Rajashik Datta
Research Scholar @University Of Calcutta, Kolkata
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WORK HISTORY
Research Scholar @University Of Calcutta, Kolkata
Kolkata, IN
Engineered FHFAM (FH-FAM), a fuzzy-hypergraph feature selection algorithm, achieving the best mean accuracy (81.43%) and best mean feature reduction (89.28%) across 15 agriculture/remote-sensing datasets (5/15 wins) with 11.08s average runtime and statistically significant accuracy gains over key baselines (Wilcoxon p < 0.05)- Proposed SIFHFAM, a stage-wise intuitionistic-fuzzy hypergraph selector with a monotone submodular coverage objective and greedy (1−1/e) guarantee, delivering the top average accuracy (≈84%) while pruning ≈99% features (typically retaining <2%) across 14 high-dimensional benchmarks in ∼0.1s/run under 10× repeated 75/25 train-test splits.
EDUCATION
Institute Of Engineering and Management
Bachelor of Technology - BTech, Computer Science
DAV Schools Network
High School, Pure Science
Nirmala Convent School, Siliguri
Junior School, Middle School, Science
ABOUT RAJASHIK DATTA
Research Intern @ University of Nebraska-Lincoln | Research Scholar @ University of Calcutta | CSE(AI) Senior @ IEM | Interests : AIML, Computer Vision, xAI, GenAI
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