Personal profile
Education
B.E., M.Tech., Ph.D
Research Interests
Area of Interest
Artificial Intelligence, Machine Learning, Data Science, Health Informatics and Casual Inference.
Area of Expertise
Artificial Intelligence, Machine Learning, Data Science, Health Informatics and Casual Inference.
Area of Research
Artificial Intelligence, Machine Learning, Data Science, Health Informatics and Casual Inference.
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Dive into the research topics where Krishnaraj Chadaga is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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AlzStack: Forecasting early-onset Alzheimer's with an explainable AI system using multiple data balancing techniques
Modali, V. A., Pavanya, M., Arjunan, V., Cenitta, D., Sampathila, N., Kamath, R. & Chadaga, K., 06-2026, In: Global Epidemiology. 11, 100261.Research output: Contribution to journal › Comment/debate › peer-review
Open Access -
AlzStack: Forecasting early-onset Alzheimer's with an explainable AI system using multiple data balancing techniques
Modali, V. A., Pavanya, M., Arjunan, R. V., Cenitta, D., Sampathila, N., Kamath, R. & Chadaga, K., 06-2026, In: Global Epidemiology. 11, 100235.Research output: Contribution to journal › Article › peer-review
Open Access1 Link opens in a new tab Citation (Scopus) -
Countering synthetic realities: Advances, challenges, and future directions in deepfake image detection
Prabhu, O., Naik, S. S., BK, P., Prabhu, S. & Chadaga, K., 06-2026, In: Systems and Soft Computing. 8, 200476.Research output: Contribution to journal › Review article › peer-review
Open Access -
DVTPRED: an explainable machine learning framework for the early prediction of deep vein thrombosis
Chadaga, K., Muralikrishna, H., Sampathila, N., Chadaga, R. & Bhandage, V., 01-01-2026, In: Journal of Intelligent Systems. 35, 1, 20250051.Research output: Contribution to journal › Article › peer-review
Open Access -
Explainable machine learning models for predicting current and voltage in photovoltaic systems
Dinakar, A., Cenitta, D., Arjunan, R. V., Bhandage, V. & Chadaga, K., 05-2026, In: Energy Conversion and Management: X. 30, 101627.Research output: Contribution to journal › Article › peer-review
Open Access