Tests. Using Computer Aided Diagnosis would eliminate the bias involved in the process of medical observation and reporting, moreover the patient need not report to the health centre in person.