Received the Best Student Project Award (First Rank - ITU 2024), Class Rank 1 (2025), and secured competitive fellowships such as the Mercedes-Benz Fellowship (2025) and the NSF Grassroots Fellowship (2025).
Research Experience
Research experience includes toxic comment detection (using extended LSTM), real-time anomaly detection (for cyber threats), and PCOS diagnosis (using extreme gradient boosting). He developed an extended LSTM (xLSTM) integrated within a BERT-based deep learning framework to enhance minority-class detection and improve interpretability.
Education
Insufficient information on educational background.
Background
Research interests include the trustworthiness of deep learning systems, explainability of algorithms, and the ability of data-driven systems to address real-world problems. His experiences in the library and lab have shaped his scientific and academic journey.
Miscellany
Personal interests lie in using scientific research to solve real-world problems, particularly in promoting fairness and inclusivity in the field of AI.